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UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

Authors :
Gu, Yongbin
Wu, Wenxuan
Li, Yunfan
Chen, Lizhong
Publication Year :
2020

Abstract

The recent introduction of Unified Virtual Memory (UVM) in GPUs offers a new programming model that allows GPUs and CPUs to share the same virtual memory space, which shifts the complex memory management from programmers to GPU driver/ hardware and enables kernel execution even when memory is oversubscribed. Meanwhile, UVM may also incur considerable performance overhead due to tracking and data migration along with special handling of page faults and page table walk. As UVM is attracting significant attention from the research community to develop innovative solutions to these problems, in this paper, we propose a comprehensive UVM benchmark suite named UVMBench to facilitate future research on this important topic. The proposed UVMBench consists of 32 representative benchmarks from a wide range of application domains. The suite also features unified programming implementation and diverse memory access patterns across benchmarks, thus allowing thorough evaluation and comparison with current state-of-the-art. A set of experiments have been conducted on real GPUs to verify and analyze the benchmark suite behaviors under various scenarios.<br />Comment: 10 pages

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2007.09822
Document Type :
Working Paper