Adaptive Scheduling for Systems with Asymmetric Memory Hierarchies
Name
2018.ams.micro.pdf
Description
Accepted version
Size
915.57 KB
Format
Adobe PDF
Checksum (MD5)
0502e137b9f760d99164316e8e1940a2
Author(s)
Tsai, Po-An
Chen, Changping
Sanchez, Daniel
Date Issued
December 2018
Journal
51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Tsai, Po-An et al. "Adaptive Scheduling for Systems with Asymmetric Memory Hierarchies." 51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), October 2018, Fukuoka, Japan, Institute of Electrical and Electronics Engineers (IEEE), December 2018. © 2018 IEEE
Version
Author's final manuscript
Abstract
Conventional multicores rely on deep cache hierarchies to reduce data movement. Recent advances in die stacking have enabled near-data processing (NDP) systems that reduce data movement by placing cores close to memory. NDP cores enjoy cheaper memory accesses and are more area-constrained, so they use shallow cache hierarchies instead. Since neither shallow nor deep hierarchies work well for all applications, prior work has proposed systems that incorporate both. These asymmetric memory hierarchies can be highly beneficial, but they require scheduling computation to the right hierarchy. We present AMS, an adaptive scheduler that automatically finds high-quality thread-To-hierarchy mappings. AMS monitors threads, accurately models their performance under different hierarchies and core types, and adapts algorithms first proposed for cache partitioning to produce high-quality schedules. AMS is cheap enough to use online, so it adapts to program phases, and performs within 1% of an exhaustive-search scheduler. As a result, AMS outperforms asymmetry-oblivious schedulers by up to 37% and by 18% on average.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/micro.2018.00058
