Portable performance on asymmetric multicore processors

Date

2016

Authors

Jibaja, Ivan
Cao, Ting
Blackburn, Stephen
McKinley, Kathryn

Journal Title

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Volume Title

Publisher

Association for Computing Machinery

Abstract

Static and dynamic power constraints are steering chip manufacturers to build single-ISA Asymmetric Multicore Processors (AMPs) with big and small cores. To deliver on their energy efficiency potential, schedulers must consider core sensitivity, load balance, and the critical path. Applying these criteria effectively is challenging especially for complex and non-scalable multithreaded applications. We demonstrate that runtimes for managed languages, which are now ubiquitous, provide a unique opportunity to abstract over AMP complexity and inform scheduling with rich semantics such as thread priorities, locks, and parallelism— information not directly available to the hardware, OS, or application. We present the WASH AMP scheduler, which (1) automatically identifies and accelerates critical threads in concurrent, but non-scalable applications; (2) respects thread priorities; (3) considers core availability and thread sensitivity; and (4) proportionally schedules threads on big and small cores to optimize performance and energy. We introduce new dynamic analyses that identify critical threads and classify applications as sequential, scalable, or non-scalable. Compared to prior work, WASH improves performance by 20% and energy by 9% or more on frequency-scaled AMP hardware (not simulation). Performance advantages grow to 27% when asymmetry increases. Performance advantages are robust to a complex multithreaded adversary independently scheduled by the OS. WASH effectively identifies and optimizes a wider class of workloads than prior work.

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Citation

Source

Type

Conference paper

Book Title

CGO '16 Proceedings of the 2016 International Symposium on Code Generation and Optimization, Barcelona, Spain - March 12 - 18, 2016

Entity type

Access Statement

Open Access

License Rights

Restricted until