Abstract
GIRAF is a General purpose In-storage Resistive Associative Framework based on resistive content addressable memory (RCAM), which functions simultaneously as a storage and a massively parallel associative processor. GIRAF alleviates the bandwidth wall by connecting every memory bit to processing transistors and keeping computing inside the storage arrays, thus implementing deep in-data, rather than near-data, processing. We show that GIRAF outperformed a reference computer architecture with a bandwidth-limited external storage access on a variety of data-intensive workloads. The performance of GIRAF Dot Product and Sparse Matrix-Vector multiplication exceeds the attainable performance of a reference architecture by 1200 × and 130 ×, respectively.
Original language | English |
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Pages (from-to) | 276-287 |
Number of pages | 12 |
Journal | IEEE Transactions on Parallel and Distributed Systems |
Volume | 33 |
Issue number | 2 |
DOIs | |
State | Published - 2021 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:IEEE
Keywords
- Memristors
- associative processing
- processing in memory
- processing in storage
- resistive content addressable memory