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Full-System Simulation of Mobile CPU/GPU Platforms

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https://ieeexplore.ieee.org/document/8695656
Original languageEnglish
Title of host publicationProceedings of the International Symposium on Performance Analysis of Systems and Software 2019 (ISPASS 2019)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages68-78
Number of pages11
ISBN (Electronic)978-1-7281-0746-2
ISBN (Print)978-1-7281-0747-9
DOIs
Publication statusPublished - 25 Apr 2019
EventInternational Symposium on Performance Analysis of Systems and Software 2019 - Madison, United States
Duration: 24 Mar 201926 Mar 2019
https://www.ispass.org/ispass2019/

Conference

ConferenceInternational Symposium on Performance Analysis of Systems and Software 2019
Abbreviated titleISPASS-2019
CountryUnited States
CityMadison
Period24/03/1926/03/19
Internet address

Abstract

Graphics Processing Units (GPUs) critically rely on a complex system software stack comprising kernel- and userspace drivers and Just-in-time (JIT) compilers. Yet, existing GPU simulators typically abstract away details of the software stack and GPU instruction set. Partly, this is because GPU vendors rarely release sufficient information about their latest GPU products. However, this is also due to the lack of an integrated CPU/GPU simulation framework, which is complete and powerful enough to drive the complex GPU software environment. This has led to a situation where research on GPU architectures and compilers is largely based on outdated or greatly simplified architectures and software stacks, undermining the validity of the generated results. In this paper we develop a full-system system simulation environment for a mobile platform, which enables users to run a complete and unmodified software stack for a state-of-the-art mobile Arm CPU and Mali-G71 GPU powered device. We validate our simulator against a hardware implementation and Arm’s stand-alone GPU simulator, achieving 100% architectural accuracy across all available toolchains. We demonstrate the capability of our GPU simulation framework by optimizing an advanced Computer Vision application using simulated statistics unavailable with other simulation approaches or physical GPU implementations. We demonstrate that performance optimizations for desktop GPUs trigger bottlenecks on mobile GPUs, and show the importance of efficient memory use.

Event

International Symposium on Performance Analysis of Systems and Software 2019

24/03/1926/03/19

Madison, United States

Event: Conference

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