Transit: A visual analytical model for multithreaded machines

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

  • Ang Li - , Eindhoven University of Technology, National University of Singapore (Autor:in)
  • Y. C. Tay - , National University of Singapore (Autor:in)
  • Akash Kumar - , National University of Singapore (Autor:in)
  • Henk Corporaal - , Eindhoven University of Technology (Autor:in)

Abstract

With the extraordinary growth of cores and threads in to-day's multithreaded machines, analyzing and tuning the performance of such platforms becomes a challenging task. In this paper, we propose an intuitive and visualizable model for analyzing the performance of contemporary highly con-current multithreaded machines. Based on ow balancing between service demand and service supply of the memory system, the model draws an intuitive figure to characterize machine state, identify bottlenecks and determine optimization directions. The tractability of the model is highlighted as it only requires two parameters from the workload. Our model achieves 90% and 83% prediction accuracy for computation throughput on Fermi and Kepler GPUs over the 16 applications from Rodinia benchmark.

Details

OriginalspracheEnglisch
TitelHPDC 2015 - Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing
Herausgeber (Verlag)Association for Computing Machinery, Inc
Seiten101-106
Seitenumfang6
ISBN (elektronisch)9781450335508
PublikationsstatusVeröffentlicht - 15 Juni 2015
Peer-Review-StatusJa
Extern publiziertJa

Konferenz

Titel24th ACM Symposium on High-Performance Parallel and Distributed Computing, HPDC 2015
Dauer15 - 19 Juni 2015
StadtPortland
LandUSA/Vereinigte Staaten

Schlagworte

Forschungsprofillinien der TU Dresden

Schlagwörter

  • GPUs, Multithreaded machine, Performance modeling, Performance optimization