The CMSSW benchmarking suite: using HEP code to measure CPU performance

被引:2
|
作者
Benelli, G. [1 ]
机构
[1] CERN, PH Dept, CH-1211 Geneva 23, Switzerland
关键词
D O I
10.1088/1742-6596/219/5/052016
中图分类号
O57 [原子核物理学、高能物理学];
学科分类号
070202 ;
摘要
The demanding computing needs of the CMS experiment require thoughtful planning and management of its computing infrastructure. A key factor in this process is the use of realistic benchmarks when assessing the computing power of the different architectures available. In recent years a discrepancy has been observed between the CPU performance estimates given by the reference benchmark for HEP computing (SPECint [1]) and actual performances of HEP code. Making use of the CPU performance tools from the CMSSW performance suite, comparative CPU performance studies have been carried out on several architectures. A benchmarking suite has been developed and integrated in the CMSSW framework, to allow computing centers and interested third parties to benchmark architectures directly with CMSSW. The CMSSW benchmarking suite can be used out of the box, to test and compare several machines in terms of CPU performance and report with the wanted level of detail the different benchmarking scores (e.g. by processing step) and results. In this talk we describe briefly the CMSSW software performance suite, and in detail the CMSSW benchmarking suite client/server design, the performance data analysis and the available CMSSW benchmark scores. The experience in the use of HEP code for benchmarking will be discussed and CMSSW benchmark results presented.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] HEP Benchmark Suite The centralized future of WLCG benchmarking
    Borge, Gonzalo Menendez
    26TH INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS, CHEP 2023, 2024, 295
  • [2] Suite Specks and Suite Spots: A Methodology for the Automatic Conversion of Benchmarking Programs into Intrinsically Checkpointed Assembly Code
    Ringenberg, Jeff
    Mudge, Trevor
    ISPASS 2009: IEEE INTERNATIONAL SYMPOSIUM ON PERFORMANCE ANALYSIS OF SYSTEMS AND SOFTWARE, 2009, : 227 - 237
  • [3] NPBench: A Benchmarking Suite for High-Performance NumPy
    Ziogas, Alexandros Nikolaos
    Ben-Nun, Tal
    Schneider, Timo
    Hoefler, Torsten
    PROCEEDINGS OF THE 2021 ACM INTERNATIONAL CONFERENCE ON SUPERCOMPUTING, ICS 2021, 2021, : 63 - 74
  • [4] Cross-Architecture Performance Prediction (XAPP) Using CPU Code to Predict GPU Performance
    Ardalani, Newsha
    Lestourgeon, Clint
    Sankaralingam, Karthikeyan
    Zhu, Xiaojin
    PROCEEDINGS OF THE 48TH ANNUAL IEEE/ACM INTERNATIONAL SYMPOSIUM ON MICROARCHITECTURE (MICRO-48), 2015, : 725 - 737
  • [5] Benchmarking with Supernovae: A Performance Study of the FLASH Code
    Martin, Joshua
    Feldman, Catherine
    Siegmann, Eva
    Curtis, Tony
    Carlson, David
    Coskun, Firat
    Wood, Daniel
    Gonzalez, Raul
    Harrison, Robert J.
    Calder, Alan C.
    PRACTICE AND EXPERIENCE IN ADVANCED RESEARCH COMPUTING 2024, PEARC 2024, 2024,
  • [6] Kubernetes application performance benchmarking on heterogeneous CPU architecture: An experimental review
    Noor, Jannatun
    Faysal, Badsha
    Amin, Sheikh
    Tabassum, Bushra
    Khan, Tamim Raiyan
    Rahman, Tanvir
    HIGH-CONFIDENCE COMPUTING, 2025, 5 (01):
  • [7] Benchmarking of High Performance Computing Clusters with Heterogeneous CPU/GPU Architecture
    Sukharev, Pavel V.
    Vasilyev, Nikolay P.
    Rovnyagin, Mikhail M.
    Durnov, Maxim A.
    PROCEEDINGS OF THE 2017 IEEE RUSSIA SECTION YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING CONFERENCE (2017 ELCONRUS), 2017, : 574 - 577
  • [8] Using HEP experiment workflows for the benchmarking and accounting of WLCG computing resources
    Valassi, Andrea
    Alef, Manfred
    Barbet, Jean-Michel
    Datskova, Olga
    De Maria, Riccardo
    Medeiros, Miguel Fontes
    Giordano, Domenico
    Grigoras, Costin
    Hollowell, Christopher
    Javurkova, Martina
    Khristenko, Viktor
    Lange, David
    Michelotto, Michele
    Rinaldi, Lorenzo
    Sciaba, Andrea
    Van Der Laan, Cas
    24TH INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS (CHEP 2019), 2020, 245
  • [9] BENCHMARKING FOR NONPROFITS: HOW TO MEASURE, MANAGE, AND IMPROVE PERFORMANCE
    Young, Elizabeth
    JOURNAL OF NONPROFIT & PUBLIC SECTOR MARKETING, 2008, 19 (01) : 119 - 120
  • [10] Benchmarking for Nonprofits: How to Measure, Manage, and Improve Performance
    Burkhart-Kriesel, Cheryl
    COMMUNITY DEVELOPMENT, 2006, 37 (01) : 91 - 92