Data Partitioning on Heterogeneous Multicore and Multi-GPU Systems Using Functional Performance Models of Data-Parallel Applications

Abstract

Transition to hybrid CPU/GPU platforms in high performance computing is challenging in the aspect of efficient utilisation of the heterogeneous hardware and existing optimised software. During recent years, scientific software has been ported to multicore and GPU architectures and now should be reused on hybrid platforms. In this paper, we model the… (More)
DOI: 10.1109/CLUSTER.2012.34

10 Figures and Tables

Topics

Statistics

01020201520162017
Citations per Year

Citation Velocity: 8

Averaging 8 citations per year over the last 3 years.

Learn more about how we calculate this metric in our FAQ.
  • Presentations referencing similar topics