cuda.parallel: Support structured types as algorithm inputs #3218

shwina · 2024-12-25T13:08:47Z

Description

Closes #3135.

This PR enables using struct-like types as algorithm inputs.

Example

Click to see example

Below, we define a custom type called Pixel (composed of RGB values), and perform a reduction on an array of Pixel objects to find the one with the largest g component:

from cuda.parallel.experimental.algorithms import reduce_into
from cuda.parallel.experimental.struct import gpu_struct

import numpy as np, cupy as cp

# define a struct type:
@gpu_struct
class Pixel:
    r: np.int32
    g: np.int32
    b: np.int32

# binary op that operates on our custom type:
def max_g_value(x, y):
    return x if x.g > y.g else y

# initialize input, output and initial data:
d_rgb = cp.random.randint(0, 256, (10, 3), dtype=np.int32).view(Pixel.dtype)
d_out = cp.zeros(1, Pixel.dtype)
h_init = Pixel(0, 0, 0)

# create reducer object:
reducer = reduce_into(d_rgb, d_out, max_g_value, h_init)

# compute and allocate temp storage:
temp_storage_bytes = reducer(None, d_rgb, d_out, len(d_rgb), h_init)
d_temp_storage = cp.zeros(temp_storage_bytes, dtype=np.uint8)

# perform reduction:
_ = reducer(d_temp_storage, d_rgb, d_out, len(d_rgb), h_init)

# # # results:
print()
print("Input RGB values:")
print("-----------------")
print(d_rgb.get())
print()
print("Value with largest g component:")
print("-------------------------------")
print(d_out.get())
print()

# output:
Input RGB values:
-----------------
[[(148,  54,  81)]
 [( 22, 249, 159)]
 [(115, 206,  87)]
 [(156, 190, 239)]
 [( 99, 191,   7)]
 [(232, 169,  46)]
 [( 41,  90, 230)]
 [(214, 134, 202)]
 [( 50,  80, 129)]
 [(169, 169,  12)]]

Value with largest g component:
-------------------------------
[(22, 249, 159)]

Implementation

The primary addition in this PR is the decorator @gpu_struct. It's a user-facing decorator, which enables them to define a struct similar to a dataclass. Under the hood, @gpu_struct makes a numba type corresponding to the struct, and enables it to be used in device functions (such as user defined binary and unary operations). As far as the CCCL C library is concerned, instances of this type are treated as STORAGE_T.

⚠️ This PR supports "flat" (non-nested) struct dtypes. I think it should be possible to add support for nested structs, but would prefer to do that in a future PR.

Why not use structured dtypes?

Instead of having the user define a custom dataclass-like struct type, we could have them pass numpy structured dtypes instead. However, this was rejected. The primary reason is that for Python functions accepting/returning structured dtypes, numba generates device functions accepting/returning pointers to structs. This is problematic for two reasons: (1) In the context of CCCL, binary/unary ops are expected to take arguments of type T rather than T*, and (2) memory management - who will keep the T* returned by the binary operation of a reduction alive?

Consider the following device function:

def max_g_value(x, y):
    return x if x['g'] > y['g'] else y

Below are the PTX generated by numba after compiling the function for (1) inputs as raw struct dtypes, (2) inputs as "wrapper" types. Note that for raw structs, the PTX code expects pointer-to-structs as input:

Raw struct input PTX

//
// Generated by NVIDIA NVVM Compiler
//
// Compiler Build ID: CL-35059454
// Cuda compilation tools, release 12.6, V12.6.85
// Based on NVVM 7.0.1
//

.version 8.5
.target sm_50
.address_size 64

        // .globl       max_g_value
.common .global .align 8 .u64 _ZN08NumbaEnv8__main__11max_g_valueB2v1B92cw51cXTLSUwv1sDUaKthqqNgoKmjgOR3W3CwAkMXLaJtQYkOIgxJU0gCqOkEJoHkbttqdVhoqlspQGNFHSgJ5BnXagIAE6RecordILi598EE6RecordILi598EE;
.visible .func  (.param .b64 func_retval0) max_g_value(
        .param .b64 max_g_value_param_0,
        .param .b64 max_g_value_param_1
)
{
        .reg .pred      %p<2>;
        .reg .b32       %r<3>;
        .reg .b64       %rd<4>;


        ld.param.u64    %rd1, [max_g_value_param_0];
        ld.param.u64    %rd2, [max_g_value_param_1];
        ld.u32  %r1, [%rd1+4];
        ld.u32  %r2, [%rd2+4];
        setp.gt.s32     %p1, %r1, %r2;
        selp.b64        %rd3, %rd1, %rd2, %p1;
        st.param.b64    [func_retval0+0], %rd3;
        ret;

}

Wrapper type input

//
// Generated by NVIDIA NVVM Compiler
//
// Compiler Build ID: CL-35059454
// Cuda compilation tools, release 12.6, V12.6.85
// Based on NVVM 7.0.1
//

.version 8.5
.target sm_50
.address_size 64

        // .globl       max_g_value
.common .global .align 8 .u64 _ZN08NumbaEnv8__main__11max_g_valueB2v1B92cw51cXTLSUwv1sDUaKthqqNgoKmjgOR3W3CwAkMXLaJtQYkOIgxJU0gCqOkEJoHkbttqdVhoqlspQGNFHSgJ5BnXagIAE13StructWrapper13StructWrapper;

.visible .func  (.param .align 4 .b8 func_retval0[12]) max_g_value(
        .param .b32 max_g_value_param_0,
        .param .b32 max_g_value_param_1,
        .param .b32 max_g_value_param_2,
        .param .b32 max_g_value_param_3,
        .param .b32 max_g_value_param_4,
        .param .b32 max_g_value_param_5
)
{
        .reg .pred      %p<2>;
        .reg .b32       %r<10>;


        ld.param.u32    %r1, [max_g_value_param_0];
        ld.param.u32    %r2, [max_g_value_param_1];
        ld.param.u32    %r3, [max_g_value_param_2];
        ld.param.u32    %r4, [max_g_value_param_3];
        ld.param.u32    %r5, [max_g_value_param_4];
        ld.param.u32    %r6, [max_g_value_param_5];
        setp.gt.s32     %p1, %r2, %r5;
        selp.b32        %r7, %r3, %r6, %p1;
        max.s32         %r8, %r2, %r5;
        selp.b32        %r9, %r1, %r4, %p1;
        st.param.b32    [func_retval0+0], %r9;
        st.param.b32    [func_retval0+4], %r8;
        st.param.b32    [func_retval0+8], %r7;
        ret;

}

(for posterity, the PTX generated can be viewed by compiling the code for output type "ptx" in this function and running the unit test introduced in this PR).

Note to reviewers

The API here is a little awkward, and I definitely invite suggestions for improvement. However, we may want to consider iterating on the API/implementation in follow-up PRs. In an offline discussion with @gevtushenko, we discussed that as a first pass, it's sufficient that we have some way to work with structs from Python so that the corresponding C codepath is tested.

Checklist

New or existing tests cover these changes.
The documentation is up to date with these changes.

copy-pr-bot · 2024-12-25T13:08:51Z

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shwina · 2024-12-25T13:32:24Z

/ok to test

shwina · 2024-12-25T13:48:02Z

/ok to test

python/cuda_parallel/cuda/parallel/experimental/algorithms/reduce.py

python/cuda_parallel/cuda/parallel/experimental/_structwrapper.py

github-actions · 2024-12-25T14:13:38Z

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shwina · 2025-01-07T21:01:49Z

/ok to test

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shwina · 2025-01-07T21:38:31Z

/ok to test

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github-actions · 2025-01-08T18:13:26Z

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leofang

I don't follow the section "Why not use structured dtypes?", but this LGTM.

python/cuda_parallel/cuda/parallel/experimental/struct.py

python/cuda_parallel/tests/test_reduce.py

leofang · 2025-01-10T07:16:50Z

python/cuda_parallel/tests/test_reduce.py

@@ -550,3 +551,30 @@ def binary_op(x, y):
    d_in = cp.zeros(size)[::2]
    with pytest.raises(ValueError, match="Non-contiguous arrays are not supported."):
        _ = algorithms.reduce_into(d_in, d_out, binary_op, h_init)
+
+
+def test_reduce_struct_type():


Q: why do we repeat the same test here? I thought test_reduce_api.py also gets tested?

Yes, but at the moment the way our documentation examples work is by literalinclude'ing the tests from test_reduce_api.py.

There's no technical reason we can't just literalinclude the tests from test_reduce.py directly. But I do like keeping all the examples together in a separate file.

I'd like to move away from this to proper doctests (although maybe that should wait until our documentation system change away from repo_man). cc: @NaderAlAwar for viz as we briefly chatted about that as well.

Same question asked differently: What is lost if we delete this copy? (Why do you want it here, too?)

tests in this module are primarily for testing correctness

tests in the module test_reduce_api.py are didactic and primarily for teaching the API

We might choose to change the tests in test_reduce_api.py so that they illustrate a concept more clearly, or they might disappear altogether in favor of doctests. Tests in this module are far less likely to be deleted.

We could get rid of test_reduce_api.py altogether and instead have the documentation reference tests directly from this module, but again, it seems cleaner to have all the documentation examples together in a single module.

FWIW, I had terrible run-ins with non-trivial copy-pasted code. E.g. I thought I fixed the problem already not realizing there are two copies, or being confused about which is which in the heat of the moment, etc.

My strong preference would be to delete the copy here. As long as you have me as a reviewer, there will be someone asking a lot of questions if you want to remove it completely without giving a good explanation :-)

I.e. if/when you get rid of test_reduce_api.py, I'd be paranoid about making sure no tests are losts.

My strong preference would be to delete the copy here.

I removed it in 75b65ef

github-actions · 2025-01-14T15:35:10Z

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NaderAlAwar

Looks good

NaderAlAwar · 2025-01-14T15:40:49Z

python/cuda_parallel/cuda/parallel/experimental/algorithms/reduce.py

-            cccl.host_array_to_value(h_init),
+            cccl.to_cccl_value(
+                h_init if isinstance(h_init, np.ndarray) else h_init._data
+            ),


Minor point, but I feel like it would be more readable to extract this expression to a variable and pass that in.

Given @rwgk's concerns here as well (#3218 (comment)), I've made it so that to_cccl_value() accepts a GpuStruct in addition to ndarray:

e75bc7c

NaderAlAwar · 2025-01-14T15:41:13Z

python/cuda_parallel/cuda/parallel/experimental/algorithms/reduce.py

-            cccl.host_array_to_value(h_init),
+            cccl.to_cccl_value(
+                h_init if isinstance(h_init, np.ndarray) else h_init._data
+            ),


same comment as above

rwgk · 2025-01-14T16:42:39Z

python/cuda_parallel/cuda/parallel/experimental/struct.py

@@ -0,0 +1,136 @@
+from dataclasses import dataclass


Do we need to add copyright notices?

(I think some existing files are missing copyright notices, too).

