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- W3042739957 abstract "Modern Graphics Processing Units (GPUs) require large hardware resources for massive parallel thread executions. In particular, modern GPUs have a large register file composed of Static Random Access Memory (SRAM). Due to the high leakage current of SRAM, the register file consumes approximately 20% of the total GPU energy. The energy efficiency of the register file becomes more critical as the throughput of GPUs increases. For more energy-efficient GPUs, the usage of non-volatile memory such as Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM) as the GPU register file has been studied extensively. STT-MRAM requires a lower leakage current compared to SRAM and provides an appropriate read performance. However, using STT-MRAM directly in the GPU register file causes problems in performance and endurance because of complicated write procedures and material characteristics. To overcome these challenges, we propose a novel register file architecture and its management system for GPUs, named Hi-End, which exploits the data locality and compressibility of the register file. For STT-MRAM-based GPU register files, Hi-End increases the data write performance and endurance by caching and data compression, respectively. In our evaluation, Hi-End enhances the energy efficiency of a GPU register file by 70.02% and reduces the write operations by up to 95.98% with negligible performance degradation compared to SRAM-based register files." @default.
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- W3042739957 date "2020-01-01" @default.
- W3042739957 modified "2023-10-15" @default.
- W3042739957 title "Hi-End: Hierarchical, Endurance-Aware STT-MRAM-Based Register File for Energy-Efficient GPUs" @default.
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- W3042739957 doi "https://doi.org/10.1109/access.2020.3008719" @default.
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