PHAST Library — Enabling Single-Source and High Performance Code for GPUs and Multi-cores
PHAST Library — Enabling Single-Source and High Performance Code for GPUs and Multi-cores
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PHAST 库 — 为 GPU 和多核启用单源高性能代码
DOI：
10.1109/hpcs.2017.109
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
S. Bartolini
中科院分区：
文献类型：
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作者：
Biagio Peccerillo;S. Bartolini
并行异构体系结构（如多核和GPU）的模拟在编程语言/框架领域提出了新的挑战。模拟器的应用程序需要以一种可以轻松适应特定架构的方式表达，有效地调整每个架构，同时防止由于不统一的手工优化而引入偏差。最常见的异构编程框架太低级，因此我们提出PHAST，一个面向多核和Nvidia GPU的高级异构C++库。它允许在高抽象级别上编写代码，以达到良好的性能，同时允许精细的参数调优，而不是屏蔽代码进行低级优化。我们在两种支持的架构上评估了DCT 8x8的PHAST。在多核上，我们发现PHAST实现比OpenCL（AMD供应商）实现快10倍左右，但比OpenCL（英特尔供应商）慢4倍左右，后者有效地利用了自动向量化。在Nvidia GPU上，PHAST代码的性能比CUDA SDK参考版本高出55.14%。
The simulation of parallel heterogeneous architectures such as multi-cores and GPUs sets new challenges in the programming language/framework domain. Applications for simulators need to be expressed in a way that can be easily adapted for the specific architectures, effectively tuned for on each of them while preventing from introducing biases due to non-uniform hand-made optimizations. The most common heterogeneous programming frameworks are too low-level, so we propose PHAST, a high-level heterogeneous C++ library targetable on multi-cores and Nvidia GPUs. It permits to write code at a high level of abstraction, to reach good performance while allowing for fine parameter tuning and not shielding code from low-level optimizations. We evaluate PHAST in the case of DCT8x8 on both supported architectures. On multi-cores, we found that PHAST implementation is around ten times faster than OpenCL (AMD vendor) implementation, but up to about 4x slower than OpenCL (Intel vendor) one, which effectively leverages auto-vectorization. On Nvidia GPUs, PHAST code performs up to 55.14% better than CUDA SDK reference version.