Fixed in 8ea0fc9

github-actions · 2025-01-14T21:07:55Z

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#	Runner
1	`linux-amd64-gpu-v100-latest-1`

) * Introduce gpu_struct decorator and typing * Enable `reduce` to accept arrays of structs as inputs * Add test for reducing arrays-of-struct * Update documentation * Use a numpy array rather than ctypes object * Change zeros -> empty for output array and temp storage * Add a TODO for typing GpuStruct * Documentation udpates * Remove test_reduce_struct_type from test_reduce.py * Revert to `to_cccl_value()` accepting ndarray + GpuStruct * Bump copyrights --------- Co-authored-by: Ashwin Srinath <[email protected]>

implement `add_sat` split `signed`/`unsigned` implementation, improve implementation for MSVC improve device `add_sat` implementation add `add_sat` test improve generic `add_sat` implementation for signed types implement `sub_sat` allow more msvc intrinsics on x86 add op tests partially implement `mul_sat` implement `div_sat` and `saturate_cast` add `saturate_cast` test simplify `div_sat` test Deprectate C++11 and C++14 for libcu++ (#3173) * Deprectate C++11 and C++14 for libcu++ Co-authored-by: Bernhard Manfred Gruber <[email protected]> Implement `abs` and `div` from `cstdlib` (#3153) * implement integer abs functions * improve tests, fix constexpr support * just use the our implementation * implement `cuda::std::div` * prefer host's `div_t` like types * provide `cuda::std::abs` overloads for floats * allow fp abs for NVRTC * silence msvc's warning about conversion from floating point to integral Fix missing radix sort policies (#3174) Fixes NVBug 5009941 Introduces new `DeviceReduce::Arg{Min,Max}` interface with two output iterators (#3148) * introduces new arg{min,max} interface with two output iterators * adds fp inf tests * fixes docs * improves code example * fixes exec space specifier * trying to fix deprecation warning for more compilers * inlines unzip operator * trying to fix deprecation warning for nvhpc * integrates supression fixes in diagnostics * pre-ctk 11.5 deprecation suppression * fixes icc * fix for pre-ctk11.5 * cleans up deprecation suppression * cleanup Extend tuning documentation (#3179) Add codespell pre-commit hook, fix typos in CCCL (#3168) * Add codespell pre-commit hook * Automatic changes from codespell. * Manual changes. Fix parameter space for TUNE_LOAD in scan benchmark (#3176) fix various old compiler checks (#3178) implement C++26 `std::projected` (#3175) Fix pre-commit config for codespell and remaining typos (#3182) Massive cleanup of our config (#3155) Fix UB in atomics with automatic storage (#2586) * Adds specialized local cuda atomics and injects them into most atomics paths. Co-authored-by: Georgy Evtushenko <[email protected]> Co-authored-by: gonzalobg <[email protected]> * Allow CUDA 12.2 to keep perf, this addresses earlier comments in #478 * Remove extraneous double brackets in unformatted code. * Merge unsafe atomic logic into `__cuda_is_local`. * Use `const_cast` for type conversions in cuda_local.h * Fix build issues from interface changes * Fix missing __nanosleep on sm70- * Guard __isLocal from NVHPC * Use PTX instead of running nothing from NVHPC * fixup /s/nvrtc/nvhpc * Fixup missing CUDA ifdef surrounding device code * Fix codegen * Bypass some sort of compiler bug on GCC7 * Apply suggestions from code review * Use unsafe automatic storage atomics in codegen tests --------- Co-authored-by: Georgy Evtushenko <[email protected]> Co-authored-by: gonzalobg <[email protected]> Co-authored-by: Michael Schellenberger Costa <[email protected]> Refactor the source code layout for `cuda.parallel` (#3177) * Refactor the source layout for cuda.parallel * Add copyright * Address review feedback * Don't import anything into `experimental` namespace * fix import --------- Co-authored-by: Ashwin Srinath <[email protected]> new type-erased memory resources (#2824) s/_LIBCUDACXX_DECLSPEC_EMPTY_BASES/_CCCL_DECLSPEC_EMPTY_BASES/g (#3186) Document address stability of `thrust::transform` (#3181) * Do not document _LIBCUDACXX_MARK_CAN_COPY_ARGUMENTS * Reformat and fix UnaryFunction/BinaryFunction in transform docs * Mention transform can use proclaim_copyable_arguments * Document cuda::proclaims_copyable_arguments better * Deprecate depending on transform functor argument addresses Fixes: #3053 turn off cuda version check for clangd (#3194) [STF] jacobi example based on parallel_for (#3187) * Simple jacobi example with parallel for and reductions * clang-format * remove useless capture list fixes pre-nv_diag suppression issues (#3189) Prefer c2h::type_name over c2h::demangle (#3195) Fix memcpy_async* tests (#3197) * memcpy_async_tx: Fix bug in test Two bugs, one of which occurs in practice: 1. There is a missing fence.proxy.space::global between the writes to global memory and the memcpy_async_tx. (Occurs in practice) 2. The end of the kernel should be fenced with `__syncthreads()`, because the barrier is invalidated in the destructor. If other threads are still waiting on it, there will be UB. (Has not yet manifested itself) * cp_async_bulk_tensor: Pre-emptively fence more in test Add type annotations and mypy checks for `cuda.parallel` (#3180) * Refactor the source layout for cuda.parallel * Add initial type annotations * Update pre-commit config * More typing * Fix bad merge * Fix TYPE_CHECKING and numpy annotations * typing bindings.py correctly * Address review feedback --------- Co-authored-by: Ashwin Srinath <[email protected]> Fix rendering of cuda.parallel docs (#3192) * Fix pre-commit config for codespell and remaining typos * Fix rendering of docs for cuda.parallel --------- Co-authored-by: Ashwin Srinath <[email protected]> Enable PDL for DeviceMergeSortBlockSortKernel (#3199) The kernel already contains a call to _CCCL_PDL_GRID_DEPENDENCY_SYNC. This commit enables PDL when launching the kernel. Adds support for large `num_items` to `DeviceReduce::{ArgMin,ArgMax}` (#2647) * adds benchmarks for reduce::arg{min,max} * preliminary streaming arg-extremum reduction * fixes implicit conversion * uses streaming dispatch class * changes arg benches to use new streaming reduce * streaming arg-extrema reduction * fixes style * fixes compilation failures * cleanups * adds rst style comments * declare vars const and use clamp * consolidates argmin argmax benchmarks * fixes thrust usage * drops offset type in arg-extrema benchmarks * fixes clang cuda * exec space macros * switch to signed global offset type for slightly better perf * clarifies documentation * applies minor benchmark style changes from review comments * fixes interface documentation and comments * list-init accumulating output op * improves style, comments, and tests * cleans up aggregate init * renames dispatch class usage in benchmarks * fixes merge conflicts * addresses review comments * addresses review comments * fixes assertion * removes superseded implementation * changes large problem tests to use new interface * removes obsolete tests for deprecated interface Fixes for Python 3.7 docs environment (#3206) Co-authored-by: Ashwin Srinath <[email protected]> Adds support for large number of items to `DeviceTransform` (#3172) * moves large problem test helper to common file * adds support for large num items to device transform * adds tests for large number of items to device interface * fixes format * addresses review comments cp_async_bulk: Fix test (#3198) * memcpy_async_tx: Fix bug in test Two bugs, one of which occurs in practice: 1. There is a missing fence.proxy.space::global between the writes to global memory and the memcpy_async_tx. (Occurs in practice) 2. The end of the kernel should be fenced with `__syncthreads()`, because the barrier is invalidated in the destructor. If other threads are still waiting on it, there will be UB. (Has not yet manifested itself) * cp_async_bulk_tensor: Pre-emptively fence more in test * cp_async_bulk: Fix test The global memory pointer could be misaligned. cudax fixes for msvc 14.41 (#3200) avoid instantiating class templates in `is_same` implementation when possible (#3203) Fix: make launchers a CUB detail; make kernel source functions hidden. (#3209) * Fix: make launchers a CUB detail; make kernel source functions hidden. * [pre-commit.ci] auto code formatting * Address review comments, fix which macro gets fixed. help the ranges concepts recognize standard contiguous iterators in c++14/17 (#3202) unify macros and cmake options that control the suppression of deprecation warnings (#3220) * unify macros and cmake options that control the suppression of deprecation warnings * suppress nvcc warning #186 in thrust header tests * suppress c++ dialect deprecation warnings in libcudacxx header tests Fx thread-reduce performance regression (#3225) cuda.parallel: In-memory caching of build objects (#3216) * Define __eq__ and __hash__ for Iterators * Define cache_with_key utility and use it to cache Reduce objects * Add tests for caching Reduce objects * Tighten up types * Updates to support 3.7 * Address review feedback * Introduce IteratorKind to hold iterator type information * Use the .kind to generate an abi_name * Remove __eq__ and __hash__ methods from IteratorBase * Move helper function * Formatting * Don't unpack tuple in cache key --------- Co-authored-by: Ashwin Srinath <[email protected]> Just enough ranges for c++14 `span` (#3211) use generalized concepts portability macros to simplify the `range` concept (#3217) fixes some issues in the concepts portability macros and then re-implements the `range` concept with `_CCCL_REQUIRES_EXPR` Use Ruff to sort imports (#3230) * Update pyproject.tomls for import sorting * Update files after running pre-commit * Move ruff config to pyproject.toml --------- Co-authored-by: Ashwin Srinath <[email protected]> fix tuning_scan sm90 config issue (#3236) Co-authored-by: Shijie Chen <[email protected]> [STF] Logical token (#3196) * Split the implementation of the void interface into the definition of the interface, and its implementations on streams and graphs. * Add missing files * Check if a task implementation can match a prototype where the void_interface arguments are ignored * Implement ctx.abstract_logical_data() which relies on a void data interface * Illustrate how to use abstract handles in local contexts * Introduce an is_void_interface() virtual method in the data interface to potentially optimize some stages * Small improvements in the examples * Do not try to allocate or move void data * Do not use I as a variable * fix linkage error * rename abtract_logical_data into logical_token * Document logical token * fix spelling error * fix sphinx error * reflect name changes * use meaningful variable names * simplify logical_token implementation because writeback is already disabled * add a unit test for token elision * implement token elision in host_launch * Remove unused type * Implement helpers to check if a function can be invoked from a tuple, or from a tuple where we removed tokens * Much simpler is_tuple_invocable_with_filtered implementation * Fix buggy test * Factorize code * Document that we can ignore tokens for task and host_launch * Documentation for logical data freeze Fix ReduceByKey tuning (#3240) Fix RLE tuning (#3239) cuda.parallel: Forbid non-contiguous arrays as inputs (or outputs) (#3233) * Forbid non-contiguous arrays as inputs (or outputs) * Implement a more robust way to check for contiguity * Don't bother if cublas unavailable * Fix how we check for zero-element arrays * sort imports --------- Co-authored-by: Ashwin Srinath <[email protected]> expands support for more offset types in segmented benchmark (#3231) Add escape hatches to the cmake configuration of the header tests so that we can tests deprecated compilers / dialects (#3253) * Add escape hatches to the cmake configuration of the header tests so that we can tests deprecated compilers / dialects * Do not add option twice ptx: Add add_instruction.py (#3190) This file helps create the necessary structure for new PTX instructions. Co-authored-by: Allard Hendriksen <[email protected]> Bump main to 2.9.0. (#3247) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Drop cub::Mutex (#3251) Fixes: #3250 Remove legacy macros from CUB util_arch.cuh (#3257) Fixes: #3256 Remove thrust::[unary|binary]_traits (#3260) Fixes: #3259 Architecture and OS identification macros (#3237) Bump