Lost in heterogeneity: Architectural selection based on code features
Document Type
Conference Proceeding
Publication Date
11-15-2015
Abstract
Automatic parallelizing compilers have evolved greatly over the last decade. Tools like Pluto, Pr4All and PPCG are widely adopted to generate optimized OpenMP, CUDA and OpenCL codes. However, in the end, it is the programmer's responsibility to select the best target architecture for a particular application. In this work we provide a solution for the problem of architectural selection. We introduce a low cost model based on a classiffication problem which selects the fastest architecture for the generated code. We integrate our model in PPCG, a state of the art polyhedral compiler. Our experiments show that our model selects the fastest architecture 87% of the time when choosing between an Ivy Bridge Xeon CPU and a Kepler GPU and 81% of the time when choosing between a Xeon Sandy Bridge CPU and a Xeon Phi acceleration card.
Publication Source (Journal or Book title)
Proceedings of Co-HPC 2015: 2nd International Workshop on Hardware-Software Co-Design for High Performance Computing - Held in conjunction with SC 2015: The International Conference for High Performance Computing, Networking, Storage and Analysis
Recommended Citation
AbuAsal, S., Tohid, R., & Ramanujam, J. (2015). Lost in heterogeneity: Architectural selection based on code features. Proceedings of Co-HPC 2015: 2nd International Workshop on Hardware-Software Co-Design for High Performance Computing - Held in conjunction with SC 2015: The International Conference for High Performance Computing, Networking, Storage and Analysis https://doi.org/10.1145/2834899.2834904