"Julia support for native CUDA programming.
GPUs and other accelerators are popular devices for accelerating
compute-intensive, parallelizable applications. However, programming
these devices is a difficult task. Writing efficient device code is
challenging, and is typically done in a low-level programming language.
High-level languages are rarely supported, or do not integrate with the
rest of the high-level language ecosystem. To overcome this, we propose
compiler infrastructure to efficiently add support for new hardware or
environments to an existing programming language. We evaluate our
approach by adding support for NVIDIA GPUs to the Julia programming
language. By integrating with the existing compiler, we significantly
lower the cost to implement and maintain the new compiler, and
facilitate reuse of existing application code. Moreover, use of the
high-level Julia programming language enables new and dynamic approaches
for GPU programming. This greatly improves programmer productivity,
while maintaining application performance similar to that of the
official NVIDIA CUDA toolkit.
https://github.com/JuliaGPU/CUDAnative.jl
https://hgpu.org/?p=17878
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