The simulation is an important means of performance evaluation of the computer architecture. Nowadays,
the serial simulation of general purpose graphics processing unit (GPGPU) architecture is the main bottleneck
for the simulation speed. To address this issue, we propose the intra-kernel parallelization on a multicore
processor and the inter-kernel parallelization on a multiple-machine platform. We apply these two methods to
the GPGPU-sim simulator. The intra-kernel parallelization method firstly parallelizes the serial simulation of
multiple compute units in one cycle. Then it parallelizes the timing and functional simulation to reduce the
performance loss caused by the synchronization between different compute units. The inter-kernel parallelization
method divides multiple kernels of a CUDA program into several groups and distributes these groups across multiple
simulation hosts to perform the simulation. Experimental results show that the intra-kernel parallelization
method achieves a speed-up of up to 12 with a maximum error rate of 0.009 4% on a 32-core machine, and the
inter-kernel parallelization method can accelerate the simulation by a factor of up to 3.9 with a maximum error
rate of 0.11% on four simulation hosts. The orthogonality between these two methods allows us to combine them
together on multiple multi-core hosts to get further performance improvements.
ZHAO Xia* (赵 夏), MA Sheng (马 胜), CHEN Wei (陈 微), WANG Zhiying (王志英)
. Exploiting Parallelism in the Simulation of General Purpose Graphics Processing Unit Program[J]. Journal of Shanghai Jiaotong University(Science), 2016
, 21(3)
: 280
-288
.
DOI: 10.1007/s12204-016-1723-2
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