main to 3.0.0. (#3265) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Drop thrust not1 and not2 (#3264) Fixes: #3263 CCCL Internal macro documentation (#3238) Deprecate GridBarrier and GridBarrierLifetime (#3258) Fixes: #1389 Require at least gcc7 (#3268) Fixes: #3267 Drop thrust::[unary|binary]_function (#3274) Fixes: #3273 Drop ICC from CI (#3277) [STF] Corruption of the capture list of an extended lambda with a parallel_for construct on a host execution place (#3270) * Add a test to reproduce a bug observed with parallel_for on a host place * clang-format * use _CCCL_ASSERT * Attempt to debug * do not create a tuple with a universal reference that is out of scope when we use it, use an lvalue instead * fix lambda expression * clang-format Enable thrust::identity test for non-MSVC (#3281) This seems to be an oversight when the test was added Co-authored-by: Michael Schellenberger Costa <[email protected]> Enable PDL in triple chevron launch (#3282) It seems PDL was disabled by accident when _THRUST_HAS_PDL was renamed to _CCCL_HAS_PDL during the review introducing the feature. Disambiguate line continuations and macro continuations in <nv/target> (#3244) Drop VS 2017 from CI (#3287) Fixes: #3286 Drop ICC support in code (#3279) * Drop ICC from code Fixes: #3278 Co-authored-by: Michael Schellenberger Costa <[email protected]> Make CUB NVRTC commandline arguments come from a cmake template (#3292) Propose the same components (thrust, cub, libc++, cudax, cuda.parallel,...) in the bug report template than in the feature request template (#3295) Use process isolation instead of default hyper-v for Windows. (#3294) Try improving build times by using process isolation instead of hyper-v Co-authored-by: Michael Schellenberger Costa <[email protected]> [pre-commit.ci] pre-commit autoupdate (#3248) * [pre-commit.ci] pre-commit autoupdate updates: - [github.com/pre-commit/mirrors-clang-format: v18.1.8 → v19.1.6](https://github.com/pre-commit/mirrors-clang-format/compare/v18.1.8...v19.1.6) - [github.com/astral-sh/ruff-pre-commit: v0.8.3 → v0.8.6](https://github.com/astral-sh/ruff-pre-commit/compare/v0.8.3...v0.8.6) - [github.com/pre-commit/mirrors-mypy: v1.13.0 → v1.14.1](https://github.com/pre-commit/mirrors-mypy/compare/v1.13.0...v1.14.1) Co-authored-by: Michael Schellenberger Costa <[email protected]> Drop Thrust legacy arch macros (#3298) Which were disabled and could be re-enabled using THRUST_PROVIDE_LEGACY_ARCH_MACROS Drop Thrust's compiler_fence.h (#3300) Drop CTK 11.x from CI (#3275) * Add cuda12.0-gcc7 devcontainer * Move MSVC2017 jobs to CTK 12.6 Those is the only combination where rapidsai has devcontainers * Add /Zc:__cplusplus for the libcudacxx tests * Only add excape hatch for affected CTKs * Workaround missing cudaLaunchKernelEx on MSVC cudaLaunchKernelEx requires C++11, but unfortunately <cuda_runtime.h> checks this using the __cplusplus macro, which is reported wrongly for MSVC. CTK 12.3 fixed this by additionally detecting _MSV_VER. As a workaround, we provide our own copy of cudaLaunchKernelEx when it is not available from the CTK. * Workaround nvcc+MSVC issue * Regenerate devcontainers Fixes: #3249 Co-authored-by: Michael Schellenberger Costa <[email protected]> Drop CUB's util_compiler.cuh (#3302) All contained macros were deprecated Update packman and repo_docs versions (#3293) Co-authored-by: Ashwin Srinath <[email protected]> Drop Thrust's deprecated compiler macros (#3301) Drop CUB_RUNTIME_ENABLED and __THRUST_HAS_CUDART__ (#3305) Adds support for large number of items to `DevicePartition::If` with the `ThreeWayPartition` overload (#2506) * adds support for large number of items to three-way partition * adapts interface to use choose_signed_offset_t * integrates applicable feedback from device-select pr * changes behavior for empty problems * unifies grid constant macro * fixes kernel template specialization mismatch * integrates _CCCL_GRID_CONSTANT changes * resolve merge conflicts * fixes checks in test * fixes test verification * improves tests * makes few improvements to streaming dispatch * improves code comment on test * fixes unrelated compiler error * minor style improvements Refactor scan tunings (#3262) Require C++17 for compiling Thrust and CUB (#3255) * Issue an unsuppressable warning when compiling with < C++17 * Remove C++11/14 presets * Remove CCCL_IGNORE_DEPRECATED_CPP_DIALECT from headers * Remove [CUB|THRUST|TCT]_IGNORE_DEPRECATED_CPP_[11|14] * Remove CUB_ENABLE_DIALECT_CPP[11|14] * Update CI runs * Remove C++11/14 CI runs for CUB and Thrust * Raise compiler minimum versions for C++17 * Update ReadMe * Drop Thrust's cpp14_required.h * Add escape hatch for C++17 removal Fixes: #3252 Implement `views::empty` (#3254) * Disable pair conversion of subrange with clang in C++17 * Fix namespace views * Implement `views::empty` This implements `std::ranges::views::empty`, see https://en.cppreference.com/w/cpp/ranges/empty_view Refactor `limits` and `climits` (#3221) * implement builtins for huge val, nan and nans * change `INFINITY` and `NAN` implementation for NVRTC cuda.parallel: Add documentation for the current iterators along with examples and tests (#3311) * Add tests demonstrating usage of different iterators * Update documentation of reduce_into by merging import code snippet with the rest of the example * Add documentation for current iterators * Run pre-commit checks and update accordingly * Fix comments to refer to the proper lines in the code snippets in the docs Drop clang<14 from CI, update devcontainers. (#3309) Co-authored-by: Bernhard Manfred Gruber <[email protected]> [STF] Cleanup task dependencies object constructors (#3291) * Define tag types for access modes * - Rework how we build task_dep objects based on access mode tags - pack_state is now responsible for using a const_cast for read only data * Greatly simplify the previous attempt : do not define new types, but use integral constants based on the enums * It seems the const_cast was not necessarily so we can simplify it and not even do some dispatch based on access modes Disable test with a gcc-14 regression (#3297) Deprecate Thrust's cpp_compatibility.h macros (#3299) Remove dropped function objects from docs (#3319) Document `NV_TARGET` macros (#3313) [STF] Define ctx.pick_stream() which was missing for the unified context (#3326) * Define ctx.pick_stream() which was missing for the unified context * clang-format Deprecate cub::IterateThreadStore (#3337) Drop CUB's BinaryFlip operator (#3332) Deprecate cub::Swap (#3333) Clarify transform output can overlap input (#3323) Drop CUB APIs with a debug_synchronous parameter (#3330) Fixes: #3329 Drop CUB's util_compiler.cuh for real (#3340) PR #3302 planned to drop the file, but only dropped its content. This was an oversight. So let's drop the entire file. Drop cub::ValueCache (#3346) limits offset types for merge sort (#3328) Drop CDPv1 (#3344) Fixes: #3341 Drop thrust::void_t (#3362) Use cuda::std::addressof in Thrust (#3363) Fix all_of documentation for empty ranges (#3358) all_of always returns true on an empty range. [STF] Do not keep track of dangling events in a CUDA graph backend (#3327) * Unlike the CUDA stream backend, nodes in a CUDA graph are necessarily done when the CUDA graph completes. Therefore keeping track of "dangling events" is a waste of time and resources. * replace can_ignore_dangling_events by track_dangling_events which leads to more readable code * When not storing the dangling events, we must still perform the deinit operations that were producing these events ! Extract scan kernels into NVRTC-compilable header (#3334) * Extract scan kernels into NVRTC-compilable header * Update cub/cub/device/dispatch/dispatch_scan.cuh Co-authored-by: Georgii Evtushenko <[email protected]> --------- Co-authored-by: Ashwin Srinath <[email protected]> Co-authored-by: Georgii Evtushenko <[email protected]> Drop deprecated aliases in Thrust functional (#3272) Fixes: #3271 Drop cub::DivideAndRoundUp (#3347) Use cuda::std::min/max in Thrust (#3364) Implement `cuda::std::numeric_limits` for `__half` and `__nv_bfloat16` (#3361) * implement `cuda::std::numeric_limits` for `__half` and `__nv_bfloat16` Cleanup util_arch (#2773) Deprecate thrust::null_type (#3367) Deprecate cub::DeviceSpmv (#3320) Fixes: #896 Improves `DeviceSegmentedSort` test run time for large number of items and segments (#3246) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * fixes spelling * adds tests for large number of segments * fixes narrowing conversion in tests * addresses review comments * fixes includes Compile basic infra test with C++17 (#3377) Adds support for large number of items and large number of segments to `DeviceSegmentedSort` (#3308) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * addresses review comments * introduces segment offset type * adds tests for large number of segments * adds support for large number of segments * drops segment offset type * fixes thrust namespace * removes about-to-be-deprecated cub iterators * no exec specifier on defaulted ctor * fixes gcc7 linker error * uses local_segment_index_t throughout * determine offset type based on type returned by segment iterator begin/end iterators * minor style improvements Exit with error when RAPIDS CI fails. (#3385) cuda.parallel: Support structured types as algorithm inputs (#3218) * Introduce gpu_struct decorator and typing * Enable `reduce` to accept arrays of structs as inputs * Add test for reducing arrays-of-struct * Update documentation * Use a numpy array rather than ctypes object * Change zeros -> empty for output array and temp storage * Add a TODO for typing GpuStruct * Documentation udpates * Remove test_reduce_struct_type from test_reduce.py * Revert to `to_cccl_value()` accepting ndarray + GpuStruct * Bump copyrights --------- Co-authored-by: Ashwin Srinath <[email protected]> Deprecate thrust::async (#3324) Fixes: #100 Review/Deprecate CUB `util.ptx` for CCCL 2.x (#3342) Fix broken `_CCCL_BUILTIN_ASSUME` macro (#3314) * add compiler-specific path * fix device code path * add _CCC_ASSUME Deprecate thrust::numeric_limits (#3366) Replace `typedef` with `using` in libcu++ (#3368) Deprecate thrust::optional (#3307) Fixes: #3306 Upgrade to Catch2 3.8 (#3310) Fixes: #1724 refactor `<cuda/std/cstdint>` (#3325) Co-authored-by: Bernhard Manfred Gruber <[email protected]> Update CODEOWNERS (#3331) * Update CODEOWNERS * Update CODEOWNERS * Update CODEOWNERS * [pre-commit.ci] auto code formatting --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Fix sign-compare warning (#3408) Implement more cmath functions to be usable on host and device (#3382) * Implement more cmath functions to be usable on host and device * Implement math roots functions * Implement exponential functions Redefine and deprecate thrust::remove_cvref (#3394) * Redefine and deprecate thrust::remove_cvref Co-authored-by: Michael Schellenberger Costa <[email protected]> Fix assert definition for NVHPC due to constexpr issues (#3418) NVHPC cannot decide at compile time where the code would run so _CCCL_ASSERT within a constexpr function breaks it. Fix this by always using the host definition which should also work on device. Fixes #3411 Extend CUB reduce benchmarks (#3401) * Rename max.cu to custom.cu, since it uses a custom operator * Extend types covered my min.cu to all fundamental types * Add some notes on how to collect tuning parameters Fixes: #3283 Update upload-pages-artifact to v3 (#3423) * Update upload-pages-artifact to v3 * Empty commit --------- Co-authored-by: Ashwin Srinath <[email protected]> Replace and deprecate thrust::cuda_cub::terminate (#3421) `std::linalg` accessors and `transposed_layout` (#2962) Add round up/down to multiple (#3234) [FEA]: Introduce Python module with CCCL headers (#3201) * Add cccl/python/cuda_cccl directory and use from cuda_parallel, cuda_cooperative * Run `copy_cccl_headers_to_aude_include()` before `setup()` * Create python/cuda_cccl/cuda/_include/__init__.py, then simply import cuda._include to find the include path. * Add cuda.cccl._version exactly as for cuda.cooperative and cuda.parallel * Bug fix: cuda/_include only exists after shutil.copytree() ran. * Use `f"cuda-cccl @ file://{cccl_path}/python/cuda_cccl"` in setup.py * Remove CustomBuildCommand, CustomWheelBuild in cuda_parallel/setup.py (they are equivalent to the default functions) * Replace := operator (needs Python 3.8+) * Fix oversights: remove `pip3 install ./cuda_cccl` lines from README.md * Restore original README.md: `pip3 install -e` now works on first pass. * cuda_cccl/README.md: FOR INTERNAL USE ONLY * Remove `$pymajor.