GPGPU

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Highly Optimized Code Generation for Stencil Codes with Computation Reuse for GPUs
《Journal of Computer Science & Technology》2016年第6期1262-1274,共13页Wen-Jing Ma Kan Gao Guo-Ping Long 
This work was supported by the National High Technology Research and Development 863 Program of China under Grant No. 2012AA010902, and the National Natural Science Foundation of China under Grant No. 61303059.
Computation reuse is known as an effective optimization technique. However, due to the complexity of modern GPU architectures, there is yet not enough understanding regarding the intriguing implications of the interpl...
关键词：GPGPU OPENCL STENCIL code generation computation reuse 
CUDA-NP： Realizing Nested Thread-Level Parallelism in GPGPU Applications被引量：3
《Journal of Computer Science & Technology》2015年第1期3-19,共17页杨毅 李超 周辉阳 
This work was supported by the National Science Foundation of USA under Grant No. CCF-1216569 and a CAREER award of National Science Foundation of USA under Grant No. CCF-0968667.
Parallel programs consist of series of code sections with different thread-level parallelism （TLP）. As a result, it is rather common that a thread in a parallel program, such as a GPU kernel in CUDA programs, still ...
关键词：GPGPU nested parallelism COMPILER local memory 
PartialRC: A Partial Recomputing Method for Efficient Fault Recovery on GPGPUs被引量：1
《Journal of Computer Science & Technology》2012年第2期240-255,共16页徐新海 杨学军 薛京灵 林宇斐 林一松 
supported by the National Natural Science Foundation of China under Grant Nos. 60921062, 61003087, 61120106005 and 61170049
GPGPUs are increasingly being used to as performance accelerators for HPC （High Performance Computing） applications in CPU/GPU heterogeneous computing systems, including TianHe-1A, the world＇s fastest supercomputer...
关键词：GPGPU partial recomputing fault tolerance CUDA CHECKPOINTING 
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