An idiom-finding tool for increasing productivity of accelerators
An idiom-finding tool for increasing productivity of accelerators
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DOI：
10.1145/1995896.1995928
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发表时间：
2011-05
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影响因子：
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通讯作者：
L. Carrington;M. Tikir;C. Olschanowsky;M. Laurenzano;Joshua Peraza;A. Snavely;S. Poole
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文献类型：
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作者：
L. Carrington;M. Tikir;C. Olschanowsky;M. Laurenzano;Joshua Peraza;A. Snavely;S. Poole
假设有人正在考虑购买一台装有加速器的电脑。或者假设有人可以访问这样一台计算机，并且正在考虑移植代码以利用加速器。是否有理由认为购买成本或程序员的努力是值得的？如果能够在支付金钱或时间之前估计预期的改进，那就太好了。我们展示了一个分析框架和工具集来提供这样的估计：这些工具首先寻找用户定义的习惯用法，这些习惯用法是提前确定的计算和数据访问模式，可能会从加速器硬件中受益。然后应用一个性能模型来估计如果将这些习惯用法移植并在加速器上运行会有多快，并就每个习惯用法是否值得将它们移植到加速器上提出建议，并估计如果这样做了，应用程序的总体加速将是多少。作为概念验证，我们将研究重点放在收集/分散（G/S）操作上，以及在运载HC-1上加速这些操作的方法，该运载HC-1具有加速G/S的特殊目的“个性”。我们在两个大规模HPC应用程序上测试了该方法。与让程序员从视觉上检查代码寻找习语相比，习语识别工具节省了程序员数周的精力；性能模型通过对移植的最佳候选进行排序而节省了更多时间；并且性能模型是准确的，预测移植导致的G/S运行时加速在实际实现的加速的10%以内。运载工具上的G/S硬件将这些操作的速度提高了20倍，对整个应用程序运行时的总体影响是将其提高了21%。
Suppose one is considering purchase of a computer equipped with accelerators. Or suppose one has access to such a computer and is considering porting code to take advantage of the accelerators. Is there a reason to suppose the purchase cost or programmer effort will be worth it? It would be nice to able to estimate the expected improvements in advance of paying money or time. We exhibit an analytical framework and tool-set for providing such estimates: the tools first look for user-defined idioms that are patterns of computation and data access identified in advance as possibly being able to benefit from accelerator hardware. A performance model is then applied to estimate how much faster these idioms would be if they were ported and run on the accelerators, and a recommendation is made as to whether or not each idiom is worth the porting effort to put them on the accelerator and an estimate is provided of what the overall application speedup would be if this were done. As a proof-of-concept we focus our investigations on Gather/Scatter (G/S) operations and means to accelerate these available on the Convey HC-1 which has a special-purpose "personality" for accelerating G/S. We test the methodology on two large-scale HPC applications. The idiom recognizer tool saves weeks of programmer effort compared to having the programmer examine the code visually looking for idioms; performance models save yet more time by rank-ordering the best candidates for porting; and the performance models are accurate, predicting G/S runtime speedup resulting from porting to within 10% of speedup actually achieved. The G/S hardware on the Convey sped up these operations 20x, and the overall impact on total application runtime was to improve it by as much as 21%.