Initial CUDA C++ Execution Model documentation

docs/libcudacxx/extended_api.rst

@@ -6,6 +6,7 @@ Extended API
 .. toctree::
    :maxdepth: 2
 
+   extended_api/execution_model
    extended_api/memory_model
    extended_api/thread_groups
    extended_api/shapes

docs/libcudacxx/extended_api/execution_model.rst

@@ -0,0 +1,254 @@
+.. _libcudacxx-extended-api-execution-model:
+
+Execution model
+===============
+
+CUDA C++ aims to provide `_parallel forward progress_ [intro.progress.9] <https://eel.is/c++draft/intro.progress#9>`__ 
+for all device threads of execution, making the parallelization of pre-existing C++ applications with CUDA C++ straight-forward.
+
+.. dropdown:: [intro.progress]
+
+    - `[intro.progress.7] <https://eel.is/c++draft/intro.progress#7>`__: For a thread of execution
+      providing `concurrent forward progress guarantees <https://eel.is/c++draft/intro.progress#def:concurrent_forward_progress_guarantees>`__, 
+      the implementation ensures that the thread will eventually make progress for as long as it has not terminated.
+
+      [Note 5: This applies regardless of whether or not other threads of execution (if any) have been or are making progress. 
+      To eventually fulfill this requirement means that this will happen in an unspecified but finite amount of time. — end note]
+
+    - `[intro.progress.9] <https://eel.is/c++draft/intro.progress>`__: For a thread of execution providing
+      `parallel forward progress guarantees <https://eel.is/c++draft/intro.progress#9>`__, the implementation is not required to ensure that
+      the thread will eventually make progress if it has not yet executed any execution step; once this thread has executed a step, 
+      it provides concurrent forward progress guarantees.
+
+      [Note 6: This does not specify a requirement for when to start this thread of execution, which will typically be specified by the entity
+      that creates this thread of execution. For example, a thread of execution that provides concurrent forward progress guarantees and executes
+      tasks from a set of tasks in an arbitrary order, one after the other, satisfies the requirements of parallel forward progress for these
+      tasks. — end note]
+
+.. _libcudacxx-extended-api-execution-model-host-threads:
+
+Host threads
+------------
+
+The forward-progress provided by threads of execution created by the host implementation to
+execute `main <https://en.cppreference.com/w/cpp/language/main_function>`__, `std::thread <https://en.cppreference.com/w/cpp/thread/thread>`__,
+and `std::jthread https://en.cppreference.com/w/cpp/thread/jthread>`__ is implementation-defined behavior of the host
+implementation `[intro.progress] <https://eel.is/c++draft/intro.progress>`__. 
+General-purpose host implementations should provide _concurrent forward progress_.
+
+If the host implementation provides `_concurrent forward progress_ [intro.progress.7] <https://eel.is/c++draft/intro.progress#7>`__,
+then CUDA C++ provides `_parallel forward progress_ [intro.progress.9] <https://eel.is/c++draft/intro.progress#9>`__ for device threads.
+
+
+.. _libcudacxx-extended-api-execution-model-device-threads:
+
+Device threads
+--------------
+
+Once a device thread makes progress:
+
+- If the device thread is part of a `Cooperative Grid <https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__EXECUTION.html#group__CUDART__EXECUTION_1g504b94170f83285c71031be6d5d15f73>`__,
+  then all device threads in its grid shall eventually make progress.
+_ Otherwise, all device threads in its `thread-block cluster <https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#thread-block-clusters>`__ 
+  shall eventually make progress.
+
+  [Note: Threads in other thread-block clusters are not guaranteed to eventually make progress. - end note.]
+  [Note: This implies that all device-threads in its thread block shall eventually make progress. - end note.]
+
+The order in which device threads eventually get a chance to make progress is _unspecified_.
+
+Modify `[intro.progress.1] <https://eel.is/c++draft/intro.progress>`__ as follows (modifications in **bold**):
+
+The implementation may assume that any **host** thread will eventually do one of the following:
+
+    1. terminate,
+    2. invoke the function `std::this_thread::yield <https://en.cppreference.com/w/cpp/thread/yield>`__ (`[thread.thread.this] <http://eel.is/c++draft/thread.thread.this>`__),
+    3. make a call to a library I/O function,
+    4. perform an access through a volatile glvalue,
+    5. perform a synchronization operation or an atomic operation, or
+    6. continue execution of a trivial infinite loop (`[stmt.iter.general] <http://eel.is/c++draft/stmt.iter.general>`__).
