2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS)最新文献_第2页

Frontier vs the Exascale Report: Why so long? and Are We Really There Yet? 前沿与百亿亿次报告:为什么这么长时间?和我们真的到了吗?

2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS) Pub Date : 2022-11-01 DOI: 10.1109/PMBS56514.2022.00008

P. Kogge, W. Dally

引用次数: 2

An Initial Evaluation of Arm’s Scalable Matrix Extension Arm可伸缩矩阵扩展的初步评价

2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS) Pub Date : 2022-11-01 DOI: 10.1109/PMBS56514.2022.00018

Finn Wilkinson, Simon McIntosh-Smith

引用次数: 0

AppEKG: A Simple Unifying View of HPC Applications in Production AppEKG:生产环境中HPC应用的简单统一视图

2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS) Pub Date : 2022-11-01 DOI: 10.1109/PMBS56514.2022.00017

M. Al-Tahat, Strahinja Trecakov, J. Cook

引用次数: 0

WfBench: Automated Generation of Scientific Workflow Benchmarks WfBench:自动生成科学工作流基准

2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS) Pub Date : 2022-10-06 DOI: 10.1109/PMBS56514.2022.00014

T. Coleman, H. Casanova, K. Maheshwari, L. Pottier, Sean R. Wilkinson, J. Wozniak, F. Suter, M. Shankar, Rafael Ferreira da Silva

{"title":"WfBench: Automated Generation of Scientific Workflow Benchmarks","authors":"T. Coleman, H. Casanova, K. Maheshwari, L. Pottier, Sean R. Wilkinson, J. Wozniak, F. Suter, M. Shankar, Rafael Ferreira da Silva","doi":"10.1109/PMBS56514.2022.00014","DOIUrl":"https://doi.org/10.1109/PMBS56514.2022.00014","url":null,"abstract":"The prevalence of scientific workflows with high computational demands calls for their execution on various distributed computing platforms, including large-scale leadership-class high-performance computing (HPC) clusters. To handle the deployment, monitoring, and optimization of workflow executions, many workflow systems have been developed over the past decade. There is a need for workflow benchmarks that can be used to evaluate the performance of workflow systems on current and future software stacks and hardware platforms.We present a generator of realistic workflow benchmark specifications that can be translated into benchmark code to be executed with current workflow systems. Our approach generates workflow tasks with arbitrary performance characteristics (CPU, memory, and I/O usage) and with realistic task dependency structures based on those seen in production workflows. We present experimental results that show that our approach generates benchmarks that are representative of production workflows, and conduct a case study to demonstrate the use and usefulness of our generated benchmarks to evaluate the performance of workflow systems under different configuration scenarios.","PeriodicalId":321991,"journal":{"name":"2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS)","volume":"58 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113943206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8