$pyminor.` prefix in cuda_cccl _version.py (as suggested under https://github.com/NVIDIA/cccl/pull/3201#discussion_r1894035917) Command used: ci/update_version.sh 2 8 0 * Modernize pyproject.toml, setup.py Trigger for this change: * https://github.com/NVIDIA/cccl/pull/3201#discussion_r1894043178 * https://github.com/NVIDIA/cccl/pull/3201#discussion_r1894044996 * Install CCCL headers under cuda.cccl.include Trigger for this change: * https://github.com/NVIDIA/cccl/pull/3201#discussion_r1894048562 Unexpected accidental discovery: cuda.cooperative unit tests pass without CCCL headers entirely. * Factor out cuda_cccl/cuda/cccl/include_paths.py * Reuse cuda_cccl/cuda/cccl/include_paths.py from cuda_cooperative * Add missing Copyright notice. * Add missing __init__.py (cuda.cccl) * Add `"cuda.cccl"` to `autodoc.mock_imports` * Move cuda.cccl.include_paths into function where it is used. (Attempt to resolve Build and Verify Docs failure.) * Add # TODO: move this to a module-level import * Modernize cuda_cooperative/pyproject.toml, setup.py * Convert cuda_cooperative to use hatchling as build backend. * Revert "Convert cuda_cooperative to use hatchling as build backend." This reverts commit 61637d608da06fcf6851ef6197f88b5e7dbc3bbe. * Move numpy from [build-system] requires -> [project] dependencies * Move pyproject.toml [project] dependencies -> setup.py install_requires, to be able to use CCCL_PATH * Remove copy_license() and use license_files=["../../LICENSE"] instead. * Further modernize cuda_cccl/setup.py to use pathlib * Trivial simplifications in cuda_cccl/pyproject.toml * Further simplify cuda_cccl/pyproject.toml, setup.py: remove inconsequential code * Make cuda_cooperative/pyproject.toml more similar to cuda_cccl/pyproject.toml * Add taplo-pre-commit to .pre-commit-config.yaml * taplo-pre-commit auto-fixes * Use pathlib in cuda_cooperative/setup.py * CCCL_PYTHON_PATH in cuda_cooperative/setup.py * Modernize cuda_parallel/pyproject.toml, setup.py * Use pathlib in cuda_parallel/setup.py * Add `# TOML lint & format` comment. * Replace MANIFEST.in with `[tool.setuptools.package-data]` section in pyproject.toml * Use pathlib in cuda/cccl/include_paths.py * pre-commit autoupdate (EXCEPT clang-format, which was manually restored) * Fixes after git merge main * Resolve warning: AttributeError: '_Reduce' object has no attribute 'build_result' ``` =========================================================================== warnings summary =========================================================================== tests/test_reduce.py::test_reduce_non_contiguous /home/coder/cccl/python/devenv/lib/python3.12/site-packages/_pytest/unraisableexception.py:85: PytestUnraisableExceptionWarning: Exception ignored in: <function _Reduce.__del__ at 0x7bf123139080> Traceback (most recent call last): File "/home/coder/cccl/python/cuda_parallel/cuda/parallel/experimental/algorithms/reduce.py", line 132, in __del__ bindings.cccl_device_reduce_cleanup(ctypes.byref(self.build_result)) ^^^^^^^^^^^^^^^^^ AttributeError: '_Reduce' object has no attribute 'build_result' warnings.warn(pytest.PytestUnraisableExceptionWarning(msg)) -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html ============================================================= 1 passed, 93 deselected, 1 warning in 0.44s ============================================================== ``` * Move `copy_cccl_headers_to_cuda_cccl_include()` functionality to `class CustomBuildPy` * Introduce cuda_cooperative/constraints.txt * Also add cuda_parallel/constraints.txt * Add `--constraint constraints.txt` in ci/test_python.sh * Update Copyright dates * Switch to https://github.com/ComPWA/taplo-pre-commit (the other repo has been archived by the owner on Jul 1, 2024) For completeness: The other repo took a long time to install into the pre-commit cache; so long it lead to timeouts in the CCCL CI. * Remove unused cuda_parallel jinja2 dependency (noticed by chance). * Remove constraints.txt files, advertise running `pip install cuda-cccl` first instead. * Make cuda_cooperative, cuda_parallel testing completely independent. * Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc] * Try using another runner (because V100 runners seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Fix sign-compare warning (#3408) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Revert "Try using another runner (because V100 runners seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc]" This reverts commit ea33a218ed77a075156cd1b332047202adb25aa2. Error message: https://github.com/NVIDIA/cccl/pull/3201#issuecomment-2594012971 * Try using A100 runner (because V100 runners still seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Also show cuda-cooperative site-packages, cuda-parallel site-packages (after pip install) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Try using l4 runner (because V100 runners still seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Restore original ci/matrix.yaml [skip-rapids] * Use for loop in test_python.sh to avoid code duplication. * Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc][skip pre-commit.ci] * Comment out taplo-lint in pre-commit config [skip-rapids][skip-matx][skip-docs][skip-vdc] * Revert "Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc][skip pre-commit.ci]" This reverts commit ec206fd8b50a6a293e00a5825b579e125010b13d. * Implement suggestion by @shwina (https://github.com/NVIDIA/cccl/pull/3201#pullrequestreview-2556918460) * Address feedback by @leofang --------- Co-authored-by: Bernhard Manfred Gruber <[email protected]> cuda.parallel: Add optional stream argument to reduce_into() (#3348) * Add optional stream argument to reduce_into() * Add tests to check for reduce_into() stream behavior * Move protocol related utils to separate file and rework __cuda_stream__ error messages * Fix synchronization issue in stream test and add one more invalid stream test case * Rename cuda stream validation function after removing leading underscore * Unpack values from __cuda_stream__ instead of indexing * Fix linting errors * Handle TypeError when unpacking invalid __cuda_stream__ return * Use stream to allocate cupy memory in new stream test Upgrade to actions/deploy-pages@v4 (from v2), as suggested by @leofang (#3434) Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ (#3419) * Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ Fixes #3404 move to c++17, finalize device optimization fix msvc compilation, update tests Deprectate C++11 and C++14 for libcu++ (#3173) * Deprectate C++11 and C++14 for libcu++ Co-authored-by: Bernhard Manfred Gruber <[email protected]> Implement `abs` and `div` from `cstdlib` (#3153) * implement integer abs functions * improve tests, fix constexpr support * just use the our implementation * implement `cuda::std::div` * prefer host's `div_t` like types * provide `cuda::std::abs` overloads for floats * allow fp abs for NVRTC * silence msvc's warning about conversion from floating point to integral Fix missing radix sort policies (#3174) Fixes NVBug 5009941 Introduces new `DeviceReduce::Arg{Min,Max}` interface with two output iterators (#3148) * introduces new arg{min,max} interface with two output iterators * adds fp inf tests * fixes docs * improves code example * fixes exec space specifier * trying to fix deprecation warning for more compilers * inlines unzip operator * trying to fix deprecation warning for nvhpc * integrates supression fixes in diagnostics * pre-ctk 11.5 deprecation suppression * fixes icc * fix for pre-ctk11.5 * cleans up deprecation suppression * cleanup Extend tuning documentation (#3179) Add codespell pre-commit hook, fix typos in CCCL (#3168) * Add codespell pre-commit hook * Automatic changes from codespell. * Manual changes. Fix parameter space for TUNE_LOAD in scan benchmark (#3176) fix various old compiler checks (#3178) implement C++26 `std::projected` (#3175) Fix pre-commit config for codespell and remaining typos (#3182) Massive cleanup of our config (#3155) Fix UB in atomics with automatic storage (#2586) * Adds specialized local cuda atomics and injects them into most atomics paths. Co-authored-by: Georgy Evtushenko <[email protected]> Co-authored-by: gonzalobg <[email protected]> * Allow CUDA 12.2 to keep perf, this addresses earlier comments in #478 * Remove extraneous double brackets in unformatted code. * Merge unsafe atomic logic into `__cuda_is_local`. * Use `const_cast` for type conversions in cuda_local.h * Fix build issues from interface changes * Fix missing __nanosleep on sm70- * Guard __isLocal from NVHPC * Use PTX instead of running nothing from NVHPC * fixup /s/nvrtc/nvhpc * Fixup missing CUDA ifdef surrounding device code * Fix codegen * Bypass some sort of compiler bug on GCC7 * Apply suggestions from code review * Use unsafe automatic storage atomics in codegen tests --------- Co-authored-by: Georgy Evtushenko <[email protected]> Co-authored-by: gonzalobg <[email protected]> Co-authored-by: Michael Schellenberger Costa <[email protected]> Refactor the source code layout for `cuda.parallel` (#3177) * Refactor the source layout for cuda.parallel * Add copyright * Address review feedback * Don't import anything into `experimental` namespace * fix import --------- Co-authored-by: Ashwin Srinath <[email protected]> new type-erased memory resources (#2824) s/_LIBCUDACXX_DECLSPEC_EMPTY_BASES/_CCCL_DECLSPEC_EMPTY_BASES/g (#3186) Document address stability of `thrust::transform` (#3181) * Do not document _LIBCUDACXX_MARK_CAN_COPY_ARGUMENTS * Reformat and fix UnaryFunction/BinaryFunction in transform docs * Mention transform can use proclaim_copyable_arguments * Document cuda::proclaims_copyable_arguments better * Deprecate depending on transform functor argument addresses Fixes: #3053 turn off cuda version check for clangd (#3194) [STF] jacobi example based on parallel_for (#3187) * Simple jacobi example with parallel for and reductions * clang-format * remove useless capture list fixes pre-nv_diag suppression issues (#3189) Prefer c2h::type_name over c2h::demangle (#3195) Fix memcpy_async* tests (#3197) * memcpy_async_tx: Fix bug in test Two bugs, one of which occurs in practice: 1. There is a missing fence.proxy.space::global between the writes to global memory and the memcpy_async_tx. (Occurs in practice) 2. The end of the kernel should be fenced with `__syncthreads()`, because the barrier is invalidated in the destructor. If other threads are still waiting on it, there will be UB. (Has not yet manifested itself) * cp_async_bulk_tensor: Pre-emptively fence more in test Add type annotations and mypy checks for `cuda.parallel` (#3180) * Refactor the source layout for cuda.parallel * Add initial type annotations * Update pre-commit config * More typing * Fix bad merge * Fix TYPE_CHECKING and numpy annotations * typing bindings.py correctly * Address review feedback --------- Co-authored-by: Ashwin Srinath <[email protected]> Fix rendering of cuda.parallel docs (#3192) * Fix pre-commit config for codespell and remaining typos * Fix rendering of docs for cuda.parallel --------- Co-authored-by: Ashwin Srinath <[email protected]> Enable PDL for DeviceMergeSortBlockSortKernel (#3199) The kernel already contains a call to _CCCL_PDL_GRID_DEPENDENCY_SYNC. This commit enables PDL when launching the kernel. Adds support for large `num_items` to `DeviceReduce::{ArgMin,ArgMax}` (#2647) * adds benchmarks for reduce::arg{min,max} * preliminary streaming arg-extremum reduction * fixes implicit conversion * uses streaming dispatch class * changes arg benches to use new streaming reduce * streaming arg-extrema reduction * fixes style * fixes compilation failures * cleanups * adds rst style comments * declare vars const and use clamp * consolidates argmin argmax benchmarks * fixes thrust usage * drops offset type in arg-extrema benchmarks * fixes clang cuda * exec space macros * switch to signed global offset type for slightly better perf * clarifies documentation * applies minor benchmark style changes from review comments * fixes interface documentation and comments * list-init accumulating output op * improves style, comments, and tests * cleans up aggregate init * renames dispatch class usage in benchmarks * fixes merge conflicts * addresses review comments * addresses review comments * fixes assertion * removes superseded implementation * changes large problem tests to use new interface * removes obsolete tests for deprecated interface Fixes for Python 3.7 docs environment (#3206) Co-authored-by: Ashwin Srinath <[email protected]> Adds support for large number of items to `DeviceTransform` (#3172) * moves large problem test helper to common file * adds support for large num items to device transform * adds tests for large number of items to device interface * fixes format * addresses review comments cp_async_bulk: Fix test (#3198) * memcpy_async_tx: Fix bug in test Two bugs, one of which occurs in practice: 1. There is a missing fence.proxy.space::global between the writes to global memory and the memcpy_async_tx. (Occurs in practice) 2. The end of the kernel should be fenced with `__syncthreads()`, because the barrier is invalidated in the destructor. If other threads are still waiting on it, there will be UB. (Has not yet manifested itself) * cp_async_bulk_tensor: Pre-emptively fence more in test * cp_async_bulk: Fix test The global memory pointer could be misaligned. cudax fixes for msvc 14.41 (#3200) avoid instantiating class templates in `is_same` implementation when possible (#3203) Fix: make launchers a CUB detail; make kernel source functions hidden. (#3209) * Fix: make launchers a CUB detail; make kernel source functions hidden. * [pre-commit.ci] auto code formatting * Address review comments, fix which macro gets fixed. help the ranges concepts recognize standard contiguous iterators in c++14/17 (#3202) unify macros and cmake options that control the suppression of deprecation warnings (#3220) * unify macros and cmake options that control the suppression of deprecation warnings * suppress nvcc warning #186 in thrust header tests * suppress c++ dialect deprecation warnings in libcudacxx header tests Fx thread-reduce performance regression (#3225) cuda.parallel: In-memory caching of build objects (#3216) * Define __eq__ and __hash__ for Iterators * Define cache_with_key utility and use it to cache Reduce objects * Add tests for caching Reduce objects * Tighten up types * Updates to support 3.7 * Address review feedback * Introduce IteratorKind to hold iterator type information * Use the .kind to generate an abi_name * Remove __eq__ and __hash__ methods from IteratorBase * Move helper function * Formatting * Don't unpack tuple in cache key --------- Co-authored-by: Ashwin Srinath <[email protected]> Just enough ranges for c++14 `span` (#3211) use generalized concepts portability macros to simplify the `range` concept (#3217) fixes some issues in the concepts portability macros and then re-implements the `range` concept with `_CCCL_REQUIRES_EXPR` Use Ruff to sort imports (#3230) * Update pyproject.tomls for import sorting * Update files after running pre-commit * Move ruff config to pyproject.toml --------- Co-authored-by: Ashwin Srinath <[email protected]> fix tuning_scan sm90 config issue (#3236) Co-authored-by: Shijie Chen <[email protected]> [STF] Logical token (#3196) * Split the implementation of the void interface into the definition of the interface, and its implementations on streams and graphs. * Add missing files * Check if a task implementation can match a prototype where the void_interface arguments are ignored * Implement ctx.abstract_logical_data() which relies on a void data interface * Illustrate how to use abstract handles in local contexts * Introduce an is_void_interface() virtual method in the data interface to potentially optimize some stages * Small improvements in the examples * Do not try to allocate or move void data * Do not use I as a variable * fix linkage error * rename abtract_logical_data into logical_token * Document logical token * fix spelling error * fix sphinx error * reflect name changes * use meaningful variable names * simplify logical_token implementation because writeback is already disabled * add a unit test for token elision * implement token elision in host_launch * Remove unused type * Implement helpers to check if a function can be invoked from a tuple, or from a tuple where we removed tokens * Much simpler is_tuple_invocable_with_filtered implementation * Fix buggy test * Factorize code * Document that we can ignore tokens for task and host_launch * Documentation for logical data freeze Fix ReduceByKey tuning (#3240) Fix RLE tuning (#3239) cuda.parallel: Forbid non-contiguous arrays as inputs (or outputs) (#3233) * Forbid non-contiguous arrays as inputs (or outputs) * Implement a more robust way to check for contiguity * Don't bother if cublas unavailable * Fix how we check for zero-element arrays * sort imports --------- Co-authored-by: Ashwin Srinath <[email protected]> expands support for more offset types in segmented benchmark (#3231) Add escape hatches to the cmake configuration of the header tests so that we can tests deprecated compilers / dialects (#3253) * Add escape hatches to the cmake configuration of the header tests so that we can tests deprecated compilers / dialects * Do not add option twice ptx: Add add_instruction.py (#3190) This file helps create the necessary structure for new PTX instructions. Co-authored-by: Allard Hendriksen <[email protected]> Bump main to 2.9.0. (#3247) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Drop cub::Mutex (#3251) Fixes: #3250 Remove legacy macros from CUB util_arch.cuh (#3257) Fixes: #3256 Remove thrust::[unary|binary]_traits (#3260) Fixes: #3259 Architecture and OS identification macros (#3237) Bump main to 3.0.0. (#3265) Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Drop thrust not1 and not2 (#3264) Fixes: #3263 CCCL Internal macro documentation (#3238) Deprecate GridBarrier and GridBarrierLifetime (#3258) Fixes: #1389 Require at least gcc7 (#3268) Fixes: #3267 Drop thrust::[unary|binary]_function (#3274) Fixes: #3273 Drop ICC from CI (#3277) [STF] Corruption of the capture list of an extended lambda with a parallel_for construct on a host execution place (#3270) * Add a test to reproduce a bug observed with parallel_for on a host place * clang-format * use _CCCL_ASSERT * Attempt to debug * do not create a tuple with a universal reference that is out of scope when we use it, use an lvalue instead * fix lambda expression * clang-format Enable thrust::identity test for non-MSVC (#3281) This seems to be an oversight when the test was added Co-authored-by: Michael Schellenberger Costa <[email protected]> Enable PDL in triple chevron launch (#3282) It seems PDL was disabled by accident when _THRUST_HAS_PDL was renamed to _CCCL_HAS_PDL during the review introducing the feature. Disambiguate line continuations and macro continuations in <nv/target> (#3244) Drop VS 2017 from CI (#3287) Fixes: #3286 Drop ICC support in code (#3279) * Drop ICC from code Fixes: #3278 Co-authored-by: Michael Schellenberger Costa <[email protected]> Make CUB NVRTC commandline arguments come from a cmake template (#3292) Propose the same components (thrust, cub, libc++, cudax, cuda.parallel,...) in the bug report template than in the feature request template (#3295) Use process isolation instead of default hyper-v for Windows. (#3294) Try improving build times by using process isolation instead of hyper-v Co-authored-by: Michael Schellenberger Costa <[email protected]> [pre-commit.ci] pre-commit autoupdate (#3248) * [pre-commit.ci] pre-commit autoupdate updates: - [github.com/pre-commit/mirrors-clang-format: v18.1.8 → v19.1.6](https://github.com/pre-commit/mirrors-clang-format/compare/v18.1.8...v19.1.6) - [github.com/astral-sh/ruff-pre-commit: v0.8.3 → v0.8.6](https://github.com/astral-sh/ruff-pre-commit/compare/v0.8.3...v0.8.6) - [github.com/pre-commit/mirrors-mypy: v1.13.0 → v1.14.1](https://github.com/pre-commit/mirrors-mypy/compare/v1.13.0...v1.14.1) Co-authored-by: Michael Schellenberger Costa <[email protected]> Drop Thrust legacy arch macros (#3298) Which were disabled and could be re-enabled using THRUST_PROVIDE_LEGACY_ARCH_MACROS Drop Thrust's compiler_fence.h (#3300) Drop CTK 11.x from CI (#3275) * Add cuda12.0-gcc7 devcontainer * Move MSVC2017 jobs to CTK 12.6 Those is the only combination where rapidsai has devcontainers * Add /Zc:__cplusplus for the libcudacxx tests * Only add excape hatch for affected CTKs * Workaround missing cudaLaunchKernelEx on MSVC cudaLaunchKernelEx requires C++11, but unfortunately <cuda_runtime.h> checks this using the __cplusplus macro, which is reported wrongly for MSVC. CTK 12.3 fixed this by additionally detecting _MSV_VER. As a workaround, we provide our own copy of cudaLaunchKernelEx when it is not available from the CTK. * Workaround nvcc+MSVC issue * Regenerate devcontainers Fixes: #3249 Co-authored-by: Michael Schellenberger Costa <[email protected]> Update packman and repo_docs versions (#3293) Co-authored-by: Ashwin Srinath <[email protected]> Drop Thrust's deprecated compiler macros (#3301) Drop CUB_RUNTIME_ENABLED and __THRUST_HAS_CUDART__ (#3305) Adds support for large number of items to `DevicePartition::If` with the `ThreeWayPartition` overload (#2506) * adds support for large number of items to three-way partition * adapts interface to use choose_signed_offset_t * integrates applicable feedback from device-select pr * changes behavior for empty problems * unifies grid constant macro * fixes kernel template specialization mismatch * integrates _CCCL_GRID_CONSTANT changes * resolve merge conflicts * fixes checks in test * fixes test verification * improves tests * makes few improvements to streaming dispatch * improves code comment on test * fixes unrelated compiler error * minor style improvements Refactor scan tunings (#3262) Require C++17 for compiling Thrust and CUB (#3255) * Issue an unsuppressable warning when compiling with < C++17 * Remove C++11/14 presets * Remove CCCL_IGNORE_DEPRECATED_CPP_DIALECT from headers * Remove [CUB|THRUST|TCT]_IGNORE_DEPRECATED_CPP_[11|14] * Remove CUB_ENABLE_DIALECT_CPP[11|14] * Update CI runs * Remove C++11/14 CI runs for CUB and Thrust * Raise compiler minimum versions for C++17 * Update ReadMe * Drop Thrust's cpp14_required.h * Add escape hatch for C++17 removal Fixes: #3252 Implement `views::empty` (#3254) * Disable pair conversion of subrange with clang in C++17 * Fix namespace views * Implement `views::empty` This implements `std::ranges::views::empty`, see https://en.cppreference.com/w/cpp/ranges/empty_view Refactor `limits` and `climits` (#3221) * implement builtins for huge val, nan and nans * change `INFINITY` and `NAN` implementation for NVRTC cuda.parallel: Add documentation for the current iterators along with examples and tests (#3311) * Add tests demonstrating usage of different iterators * Update documentation of reduce_into by merging import code snippet with the rest of the example * Add documentation for current iterators * Run pre-commit checks and update accordingly * Fix comments to refer to the proper lines in the code snippets in the docs Drop clang<14 from CI, update devcontainers. (#3309) Co-authored-by: Bernhard Manfred Gruber <[email protected]> [STF] Cleanup task dependencies object constructors (#3291) * Define tag types for access modes * - Rework how we build task_dep objects based on access mode tags - pack_state is now responsible for using a const_cast for read only data * Greatly simplify the previous attempt : do not define new types, but use integral constants based on the enums * It seems the const_cast was not necessarily so we can simplify it and not even do some dispatch based on access modes Disable test with a gcc-14 regression (#3297) Deprecate Thrust's cpp_compatibility.h macros (#3299) Remove dropped function objects from docs (#3319) Document `NV_TARGET` macros (#3313) [STF] Define ctx.pick_stream() which was missing for the unified context (#3326) * Define ctx.pick_stream() which was missing for the unified context * clang-format Deprecate cub::IterateThreadStore (#3337) Drop CUB's BinaryFlip operator (#3332) Deprecate cub::Swap (#3333) Clarify transform output can overlap input (#3323) Drop CUB APIs with a debug_synchronous parameter (#3330) Fixes: #3329 Drop CUB's util_compiler.cuh for real (#3340) PR #3302 planned to drop the file, but only dropped its content. This was an oversight. So let's drop the