+
+**The implementation may assume that any device thread will eventually do one of the following:**
+
+    1. **terminate**,
+    2. **make a call to a library I/O function**,
+    3. **perform an access through a volatile glvalue except if the designated object has automatic storage duration, or**
+    4. **perform a synchronization operation or an atomic read operation except if the designated object has automatic storage duration.**
+
+.. dropdown:: Examples of forward progress guarantee differences between host and device threads due to modifications to [intro.progress.1].
+
+    The following examples refer to the itemized sub-clauses of the implementation assumptions for host and device threads above
+    using "host.threads.<id>" and "device.threads.<id>", respectively.
+
+    .. code:: cuda
+        // Example: Execution.Model.Device.0
+        // Outcome: grid eventually terminates per device.threads.4 because the atomic object does not have automatic storage duration.
+        __global__ void ii(cuda::atomic_ref<int, cuda::thread_scope_device> atom) {
+            if (threadIdx.x == 0) {
+                while(atom.load(cuda::memory_order_relaxed) == 0);
+            } else if (threadIdx.x == 1) {
+                atom.store(1, cuda::memory_order_relaxed);
+            }
+        }
+
+    .. code:: cuda
+        // Example: Execution.Model.Device.1
+        // Allowed outcome: No thread makes progress because device threads don't support host.threads.2.
+        __global__ void ii() {
+            while(true) std::this_thread::yield();
+        }
+
+    .. code:: cuda
+        // Example: Execution.Model.Device.2
+        // Allowed outcome: No thread makes progress because device threads don't support host.threads.4
+        // for objects with automatic storage duration (see exception in device.threads.3).
+        __global__ void iv() {
+            volatile bool True = true;
+            while(True);
+        }
+
+    .. code:: cuda
+        // Example: Execution.Model.Device.3
+        // Allowed outcome: No thread makes progress because device threads don't support host.threads.5
+        // for objects with automatic storage duration (see exception in device.threads.4).
+        __global__ void v_atomic_automatic() {
+            cuda::atomic<bool, cuda::thread_scope_thread> True = true;
+            while(True.load());
+        }
+
+    .. code:: cuda
+        // Example: Execution.Model.Device.4
+        // Allowed outcome: No thread makes progress because device threads don't support host.thread.6.
+        __global void vi() {
+            while(true) { /* empty */ }
+        }
+
+.. _libcudacxx-extended-api-execution-model-cuda-apis:
+
+CUDA APIs
+---------
+
+Any CUDA API shall eventually either return or ensure at least one device-thread makes progress.
+
+CUDA query functions (e.g. `cudaStreamQuery <https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__STREAM.html#group__CUDART__STREAM_1g2021adeb17905c7ec2a3c1bf125c5435>`__,
+`cudaEventQuery <https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__EVENT.html#group__CUDART__EVENT_1g2bf738909b4a059023537eaa29d8a5b7>`__, etc.) shall not consistently 
+return ``cudaErrorNotReady`` without a device-thread making progress.
+
+[Note: The device-thread need not be "related" to the API call, e.g., an API operating on one stream or process may ensure progress of a device-thread on another stream or process. - end note.]
+
+[Note: A simple but not sufficient method to test workloads for CUDA API Forward Progress conformance is to run them with following environment variables set: ``CUDA_DEVICE_MAX_CONNECTIONS=1 CUDA_LAUNCH_BLOCKING=1`` - end note.]
+
+.. dropdown:: Examples of CUDA API forward progress guarantees.
+
+    .. code:: cuda
+        // Example: Execution.Model.API.1 
+        // Outcome: if device empty, terminates and returns cudaSuccess.
+        // Rationale: CUDA guarantees that if the device is empty:
+        // - `cudaDeviceSynchronize` eventually ensures that at least one device-thread makes progress, which implies that eventually `hello_world` grid and one of its device-threads start.
+        // - All thread-block threads eventually start (due to "if a device thread makes progress, all other threads in its thread-block cluster eventually make progress").
+        // - Once all threads in thread-block arrive at `__syncthreads` barrier, all waiting threads are unblocked.
+        // - Therefore all device threads eventually exit the `hello_world`` grid.
+        // - And `cudaDeviceSynchronize`` eventually unblocks.
+        __global__ void hello_world() { __syncthreads(); }
+        int main() {
+            hello_world<<<1,2>>>();
