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Facilitating the development of stencil applications using the Heterogeneous Programming Library

机译:使用异构编程库促进模板应用程序的开发

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Stencil computations are very common in scientific codes. Heterogeneous systems achieve good results solving these problems, but their programming is complex because of the ghost regions required in multi-device implementations and the difficulty to properly exploit their hardware. The Heterogeneous Programming Library (HPL) is a recent framework that improves the pro-grammability of heterogeneous devices. This paper describes two extensions of HPL focused on stencil computations. The first one allows to automatically update the ghost regions they involve. The second one automates the implementation of the computational kernels of these algorithms. In our evaluation, the first mechanism reduces on average the number of lines of code and the Halstead programming effort of the host code of comparable HPL baselines by 34% and 64.2%, respectively, while the second contribution reduces these metrics by 72% and 79% in the computational kernels, respectively. Also, the first technique has negligible performance overheads, while the second one matches the performance of manually developed kernels. As an added benefit, the facilitation of the development of these codes thanks to these techniques helps programmers experiment with optimizations suited for this applications such as the ghost cell expansion technique, which provides speedups of up to 13% in our experiments.
机译:模板计算在科学规范中非常普遍。异构系统可以很好地解决这些问题,但是由于多设备实现中需要重影区域以及难以正确利用其硬件,因此其编程非常复杂。异构编程库(HPL)是一个最新的框架,可提高异构设备的可编程性。本文介绍了专注于模板计算的HPL的两个扩展。第一个允许自动更新它们涉及的重影区域。第二个自动化这些算法的计算内核的实现。在我们的评估中,第一种机制平均将可比较的HPL基线的代码行数和主机代码的Halstead编程工作量分别减少了34%和64.2%,而第二种机制将这些指标减少了72%和79 %分别在计算内核中。同样,第一种技术的性能开销可以忽略不计,而第二种技术与手动开发的内核的性能相匹配。另外一个好处是,由于这些技术而促进了这些代码的开发,从而帮助程序员进行了适合该应用的优化实验,例如鬼单元扩展技术,该技术在我们的实验中提供了高达13%的加速。

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