Advancing Near-Data Processing with Precise Exceptions and Efficient Data Fetching

2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)(2022)

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摘要
Near-Data Processing (NDP) modifies the traditional computer system design by placing logic near the memory, bringing computation to the data. One NDP approach places such elements on the logic layer of 3D-stacked memories to quickly access data while avoiding reliance on narrow buses and better accessing the parallelism these devices offer. However, NDP architectures often fail to fully leverage available memory resources. In this work, we propose adding an instruction buffer to a common NDP design with large vector instructions. This modification allows the NDP to fetch instruction operands out of program order and delegates some responsibility regarding precise exceptions to the near-data device. Our results show our modifications cause a reduction in execution time of up to 28% while consuming up to 25% less energy.
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关键词
near-data processing,3d-stacked memory,computer architecture
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