Comparative analysis of coprocessors. (4th September 2018)

• Record Type: Journal Article
• Authors: Sakdhnagool, Putt; Sabne, Amit; Eigenmann, Rudolf
• Is Part Of: Concurrency and computation. Volume 31:Number 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-09-04
• Subjects: accelerator -- GPU -- performance -- productivity -- Xeon Phi; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4756
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: While GPUs have seen a steady increase in usage, Xeon Phis have struggled in proving their value, and eventually got discontinued. Is this a matter of the Intel many‐core architecture's younger age or are there reasons due to specific features? This paper reviews quantitative information addressing these questions. Using two latest coprocessors, we evaluate performance and programming productivity across a range of microbenchmarks and applications. We consider productivity as the percentage of hand‐optimized performance reached by a simple high‐level parallel programming model that is translated onto the specific architectures by advanced compilers. We evaluate and compare the performance of the two coprocessors and point out where Xeon Phis fall short. We also briefly review the performance of different execution modes of Xeon Phis. Moreover, unlike common expectation, we found that Xeon Phis' productivity is marginally better that GPUs. The current results suggest that the performance advantage of GPUs outweighs the productivity benefit of Xeon Phis. Closing the performance gap and increasing the productivity benefit that a more regular many‐core paradigm can offer will be essential in designing a next‐generation architecture.