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-+ Rust GPU makes it possible to write and run GPU software in Rust, + leveraging the language's powerful safety and concurrency features to + enhance performance and reliability. With Rust GPU, you can seamlessly + develop for both CPU and GPU using a unified codebase, all while + benefiting from Rustβs existing ecosystem. +
++ The Rust GPU compiler backend emits code compatible with{" "} + Vulkan, ensuring your code runs + across a{" "} + + wide range of devices and vendors + + . +
++ If instead you wish to stick to the NVIDIA-only ecosystem, stay + tuned as the{" "} + Rust CUDA{" "} + project is in the process of being rebooted and possibly integrated + with Rust GPU. +
+
+ There is no longer a need to learn a GPU-specific programming
+ language. You can write both CPU and GPU code in Rust, leveraging
+ your existing Rust knowledge and maintaining a consistent
+ development experience. Furthermore, the{" "}
+ same code can run on both the CPU and GPU, with divergent
+ behavior gated behind cfg
attributes and macros where
+ necessary.
+
+ Even if your current codebase isn't written in Rust, choosing Rust + for the GPU parts gives you more widely applicable skills in one of + the{" "} + + fastest-growing languages on GitHub + + . Rust is also one of the{" "} + + most admired programming languages + {" "} + while GPU-specific languages are considered a necessary evil. +
++ Rust's ownership model and type system guarantee memory safety, + minimizing bugs and undefined behavior. Rust's borrow checker also + enables fearless concurrency, which is essential for maximizing + performance on massively parallel GPUs. +
++ Programming in GPU-specific languages can often feel like{" "} + + taking a step back to the 90s + + , where primitive tools and sharp edges abound. Because of this, + code written for GPUs is simplistic with low cyclomatic complexity. + Rust has an expressive type system and zero-cost abstractions that + enable writing high-level, reusable code without sacrificing + performance. This approach leads to more maintainable and + sophisticated GPU programs, streamlining the development process and + enhancing productivity. +
+
+ The state-of-the-art for sharing GPU code is copy and pasting. With
+ Rust GPU we are excited to bring the excellent cargo
{" "}
+ and crates.io ecosystem to GPU programming and provide some sanity.
+
+ Rust's no_std
ecosystem offers a wide array of
+ libraries that can be used in environments without the standard
+ library. Traditionally this has meant embedded devices, but a lot of
+ the same assumptions apply to GPUs! As a consequence, you can reuse{" "}
+
+ existing no_std
libraries from crates.io
+ {" "}
+ in your GPU code{" "}
+ without the authors explicitly adding GPU support. This is
+ uniquely enabled by Rust GPU's implementation choices and Rust's{" "}
+
+ registers
+
+ . Sharing and reusing code from the greater Rust ecosystem is a
+ superpower when writing GPU programs that will massively compound
+ over time.
+
{{ page.summary }}
-The future of GPU programming
- -