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Directive-based General-purpose GPU ProgrammingHan, Tian Yi David 19 January 2010 (has links)
Graphics Processing Units (GPUs) have become a competitive accelerator for
non-graphics applications, mainly driven by the improvements in GPU programmability. Although the Compute Unified Device Architecture (CUDA) is a simple C-like interface for programming NVIDIA GPUs, porting applications to CUDA remains a challenge to average programmers. In particular, CUDA places on the programmer the burden of packaging GPU code in separate functions, of explicitly managing data transfer between the host and GPU memories, and of manually optimizing the utilization of the GPU memory. We have designed hiCUDA, a high-level directive-based language for CUDA programming. It allows programmers to perform these tedious tasks in a simpler manner, and directly to the sequential code. We have also prototyped a compiler that translates a hiCUDA program to a CUDA program and can handle real-world applications.
Experiments using seven standard CUDA benchmarks show that the simplicity hiCUDA provides comes at no expense to performance.
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Directive-based General-purpose GPU ProgrammingHan, Tian Yi David 19 January 2010 (has links)
Graphics Processing Units (GPUs) have become a competitive accelerator for
non-graphics applications, mainly driven by the improvements in GPU programmability. Although the Compute Unified Device Architecture (CUDA) is a simple C-like interface for programming NVIDIA GPUs, porting applications to CUDA remains a challenge to average programmers. In particular, CUDA places on the programmer the burden of packaging GPU code in separate functions, of explicitly managing data transfer between the host and GPU memories, and of manually optimizing the utilization of the GPU memory. We have designed hiCUDA, a high-level directive-based language for CUDA programming. It allows programmers to perform these tedious tasks in a simpler manner, and directly to the sequential code. We have also prototyped a compiler that translates a hiCUDA program to a CUDA program and can handle real-world applications.
Experiments using seven standard CUDA benchmarks show that the simplicity hiCUDA provides comes at no expense to performance.
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