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arXiv 0910.0262hep-lat
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MILC格点量子色动力学应用的单元处理器实现

Cell processor implementation of a MILC lattice QCD application

Guochun Shi, Volodymyr Kindratenko, Steven Gottlieb

摘要:

我们目前的结果的实施一个MILC格点量子色动力学应用模拟与动态三叶草费米子使用混合分子动力学R算法的细胞宽带引擎处理器。负责98.8%的整体执行时间的54个计算内核被移植到细胞的协同处理元件(SPE)。剩下的应用程序框架,包括基于MPI的分布式代码执行,留给了Cell的PowerPC处理器。我们观察到,我们很少使用任何内核实现超过10 GFLOPS,这只是Cell峰值性能的4%多一点。与此同时,许多内核都保持着接近20 GB/s的带宽,这是Cell峰值的78%。这表明应用程序性能受到主存和SPE之间带宽的限制。尽管有此限制,但在将3.2 GHz Cell处理器与2.33 GHz Intel Xeon处理器的单核进行比较时,实现了8.7倍(对于8x8 x16 x16点阵)和9.6倍(对于16 x16 x16点阵)的加速比。当比较在双单元刀片和四核双芯片英特尔至强刀片上执行的代码时,加速比为1.5倍(8x8 x16 x16点阵)和4.1倍(16 x16 x16点阵)。

英文摘要:

We present results of the implementation of one MILC lattice QCD application-simulation with dynamical clover fermions using the hybrid-molecular dynamics R algorithm-on the Cell Broadband Engine processor. Fifty-four individual computational kernels responsible for 98.8% of the overall execution time were ported to the Cell's Synergistic Processing Elements (SPEs). The remaining application framework, including MPI-based distributed code execution, was left to the Cell's PowerPC processor. We observe that we only infrequently achieve more than 10 GFLOPS with any of the kernels, which is just over 4% of the Cell's peak performance. At the same time, many of the kernels are sustaining a bandwidth close to 20 GB/s, which is 78% of the Cell's peak. This indicates that the application performance is limited by the bandwidth between the main memory and the SPEs. In spite of this limitation, speedups of 8.7x (for 8x8x16x16 lattice) and 9.6x (for 16x16x16x16 lattice) were achieved when comparing a 3.2 GHz Cell processor to a single core of a 2.33 GHz Intel Xeon processor. When comparing the code scaled up to execute on a dual-Cell blade and a quad-core dual-chip Intel Xeon blade, the speedups are 1.5x (8x8x16x16 lattice) and 4.1x (16x16x16x16 lattice).

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