+            return (int)cudaDeviceSynchronize();
+        }
+
+    .. code:: cuda
+        // Example: Execution.Model.API.2
+        // Allowed outcome: eventually, no thread makes progress.
+        // Rationale: the `cudaDeviceSynchronize` API below is only called if a device thread eventually makes progress and sets the flag.
+        // However, CUDA only guarantees that `producer` device thread eventually starts if the synchronization API is called.
+        // Therefore, the host thread may never be unblocked from the flag spin-loop.
+        cuda::atomic<int, cuda::thread_scope_system> flag = 0;
+        __global__ void producer() { flag.store(1); }
+        int main() {
+            cudaHostRegister(&flag, sizeof(flag));
+            producer<<<1,1>>>();
+            while (flag.load() == 0);
+            return cudaDeviceSynchronize();
+        }
+
+    .. code:: cuda
+        // Example: Execution.Model.API.3
+        // Allowed outcome: eventually, no thread makes progress.
+        // Rationale: same as Example.Model.API.2, with the addition that a single CUDA query API call does not guarantee
+        // the device thread eventually starts, only repeated CUDA query API calls do (see Execution.Model.API.4).
+        cuda::atomic<int, cuda::thread_scope_system> flag = 0;
+        __global__ void producer() { flag.store(1); }
+        int main() {
+            cudaHostRegister(&flag, sizeof(flag));
+            producer<<<1,1>>>();
+            (void)cudaStreamQuery(0);
+            while (flag.load() == 0);
+            return cudaDeviceSynchronize();
+        }
+
+    .. code:: cuda
+        // Example: Execution.Model.API.4
+        // Outcome: terminates.
+        // Rationale: same as Execution.Model.API.3, but this example repeatedly calls
+        // a CUDA query API in within the flag spin-loop, which guarantees that the device thread
+        // eventually makes progress.
+        cuda::atomic<int, cuda::thread_scope_system> flag = 0;
+        __global__ void producer() { flag.store(1); }
+        int main() {
+            cudaHostRegister(&flag, sizeof(flag));
+            producer<<<1,1>>>();
+            while (flag.load() == 0) { 
+                (void)cudaStreamQuery(0);
+            }
+            return cudaDeviceSynchronize();
+        }
+
+.. _libcudacxx-extended-api-execution-model-stream-ordering:
+
+Stream and event ordering
+-------------------------
+
+A device-thread shall not make progress if it is dependent on termination of one or more unterminated device-threads or tasks via CUDA streams and/or events.
+
+[Note: This excludes dependencies such as Programmatic Dependent Launch or Launch Completion which do not encompass termination of the dependency. - end note.]
+
+[Note: Tasks are also known as `Commands <https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#streams>`__. - end note. ]
+
+.. dropdown:: Examples of CUDA API forward progress guarantees due to Stream and event ordering
+
+    .. code:: cuda
+        // Example: Exeuction.Model.Stream.0
+        // Allowed outcome: eventually, no thread makes progress.
+        // Rationale: while CUDA guarantees that one device thread makes progress, since there
+        // is no dependency between `first` and `second`, it does not guarantee which thread,
+        // and therefore it could always pick the device thread from `second`, which then never 
+        // unblocks from the spin-loop.
+        // That is, `second` may starve `first`.
+        cuda::atomic<int, cuda::thread_scope_system> flag = 0;
+        __global__ void first() { flag.store(1, rlx); }
+        __global__ void second() { while(flag.load(rlx) == 0) {} }
+        int main() {
+            cudaHostRegister(&flag, sizeof(flag));
+            cudaStream_t s0, s1;
+            cudaStreamCreate(&s0); 
+            cudaStreamCreate(&s1);
+            first<<<1,1,0,s0>>>();
+            second<<<1,1,0,s1>>>();
+            return cudaDeviceSynchronize();
+        }
+
+    .. code:: cuda
+        // Example: Exeuction.Model.Stream.1
+        // Outcome: terminates.
+        // Rationale: same as Execution.Model.Stream.0, but this example has a stream dependency
+        // between first and second, which requires CUDA to run the grids in order.
+        cuda::atomic<int, cuda::thread_scope_system> flag = 0;
+        __global__ void first() { flag.store(1, rlx); }
+        __global__ void second() { while(flag.load(rlx) == 0) {} }
+        int main() {
+            cudaHostRegister(&flag, sizeof(flag));
+            cudaStream_t s0;
+            cudaStreamCreate(&s0); 
+            first<<<1,1,0,s0>>>();
+            second<<<1,1,0,s0>>>();
+            return cudaDeviceSynchronize();
+        }