entire file. Drop cub::ValueCache (#3346) limits offset types for merge sort (#3328) Drop CDPv1 (#3344) Fixes: #3341 Drop thrust::void_t (#3362) Use cuda::std::addressof in Thrust (#3363) Fix all_of documentation for empty ranges (#3358) all_of always returns true on an empty range. [STF] Do not keep track of dangling events in a CUDA graph backend (#3327) * Unlike the CUDA stream backend, nodes in a CUDA graph are necessarily done when the CUDA graph completes. Therefore keeping track of "dangling events" is a waste of time and resources. * replace can_ignore_dangling_events by track_dangling_events which leads to more readable code * When not storing the dangling events, we must still perform the deinit operations that were producing these events ! Extract scan kernels into NVRTC-compilable header (#3334) * Extract scan kernels into NVRTC-compilable header * Update cub/cub/device/dispatch/dispatch_scan.cuh Co-authored-by: Georgii Evtushenko <[email protected]> --------- Co-authored-by: Ashwin Srinath <[email protected]> Co-authored-by: Georgii Evtushenko <[email protected]> Drop deprecated aliases in Thrust functional (#3272) Fixes: #3271 Drop cub::DivideAndRoundUp (#3347) Use cuda::std::min/max in Thrust (#3364) Implement `cuda::std::numeric_limits` for `__half` and `__nv_bfloat16` (#3361) * implement `cuda::std::numeric_limits` for `__half` and `__nv_bfloat16` Cleanup util_arch (#2773) Deprecate thrust::null_type (#3367) Deprecate cub::DeviceSpmv (#3320) Fixes: #896 Improves `DeviceSegmentedSort` test run time for large number of items and segments (#3246) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * fixes spelling * adds tests for large number of segments * fixes narrowing conversion in tests * addresses review comments * fixes includes Compile basic infra test with C++17 (#3377) Adds support for large number of items and large number of segments to `DeviceSegmentedSort` (#3308) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * addresses review comments * introduces segment offset type * adds tests for large number of segments * adds support for large number of segments * drops segment offset type * fixes thrust namespace * removes about-to-be-deprecated cub iterators * no exec specifier on defaulted ctor * fixes gcc7 linker error * uses local_segment_index_t throughout * determine offset type based on type returned by segment iterator begin/end iterators * minor style improvements Exit with error when RAPIDS CI fails. (#3385) cuda.parallel: Support structured types as algorithm inputs (#3218) * Introduce gpu_struct decorator and typing * Enable `reduce` to accept arrays of structs as inputs * Add test for reducing arrays-of-struct * Update documentation * Use a numpy array rather than ctypes object * Change zeros -> empty for output array and temp storage * Add a TODO for typing GpuStruct * Documentation udpates * Remove test_reduce_struct_type from test_reduce.py * Revert to `to_cccl_value()` accepting ndarray + GpuStruct * Bump copyrights --------- Co-authored-by: Ashwin Srinath <[email protected]> Deprecate thrust::async (#3324) Fixes: #100 Review/Deprecate CUB `util.ptx` for CCCL 2.x (#3342) Fix broken `_CCCL_BUILTIN_ASSUME` macro (#3314) * add compiler-specific path * fix device code path * add _CCC_ASSUME Deprecate thrust::numeric_limits (#3366) Replace `typedef` with `using` in libcu++ (#3368) Deprecate thrust::optional (#3307) Fixes: #3306 Upgrade to Catch2 3.8 (#3310) Fixes: #1724 refactor `<cuda/std/cstdint>` (#3325) Co-authored-by: Bernhard Manfred Gruber <[email protected]> Update CODEOWNERS (#3331) * Update CODEOWNERS * Update CODEOWNERS * Update CODEOWNERS * [pre-commit.ci] auto code formatting --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Fix sign-compare warning (#3408) Implement more cmath functions to be usable on host and device (#3382) * Implement more cmath functions to be usable on host and device * Implement math roots functions * Implement exponential functions Redefine and deprecate thrust::remove_cvref (#3394) * Redefine and deprecate thrust::remove_cvref Co-authored-by: Michael Schellenberger Costa <[email protected]> Fix assert definition for NVHPC due to constexpr issues (#3418) NVHPC cannot decide at compile time where the code would run so _CCCL_ASSERT within a constexpr function breaks it. Fix this by always using the host definition which should also work on device. Fixes #3411 Extend CUB reduce benchmarks (#3401) * Rename max.cu to custom.cu, since it uses a custom operator * Extend types covered my min.cu to all fundamental types * Add some notes on how to collect tuning parameters Fixes: #3283 Update upload-pages-artifact to v3 (#3423) * Update upload-pages-artifact to v3 * Empty commit --------- Co-authored-by: Ashwin Srinath <[email protected]> Replace and deprecate thrust::cuda_cub::terminate (#3421) `std::linalg` accessors and `transposed_layout` (#2962) Add round up/down to multiple (#3234) [FEA]: Introduce Python module with CCCL headers (#3201) * Add cccl/python/cuda_cccl directory and use from cuda_parallel, cuda_cooperative * Run `copy_cccl_headers_to_aude_include()` before `setup()` * Create python/cuda_cccl/cuda/_include/__init__.py, then simply import cuda._include to find the include path. * Add cuda.cccl._version exactly as for cuda.cooperative and cuda.parallel * Bug fix: cuda/_include only exists after shutil.copytree() ran. * Use `f"cuda-cccl @ file://{cccl_path}/python/cuda_cccl"` in setup.py * Remove CustomBuildCommand, CustomWheelBuild in cuda_parallel/setup.py (they are equivalent to the default functions) * Replace := operator (needs Python 3.8+) * Fix oversights: remove `pip3 install ./cuda_cccl` lines from README.md * Restore original README.md: `pip3 install -e` now works on first pass. * cuda_cccl/README.md: FOR INTERNAL USE ONLY * Remove `$pymajor.$pyminor.` prefix in cuda_cccl _version.py (as suggested under https://github.com/NVIDIA/cccl/pull/3201#discussion_r1894035917) Command used: ci/update_version.sh 2 8 0 * Modernize pyproject.toml, setup.py Trigger for this change: * https://github.com/NVIDIA/cccl/pull/3201#discussion_r1894043178 * https://github.com/NVIDIA/cccl/pull/3201#discussion_r1894044996 * Install CCCL headers under cuda.cccl.include Trigger for this change: * https://github.com/NVIDIA/cccl/pull/3201#discussion_r1894048562 Unexpected accidental discovery: cuda.cooperative unit tests pass without CCCL headers entirely. * Factor out cuda_cccl/cuda/cccl/include_paths.py * Reuse cuda_cccl/cuda/cccl/include_paths.py from cuda_cooperative * Add missing Copyright notice. * Add missing __init__.py (cuda.cccl) * Add `"cuda.cccl"` to `autodoc.mock_imports` * Move cuda.cccl.include_paths into function where it is used. (Attempt to resolve Build and Verify Docs failure.) * Add # TODO: move this to a module-level import * Modernize cuda_cooperative/pyproject.toml, setup.py * Convert cuda_cooperative to use hatchling as build backend. * Revert "Convert cuda_cooperative to use hatchling as build backend." This reverts commit 61637d608da06fcf6851ef6197f88b5e7dbc3bbe. * Move numpy from [build-system] requires -> [project] dependencies * Move pyproject.toml [project] dependencies -> setup.py install_requires, to be able to use CCCL_PATH * Remove copy_license() and use license_files=["../../LICENSE"] instead. * Further modernize cuda_cccl/setup.py to use pathlib * Trivial simplifications in cuda_cccl/pyproject.toml * Further simplify cuda_cccl/pyproject.toml, setup.py: remove inconsequential code * Make cuda_cooperative/pyproject.toml more similar to cuda_cccl/pyproject.toml * Add taplo-pre-commit to .pre-commit-config.yaml * taplo-pre-commit auto-fixes * Use pathlib in cuda_cooperative/setup.py * CCCL_PYTHON_PATH in cuda_cooperative/setup.py * Modernize cuda_parallel/pyproject.toml, setup.py * Use pathlib in cuda_parallel/setup.py * Add `# TOML lint & format` comment. * Replace MANIFEST.in with `[tool.setuptools.package-data]` section in pyproject.toml * Use pathlib in cuda/cccl/include_paths.py * pre-commit autoupdate (EXCEPT clang-format, which was manually restored) * Fixes after git merge main * Resolve warning: AttributeError: '_Reduce' object has no attribute 'build_result' ``` =========================================================================== warnings summary =========================================================================== tests/test_reduce.py::test_reduce_non_contiguous /home/coder/cccl/python/devenv/lib/python3.12/site-packages/_pytest/unraisableexception.py:85: PytestUnraisableExceptionWarning: Exception ignored in: <function _Reduce.__del__ at 0x7bf123139080> Traceback (most recent call last): File "/home/coder/cccl/python/cuda_parallel/cuda/parallel/experimental/algorithms/reduce.py", line 132, in __del__ bindings.cccl_device_reduce_cleanup(ctypes.byref(self.build_result)) ^^^^^^^^^^^^^^^^^ AttributeError: '_Reduce' object has no attribute 'build_result' warnings.warn(pytest.PytestUnraisableExceptionWarning(msg)) -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html ============================================================= 1 passed, 93 deselected, 1 warning in 0.44s ============================================================== ``` * Move `copy_cccl_headers_to_cuda_cccl_include()` functionality to `class CustomBuildPy` * Introduce cuda_cooperative/constraints.txt * Also add cuda_parallel/constraints.txt * Add `--constraint constraints.txt` in ci/test_python.sh * Update Copyright dates * Switch to https://github.com/ComPWA/taplo-pre-commit (the other repo has been archived by the owner on Jul 1, 2024) For completeness: The other repo took a long time to install into the pre-commit cache; so long it lead to timeouts in the CCCL CI. * Remove unused cuda_parallel jinja2 dependency (noticed by chance). * Remove constraints.txt files, advertise running `pip install cuda-cccl` first instead. * Make cuda_cooperative, cuda_parallel testing completely independent. * Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc] * Try using another runner (because V100 runners seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Fix sign-compare warning (#3408) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Revert "Try using another runner (because V100 runners seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc]" This reverts commit ea33a218ed77a075156cd1b332047202adb25aa2. Error message: https://github.com/NVIDIA/cccl/pull/3201#issuecomment-2594012971 * Try using A100 runner (because V100 runners still seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Also show cuda-cooperative site-packages, cuda-parallel site-packages (after pip install) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Try using l4 runner (because V100 runners still seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Restore original ci/matrix.yaml [skip-rapids] * Use for loop in test_python.sh to avoid code duplication. * Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc][skip pre-commit.ci] * Comment out taplo-lint in pre-commit config [skip-rapids][skip-matx][skip-docs][skip-vdc] * Revert "Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc][skip pre-commit.ci]" This reverts commit ec206fd8b50a6a293e00a5825b579e125010b13d. * Implement suggestion by @shwina (https://github.com/NVIDIA/cccl/pull/3201#pullrequestreview-2556918460) * Address feedback by @leofang --------- Co-authored-by: Bernhard Manfred Gruber <[email protected]> cuda.parallel: Add optional stream argument to reduce_into() (#3348) * Add optional stream argument to reduce_into() * Add tests to check for reduce_into() stream behavior * Move protocol related utils to separate file and rework __cuda_stream__ error messages * Fix synchronization issue in stream test and add one more invalid stream test case * Rename cuda stream validation function after removing leading underscore * Unpack values from __cuda_stream__ instead of indexing * Fix linting errors * Handle TypeError when unpacking invalid __cuda_stream__ return * Use stream to allocate cupy memory in new stream test Upgrade to actions/deploy-pages@v4 (from v2), as suggested by @leofang (#3434) Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ (#3419) * Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ Fixes #3404 Fix CI issues (#3443) update docs fix review restrict allowed types replace constexpr implementations with generic optimize `__is_arithmetic_integral`

