FUSE: Fusing STT-MRAM into GPUs to alleviate off-chip memory access overheads

Jie Zhang, Myoungsoo Jung, Mahmut Kandemir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this work, we propose FUSE, a novel GPU cache system that integrates spin-transfer torque magnetic random-access memory (STT-MRAM) into the on-chip L1D cache. FUSE can minimize the number of outgoing memory accesses over the interconnection network of GPU's multiprocessors, which in turn can considerably improve the level of massive computing parallelism in GPUs. Specifically, FUSE predicts a read-level of GPU memory accesses by extracting GPU runtime information and places write-once-read-multiple (WORM) data blocks into the STT-MRAM, while accommodating write-multiple data blocks over a small portion of SRAM in the L1D cache. To further reduce the off-chip memory accesses, FUSE also allows WORM data blocks to be allocated anywhere in the STT-MRAM by approximating the associativity with the limited number of tag comparators and I/O peripherals. Our evaluation results show that, in comparison to a traditional GPU cache, our proposed heterogeneous cache reduces the number of outgoing memory references by 32% across the interconnection network, thereby improving the overall performance by 217% and reducing energy cost by 53%.

Original languageEnglish (US)
Title of host publicationProceedings - 25th IEEE International Symposium on High Performance Computer Architecture, HPCA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages426-439
Number of pages14
ISBN (Electronic)9781728114446
DOIs
StatePublished - Mar 26 2019
Event25th IEEE International Symposium on High Performance Computer Architecture, HPCA 2019 - Washington, United States
Duration: Feb 16 2019Feb 20 2019

Publication series

NameProceedings - 25th IEEE International Symposium on High Performance Computer Architecture, HPCA 2019

Conference

Conference25th IEEE International Symposium on High Performance Computer Architecture, HPCA 2019
CountryUnited States
CityWashington
Period2/16/192/20/19

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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    Zhang, J., Jung, M., & Kandemir, M. (2019). FUSE: Fusing STT-MRAM into GPUs to alleviate off-chip memory access overheads. In Proceedings - 25th IEEE International Symposium on High Performance Computer Architecture, HPCA 2019 (pp. 426-439). [8675216] (Proceedings - 25th IEEE International Symposium on High Performance Computer Architecture, HPCA 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HPCA.2019.00055