K. Rocki, D. V. Essendelft, I. Sharapov, R. Schreiber, Michael Morrison, V. Kibardin, Andrey Portnoy, J. Dietiker, M. Syamlal, Michael James
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引用次数: 45
摘要
对于PDE代码,基于cpu和gpu的系统的性能通常很低,因为PDE代码必须求解大型、稀疏且通常是结构化的线性方程系统。迭代求解器受到数据移动的限制,无论是在缓存和内存之间,还是在节点之间。在这里,我们描述了在Cerebras systems CS-1上求解此类方程组的方法,CS-1是一种具有良好内存带宽和通信延迟的晶圆级处理器。我们在单晶圆级系统上实现了0.86 PFLOPS,通过BiCGStab解决了一个线性系统,该系统由7点有限差分模板在600\ \ 595\ \ 1536$网格上产生,实现了大约三分之一的机器峰值性能。我们解释了系统,它的架构和编程,以及它在这个问题和相关问题上的性能。我们讨论了内存容量和浮点精度的问题。我们概述了将这项工作扩展到全面应用的计划。
Fast Stencil-Code Computation on a Wafer-Scale Processor
The performance of CPU-based and GPU-based systems is often low for PDE codes, where large, sparse, and often structured systems of linear equations must be solved. Iterative solvers are limited by data movement, both between caches and memory and between nodes. Here we describe the solution of such systems of equations on the Cerebras Systems CS-1, a wafer-scale processor that has the memory bandwidth and communication latency to perform well. We achieve 0.86 PFLOPS on a single wafer-scale system for the solution by BiCGStab of a linear system arising from a 7-point finite difference stencil on a $600\times 595\times 1536$ mesh, achieving about one third of the machine’s peak performance. We explain the system, its architecture and programming, and its performance on this problem and related problems. We discuss issues of memory capacity and floating point precision. We outline plans to extend this work towards full applications.