Making the Most of SMT in HPC

Author:

Porter Leo1,Laurenzano Michael A.2,Tiwari Ananta3,Jundt Adam4,Ward, Jr. William A.5,Campbell Roy5,Carrington Laura3

Affiliation:

1. EP Analytics and the University of California, San Diego

2. EP Analytics and the University of Michigan, Ann Arbor

3. EP Analytics and the San Diego Supercomputer Center

4. EP Analytics

5. Department of Defense HPC Modernization Program

Abstract

This work presents an end-to-end methodology for quantifying the performance and power benefits of simultaneous multithreading (SMT) for HPC centers and applies this methodology to a production system and workload. Ultimately, SMT’s value system-wide depends on whether users effectively employ SMT at the application level. However, predicting SMT’s benefit for HPC applications is challenging; by doubling the number of threads, the application’s characteristics may change. This work proposes statistical modeling techniques to predict the speedup SMT confers to HPC applications. This approach, accurate to within 8%, uses only lightweight, transparent performance monitors collected during a single run of the application.

Funder

Air Force Office of Scientific Research under AFOSR Award No. FA9550-12-1-0476

DoD High Performance Computing Modernization Program at the AFRL, ARL and ERDC DoD Supercomputing Resource Centers

HPCMP's PETTT program (Contract No: GS04T09DBC0017 though DRC)

Publisher

Association for Computing Machinery (ACM)

Subject

Hardware and Architecture,Information Systems,Software

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. vkpolybench: A crossplatform Vulkan Compute port of the PolyBench/GPU benchmark suite;SoftwareX;2021-07

2. Efficient detection of silent data corruption in HPC applications with synchronization-free message verification;The Journal of Supercomputing;2021-06-09

3. On the Detection of Silent Data Corruptions in HPC Applications Using Redundant Multi-threading;Euro-Par 2020: Parallel Processing Workshops;2021

4. SMT-Aware Instantaneous Footprint Optimization;Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing;2016-05-31

5. Compute bottlenecks on the new 64-bit ARM;Proceedings of the 3rd International Workshop on Energy Efficient Supercomputing - E2SC '15;2015

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