Performance Prediction for Large-Scale Heterogeneous Platforms

Ryota Yasudo, Ana L. Varbanescu, Jose G.F. Coutinho, Wayne Luk, Hideharu Amano

研究成果: Conference contribution

抄録

This paper presents an approach for analysing, modelling and predicting application performance of large-scale heterogeneous platforms. Our approach combines analytical and statistical modelling techniques, and aims to: (1) identify and characterise code regions that are the most promising candidates to benefit from acceleration; (2) provide statistical models that predict application behaviour for unobserved inputs; and (3) predict performance gain with different system architectures.

本文言語English
ホスト出版物のタイトルProceedings - 26th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2018
出版社Institute of Electrical and Electronics Engineers Inc.
ページ220
ページ数1
ISBN(電子版)9781538655221
DOI
出版ステータスPublished - 2018 9月 7
イベント26th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2018 - Boulder, United States
継続期間: 2018 4月 292018 5月 1

出版物シリーズ

名前Proceedings - 26th IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2018

Other

Other26th Annual IEEE International Symposium on Field-Programmable Custom Computing Machines, FCCM 2018
国/地域United States
CityBoulder
Period18/4/2918/5/1

ASJC Scopus subject areas

  • 人工知能
  • ハードウェアとアーキテクチャ
  • ソフトウェア

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