Name
Abstract | ||
|---|---|---|
Exploiting heterogeneous parallel hardware currently requires mapping application code to multiple disparate programming models. Unfortunately, general-purpose programming models available today can yield high performance but are too low-level to be accessible to the average programmer. We propose leveraging domain-specific languages (DSLs) to map high-level application code to heterogeneous devices. To demonstrate the potential of this approach we present OptiML, a DSL for machine learning. OptiML programs are implicitly parallel and can achieve high performance on heterogeneous hardware with no modification required to the source code. For such a DSL-based approach to be tractable at large scales, better tools are required for DSL authors to simplify language creation and parallelization. To address this concern, we introduce Delite, a system designed specifically for DSLs that is both a framework for creating an implicitly parallel DSL as well as a dynamic runtime providing automated targeting to heterogeneous parallel hardware. We show that OptiML running on Delite achieves single-threaded, parallel, and GPU performance superior to explicitly parallelized MATLAB code in nearly all cases. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/1941553.1941561 | PPOPP |
Keywords | Field | DocType |
domain-specific approach,parallel dsl,heterogeneous parallel hardware,application code,high-level application code,heterogeneous parallelism,source code,matlab code,heterogeneous hardware,high performance,dsl author,heterogeneous device,parallel programming,domain specific language,programming model,machine learning,system design,domain specific languages | Programming language,Computer science,CUDA,Source code,Digital subscriber line,Theoretical computer science,Distributed computing,Domain-specific language,Programming paradigm,Parallel computing,Code generation,Compiler,High-level programming language | Conference |
Volume | Issue | ISSN |
46 | 8 | 0362-1340 |
Citations | PageRank | References |
73 | 3.47 | 21 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hassan Chafi | 1 | 1118 | 61.11 |
| Arvind K. Sujeeth | 2 | 502 | 20.58 |
| Kevin J. Brown | 3 | 448 | 18.62 |
| HyoukJoong Lee | 4 | 414 | 17.71 |
| Anand R. Atreya | 5 | 139 | 6.54 |
| Kunle Olukotun | 6 | 4532 | 373.50 |