) * Introduce gpu_struct decorator and typing * Enable `reduce` to accept arrays of structs as inputs * Add test for reducing arrays-of-struct * Update documentation * Use a numpy array rather than ctypes object * Change zeros -> empty for output array and temp storage * Add a TODO for typing GpuStruct * Documentation udpates * Remove test_reduce_struct_type from test_reduce.py * Revert to `to_cccl_value()` accepting ndarray + GpuStruct * Bump copyrights --------- Co-authored-by: Ashwin Srinath <[email protected]>

@shwina

update docs update docs add `memcmp`, `memmove` and `memchr` implementations implement tests Use cuda::std::min/max in Thrust (NVIDIA#3364) Implement `cuda::std::numeric_limits` for `__half` and `__nv_bfloat16` (NVIDIA#3361) * implement `cuda::std::numeric_limits` for `__half` and `__nv_bfloat16` Cleanup util_arch (NVIDIA#2773) Deprecate thrust::null_type (NVIDIA#3367) Deprecate cub::DeviceSpmv (NVIDIA#3320) Fixes: NVIDIA#896 Improves `DeviceSegmentedSort` test run time for large number of items and segments (NVIDIA#3246) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * fixes spelling * adds tests for large number of segments * fixes narrowing conversion in tests * addresses review comments * fixes includes Compile basic infra test with C++17 (NVIDIA#3377) Adds support for large number of items and large number of segments to `DeviceSegmentedSort` (NVIDIA#3308) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * addresses review comments * introduces segment offset type * adds tests for large number of segments * adds support for large number of segments * drops segment offset type * fixes thrust namespace * removes about-to-be-deprecated cub iterators * no exec specifier on defaulted ctor * fixes gcc7 linker error * uses local_segment_index_t throughout * determine offset type based on type returned by segment iterator begin/end iterators * minor style improvements Exit with error when RAPIDS CI fails. (NVIDIA#3385) cuda.parallel: Support structured types as algorithm inputs (NVIDIA#3218) * Introduce gpu_struct decorator and typing * Enable `reduce` to accept arrays of structs as inputs * Add test for reducing arrays-of-struct * Update documentation * Use a numpy array rather than ctypes object * Change zeros -> empty for output array and temp storage * Add a TODO for typing GpuStruct * Documentation udpates * Remove test_reduce_struct_type from test_reduce.py * Revert to `to_cccl_value()` accepting ndarray + GpuStruct * Bump copyrights --------- Co-authored-by: Ashwin Srinath <[email protected]> Deprecate thrust::async (NVIDIA#3324) Fixes: NVIDIA#100 Review/Deprecate CUB `util.ptx` for CCCL 2.x (NVIDIA#3342) Fix broken `_CCCL_BUILTIN_ASSUME` macro (NVIDIA#3314) * add compiler-specific path * fix device code path * add _CCC_ASSUME Deprecate thrust::numeric_limits (NVIDIA#3366) Replace `typedef` with `using` in libcu++ (NVIDIA#3368) Deprecate thrust::optional (NVIDIA#3307) Fixes: NVIDIA#3306 Upgrade to Catch2 3.8 (NVIDIA#3310) Fixes: NVIDIA#1724 refactor `<cuda/std/cstdint>` (NVIDIA#3325) Co-authored-by: Bernhard Manfred Gruber <[email protected]> Update CODEOWNERS (NVIDIA#3331) * Update CODEOWNERS * Update CODEOWNERS * Update CODEOWNERS * [pre-commit.ci] auto code formatting --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Fix sign-compare warning (NVIDIA#3408) Implement more cmath functions to be usable on host and device (NVIDIA#3382) * Implement more cmath functions to be usable on host and device * Implement math roots functions * Implement exponential functions Redefine and deprecate thrust::remove_cvref (NVIDIA#3394) * Redefine and deprecate thrust::remove_cvref Co-authored-by: Michael Schellenberger Costa <[email protected]> Fix assert definition for NVHPC due to constexpr issues (NVIDIA#3418) NVHPC cannot decide at compile time where the code would run so _CCCL_ASSERT within a constexpr function breaks it. Fix this by always using the host definition which should also work on device. Fixes NVIDIA#3411 Extend CUB reduce benchmarks (NVIDIA#3401) * Rename max.cu to custom.cu, since it uses a custom operator * Extend types covered my min.cu to all fundamental types * Add some notes on how to collect tuning parameters Fixes: NVIDIA#3283 Update upload-pages-artifact to v3 (NVIDIA#3423) * Update upload-pages-artifact to v3 * Empty commit --------- Co-authored-by: Ashwin Srinath <[email protected]> Replace and deprecate thrust::cuda_cub::terminate (NVIDIA#3421) `std::linalg` accessors and `transposed_layout` (NVIDIA#2962) Add round up/down to multiple (NVIDIA#3234) [FEA]: Introduce Python module with CCCL headers (NVIDIA#3201) * Add cccl/python/cuda_cccl directory and use from cuda_parallel, cuda_cooperative * Run `copy_cccl_headers_to_aude_include()` before `setup()` * Create python/cuda_cccl/cuda/_include/__init__.py, then simply import cuda._include to find the include path. * Add cuda.cccl._version exactly as for cuda.cooperative and cuda.parallel * Bug fix: cuda/_include only exists after shutil.copytree() ran. * Use `f"cuda-cccl @ file://{cccl_path}/python/cuda_cccl"` in setup.py * Remove CustomBuildCommand, CustomWheelBuild in cuda_parallel/setup.py (they are equivalent to the default functions) * Replace := operator (needs Python 3.8+) * Fix oversights: remove `pip3 install ./cuda_cccl` lines from README.md * Restore original README.md: `pip3 install -e` now works on first pass. * cuda_cccl/README.md: FOR INTERNAL USE ONLY * Remove `$pymajor.$pyminor.` prefix in cuda_cccl _version.py (as suggested under NVIDIA#3201 (comment)) Command used: ci/update_version.sh 2 8 0 * Modernize pyproject.toml, setup.py Trigger for this change: * NVIDIA#3201 (comment) * NVIDIA#3201 (comment) * Install CCCL headers under cuda.cccl.include Trigger for this change: * NVIDIA#3201 (comment) Unexpected accidental discovery: cuda.cooperative unit tests pass without CCCL headers entirely. * Factor out cuda_cccl/cuda/cccl/include_paths.py * Reuse cuda_cccl/cuda/cccl/include_paths.py from cuda_cooperative * Add missing Copyright notice. * Add missing __init__.py (cuda.cccl) * Add `"cuda.cccl"` to `autodoc.mock_imports` * Move cuda.cccl.include_paths into function where it is used. (Attempt to resolve Build and Verify Docs failure.) * Add # TODO: move this to a module-level import * Modernize cuda_cooperative/pyproject.toml, setup.py * Convert cuda_cooperative to use hatchling as build backend. * Revert "Convert cuda_cooperative to use hatchling as build backend." This reverts commit 61637d6. * Move numpy from [build-system] requires -> [project] dependencies * Move pyproject.toml [project] dependencies -> setup.py install_requires, to be able to use CCCL_PATH * Remove copy_license() and use license_files=["../../LICENSE"] instead. * Further modernize cuda_cccl/setup.py to use pathlib * Trivial simplifications in cuda_cccl/pyproject.toml * Further simplify cuda_cccl/pyproject.toml, setup.py: remove inconsequential code * Make cuda_cooperative/pyproject.toml more similar to cuda_cccl/pyproject.toml * Add taplo-pre-commit to .pre-commit-config.yaml * taplo-pre-commit auto-fixes * Use pathlib in cuda_cooperative/setup.py * CCCL_PYTHON_PATH in cuda_cooperative/setup.py * Modernize cuda_parallel/pyproject.toml, setup.py * Use pathlib in cuda_parallel/setup.py * Add `# TOML lint & format` comment. * Replace MANIFEST.in with `[tool.setuptools.package-data]` section in pyproject.toml * Use pathlib in cuda/cccl/include_paths.py * pre-commit autoupdate (EXCEPT clang-format, which was manually restored) * Fixes after git merge main * Resolve warning: AttributeError: '_Reduce' object has no attribute 'build_result' ``` =========================================================================== warnings summary =========================================================================== tests/test_reduce.py::test_reduce_non_contiguous /home/coder/cccl/python/devenv/lib/python3.12/site-packages/_pytest/unraisableexception.py:85: PytestUnraisableExceptionWarning: Exception ignored in: <function _Reduce.__del__ at 0x7bf123139080> Traceback (most recent call last): File "/home/coder/cccl/python/cuda_parallel/cuda/parallel/experimental/algorithms/reduce.py", line 132, in __del__ bindings.cccl_device_reduce_cleanup(ctypes.byref(self.build_result)) ^^^^^^^^^^^^^^^^^ AttributeError: '_Reduce' object has no attribute 'build_result' warnings.warn(pytest.PytestUnraisableExceptionWarning(msg)) -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html ============================================================= 1 passed, 93 deselected, 1 warning in 0.44s ============================================================== ``` * Move `copy_cccl_headers_to_cuda_cccl_include()` functionality to `class CustomBuildPy` * Introduce cuda_cooperative/constraints.txt * Also add cuda_parallel/constraints.txt * Add `--constraint constraints.txt` in ci/test_python.sh * Update Copyright dates * Switch to https://github.com/ComPWA/taplo-pre-commit (the other repo has been archived by the owner on Jul 1, 2024) For completeness: The other repo took a long time to install into the pre-commit cache; so long it lead to timeouts in the CCCL CI. * Remove unused cuda_parallel jinja2 dependency (noticed by chance). * Remove constraints.txt files, advertise running `pip install cuda-cccl` first instead. * Make cuda_cooperative, cuda_parallel testing completely independent. * Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc] * Try using another runner (because V100 runners seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Fix sign-compare warning (NVIDIA#3408) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Revert "Try using another runner (because V100 runners seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc]" This reverts commit ea33a21. Error message: NVIDIA#3201 (comment) * Try using A100 runner (because V100 runners still seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Also show cuda-cooperative site-packages, cuda-parallel site-packages (after pip install) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Try using l4 runner (because V100 runners still seem to be stuck) [skip-rapids][skip-matx][skip-docs][skip-vdc] * Restore original ci/matrix.yaml [skip-rapids] * Use for loop in test_python.sh to avoid code duplication. * Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc][skip pre-commit.ci] * Comment out taplo-lint in pre-commit config [skip-rapids][skip-matx][skip-docs][skip-vdc] * Revert "Run only test_python.sh [skip-rapids][skip-matx][skip-docs][skip-vdc][skip pre-commit.ci]" This reverts commit ec206fd. * Implement suggestion by @shwina (NVIDIA#3201 (review)) * Address feedback by @leofang --------- Co-authored-by: Bernhard Manfred Gruber <[email protected]> cuda.parallel: Add optional stream argument to reduce_into() (NVIDIA#3348) * Add optional stream argument to reduce_into() * Add tests to check for reduce_into() stream behavior * Move protocol related utils to separate file and rework __cuda_stream__ error messages * Fix synchronization issue in stream test and add one more invalid stream test case * Rename cuda stream validation function after removing leading underscore * Unpack values from __cuda_stream__ instead of indexing * Fix linting errors * Handle TypeError when unpacking invalid __cuda_stream__ return * Use stream to allocate cupy memory in new stream test Upgrade to actions/deploy-pages@v4 (from v2), as suggested by @leofang (NVIDIA#3434) Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ (NVIDIA#3419) * Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ Fixes NVIDIA#3404 Fix CI issues (NVIDIA#3443) Remove deprecated `cub::min` (NVIDIA#3450) * Remove deprecated `cuda::{min,max}` * Drop unused `thrust::remove_cvref` file Fix typo in builtin (NVIDIA#3451) Moves agents to `detail::<algorithm_name>` namespace (NVIDIA#3435) uses unsigned offset types in thrust's scan dispatch (NVIDIA#3436) Default transform_iterator's copy ctor (NVIDIA#3395) Fixes: NVIDIA#2393 Turn C++ dialect warning into error (NVIDIA#3453) Uses unsigned offset types in thrust's sort algorithm calling into `DispatchMergeSort` (NVIDIA#3437) * uses thrust's dynamic dispatch for merge_sort * [pre-commit.ci] auto code formatting --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Refactor allocator handling of contiguous_storage (NVIDIA#3050) Co-authored-by: Michael Schellenberger Costa <[email protected]> Drop thrust::detail::integer_traits (NVIDIA#3391) Add cuda::is_floating_point supporting half and bfloat (NVIDIA#3379) Co-authored-by: Michael Schellenberger Costa <[email protected]> Improve docs of std headers (NVIDIA#3416) Drop C++11 and C++14 support for all of cccl (NVIDIA#3417) * Drop C++11 and C++14 support for all of cccl --------- Co-authored-by: Bernhard Manfred Gruber <[email protected]> Deprecate a few CUB macros (NVIDIA#3456) Deprecate thrust universal iterator categories (NVIDIA#3461) Fix launch args order (NVIDIA#3465) Add `--extended-lambda` to the list of removed clangd flags (NVIDIA#3432) add `_CCCL_HAS_NVFP8` macro (NVIDIA#3429) Add `_CCCL_BUILTIN_PREFETCH` (NVIDIA#3433) Drop universal iterator categories (NVIDIA#3474) Ensure that headers in `<cuda/*>` can be build with a C++ only compiler (NVIDIA#3472) Specialize __is_extended_floating_point for FP8 types (NVIDIA#3470) Also ensure that we actually can enable FP8 due to FP16 and BF16 requirements Co-authored-by: Michael Schellenberger Costa <[email protected]> Moves CUB kernel entry points to a detail namespace (NVIDIA#3468) * moves emptykernel to detail ns * second batch * third batch * fourth batch * fixes cuda parallel * concatenates nested namespaces Deprecate block/warp algo specializations (NVIDIA#3455) Fixes: NVIDIA#3409 Refactor CUB's util_debug (NVIDIA#3345)

