High Level Programming for Heterogeneous Architectures

Oren Segal; Martin Margala; Sai Rahul Chalamalasetti; Mitch Wright

High Level Programming for Heterogeneous Architectures

Performance 2014-08-22 v1 Programming Languages

Authors: Oren Segal , Martin Margala , Sai Rahul Chalamalasetti , Mitch Wright

Abstract

This work presents an effort to bridge the gap between abstract high level programming and OpenCL by extending an existing high level Java programming framework (APARAPI), based on OpenCL, so that it can be used to program FPGAs at a high level of abstraction and increased ease of programmability. We run several real world algorithms to assess the performance of the framework on both a low end and a high end system. On the low end and high end systems respectively we observed up to 78-80 percent power reduction and 4.8X-5.3X speed increase running NBody simulation, as well as up to 65-80 percent power reduction and 6.2X-7X speed increase for a KMeans, MapReduce algorithm running on top of the Hadoop framework and APARAPI.

Keywords

distributed systems computer architecture parallel programming

Cite

@article{arxiv.1408.4964,
  title  = {High Level Programming for Heterogeneous Architectures},
  author = {Oren Segal and Martin Margala and Sai Rahul Chalamalasetti and Mitch Wright},
  journal= {arXiv preprint arXiv:1408.4964},
  year   = {2014}
}

Comments

Presented at First International Workshop on FPGAs for Software Programmers (FSP 2014) (arXiv:1408.4423)

High Level Programming for Heterogeneous Architectures

Abstract

Keywords

Cite

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