) * Introduce gpu_struct decorator and typing * Enable `reduce` to accept arrays of structs as inputs * Add test for reducing arrays-of-struct * Update documentation * Use a numpy array rather than ctypes object * Change zeros -> empty for output array and temp storage * Add a TODO for typing GpuStruct * Documentation udpates * Remove test_reduce_struct_type from test_reduce.py * Revert to `to_cccl_value()` accepting ndarray + GpuStruct * Bump copyrights --------- Co-authored-by: Ashwin Srinath <[email protected]>

Cleanup util_arch (NVIDIA#2773) Improves `DeviceSegmentedSort` test run time for large number of items and segments (NVIDIA#3246) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * fixes spelling * adds tests for large number of segments * fixes narrowing conversion in tests * addresses review comments * fixes includes Adds support for large number of items and large number of segments to `DeviceSegmentedSort` (NVIDIA#3308) * fixes segment offset generation * switches to analytical verification * switches to analytical verification for pairs * addresses review comments * introduces segment offset type * adds tests for large number of segments * adds support for large number of segments * drops segment offset type * fixes thrust namespace * removes about-to-be-deprecated cub iterators * no exec specifier on defaulted ctor * fixes gcc7 linker error * uses local_segment_index_t throughout * determine offset type based on type returned by segment iterator begin/end iterators * minor style improvements cuda.parallel: Support structured types as algorithm inputs (NVIDIA#3218) * Introduce gpu_struct decorator and typing * Enable `reduce` to accept arrays of structs as inputs * Add test for reducing arrays-of-struct * Update documentation * Use a numpy array rather than ctypes object * Change zeros -> empty for output array and temp storage * Add a TODO for typing GpuStruct * Documentation udpates * Remove test_reduce_struct_type from test_reduce.py * Revert to `to_cccl_value()` accepting ndarray + GpuStruct * Bump copyrights --------- Co-authored-by: Ashwin Srinath <[email protected]> Deprecate thrust::async (NVIDIA#3324) Fixes: NVIDIA#100 Review/Deprecate CUB `util.ptx` for CCCL 2.x (NVIDIA#3342) Deprecate thrust::numeric_limits (NVIDIA#3366) Upgrade to Catch2 3.8 (NVIDIA#3310) Fixes: NVIDIA#1724 Fix sign-compare warning (NVIDIA#3408) Implement more cmath functions to be usable on host and device (NVIDIA#3382) * Implement more cmath functions to be usable on host and device * Implement math roots functions * Implement exponential functions Redefine and deprecate thrust::remove_cvref (NVIDIA#3394) * Redefine and deprecate thrust::remove_cvref Co-authored-by: Michael Schellenberger Costa <[email protected]> cuda.parallel: Add optional stream argument to reduce_into() (NVIDIA#3348) * Add optional stream argument to reduce_into() * Add tests to check for reduce_into() stream behavior * Move protocol related utils to separate file and rework __cuda_stream__ error messages * Fix synchronization issue in stream test and add one more invalid stream test case * Rename cuda stream validation function after removing leading underscore * Unpack values from __cuda_stream__ instead of indexing * Fix linting errors * Handle TypeError when unpacking invalid __cuda_stream__ return * Use stream to allocate cupy memory in new stream test Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ (NVIDIA#3419) * Deprecate `cub::{min, max}` and replace internal uses with those from libcu++ Fixes NVIDIA#3404 Remove deprecated `cub::min` (NVIDIA#3450) * Remove deprecated `cuda::{min,max}` * Drop unused `thrust::remove_cvref` file Fix typo in builtin (NVIDIA#3451) Moves agents to `detail::<algorithm_name>` namespace (NVIDIA#3435) Drop thrust::detail::integer_traits (NVIDIA#3391) Add cuda::is_floating_point supporting half and bfloat (NVIDIA#3379) Co-authored-by: Michael Schellenberger Costa <[email protected]> add `_CCCL_HAS_NVFP8` macro (NVIDIA#3429) Specialize __is_extended_floating_point for FP8 types (NVIDIA#3470) Also ensure that we actually can enable FP8 due to FP16 and BF16 requirements Co-authored-by: Michael Schellenberger Costa <[email protected]> Moves CUB kernel entry points to a detail namespace (NVIDIA#3468) * moves emptykernel to detail ns * second batch * third batch * fourth batch * fixes cuda parallel * concatenates nested namespaces Deprecate block/warp algo specializations (NVIDIA#3455) Fixes: NVIDIA#3409 fix documentation

) * Introduce gpu_struct decorator and typing * Enable `reduce` to accept arrays of structs as inputs * Add test for reducing arrays-of-struct * Update documentation * Use a numpy array rather than ctypes object * Change zeros -> empty for output array and temp storage * Add a TODO for typing GpuStruct * Documentation udpates * Remove test_reduce_struct_type from test_reduce.py * Revert to `to_cccl_value()` accepting ndarray + GpuStruct * Bump copyrights --------- Co-authored-by: Ashwin Srinath <[email protected]>

shwina commented Dec 25, 2024

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shwina force-pushed the cuda-parallel-support-structured-dtypes branch 5 times, most recently from 33b6a96 to 78c8947 Compare January 7, 2025 21:01

shwina force-pushed the cuda-parallel-support-structured-dtypes branch from 78c8947 to b031ecf Compare January 7, 2025 21:10

shwina force-pushed the cuda-parallel-support-structured-dtypes branch from b031ecf to 2f8b7bf Compare January 7, 2025 21:38

shwina force-pushed the cuda-parallel-support-structured-dtypes branch 2 times, most recently from 754832e to 3316d3f Compare January 8, 2025 13:30

shwina marked this pull request as ready for review January 8, 2025 14:23

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shwina force-pushed the cuda-parallel-support-structured-dtypes branch from 3316d3f to 256f6bb Compare January 8, 2025 14:27

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shwina force-pushed the cuda-parallel-support-structured-dtypes branch from 256f6bb to 06c924d Compare January 8, 2025 17:25

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shwina force-pushed the cuda-parallel-support-structured-dtypes branch from c53efe9 to 024a574 Compare January 13, 2025 21:58

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NaderAlAwar approved these changes Jan 14, 2025

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shwina added 11 commits January 14, 2025 14:12

Introduce gpu_struct decorator and typing

dcdfd1f

Enable reduce to accept arrays of structs as inputs

2a53620

Add test for reducing arrays-of-struct

11aeab2

Update documentation

5ff1f19

Use a numpy array rather than ctypes object

5706a5a

Change zeros -> empty for output array and temp storage

1f6ddf7

Add a TODO for typing GpuStruct

426f528

Documentation udpates

d440678

Remove test_reduce_struct_type from test_reduce.py

7206e99

Revert to to_cccl_value() accepting ndarray + GpuStruct

e75bc7c

Bump copyrights

8ea0fc9

shwina force-pushed the cuda-parallel-support-structured-dtypes branch from 75b65ef to 8ea0fc9 Compare January 14, 2025 19:25

shwina merged commit 2dec379 into NVIDIA:main Jan 14, 2025
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cuda.parallel: Support structured types as algorithm inputs #3218

cuda.parallel: Support structured types as algorithm inputs #3218

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shwina commented Dec 25, 2024 • edited Loading

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Why not use structured dtypes?

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🟩 python: Pass: 100%/1 | Total: 24m 05s | Avg: 24m 05s | Max: 24m 05s

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shwina commented Jan 7, 2025

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🟩 python: Pass: 100%/1 | Total: 24m 07s | Avg: 24m 07s | Max: 24m 07s

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🟩 python: Pass: 100%/1 | Total: 24m 41s | Avg: 24m 41s | Max: 24m 41s

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🟩 python: Pass: 100%/1 | Total: 31m 14s | Avg: 31m 14s | Max: 31m 14s

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🟩 python: Pass: 100%/1 | Total: 26m 21s | Avg: 26m 21s | Max: 26m 21s

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🟩 python: Pass: 100%/1 | Total: 36m 21s | Avg: 36m 21s | Max: 36m 21s

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🟩 python: Pass: 100%/1 | Total: 27m 58s | Avg: 27m 58s | Max: 27m 58s

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shwina commented Dec 25, 2024 •

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