RC-NVM: Dual-Addressing Non-Volatile Memory Architecture Supporting Both Row and Column Memory Accesses

Although emerging non-volatile memories (NVMs) have been comprehensively studied to design next-generation memory systems, the symmetry of the crossbar structure adopted by most NVMs has not been addressed. In this work, we argue that crossbar-based NVMs can enable dual-addressing memory architectur...

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Bibliographic Details
Published in:IEEE transactions on computers Vol. 68; no. 2; pp. 239 - 254
Main Authors: Li, Shuo, Xiao, Nong, Wang, Peng, Sun, Guangyu, Wang, Xiaoyang, Chen, Yiran, Li, Hai Helen, Cong, Jason, Zhang, Tao
Format: Journal Article
Language:English
Published: New York IEEE 01.02.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Cache storage
Computer architecture
Computer memory
crossbar
Design engineering
in-memory database
Memory architecture
Non-volatile memory
Nonvolatile memory
OLAP
OLTP
Random access memory
Workloads
ISSN:0018-9340, 1557-9956
Online Access:Get full text
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Summary:Although emerging non-volatile memories (NVMs) have been comprehensively studied to design next-generation memory systems, the symmetry of the crossbar structure adopted by most NVMs has not been addressed. In this work, we argue that crossbar-based NVMs can enable dual-addressing memory architecture, i.e., RC-NVM, to support both row- and column-oriented memory accesses for workloads with different access patterns. Through circuit-level analysis, we first prove that such a dual-addressing architecture is only practical with crossbar-based NVMs rather than DRAM. Then, we introduce the RC-NVM architecture from bank, chip and module levels, and propose RC-NVM aware memory controller. We also address the challenges to implement the end-to-end RC-NVM system. Especially, we design a novel protocol to solve the cache synonym problem with very little overhead. Finally, we introduce the deployment of RC-NVM for in-memory databases (IMDBs) and evaluate its performance with IMDBs and well-optimized general matrix multiply (GEMM) workloads. Experimental results show that with only 10 percent area overhead 1) the memory access performance of IMDBs can be improved up to 14.5X, and 2) for GEMM, RC-NVM naturally supports SIMD operations and outperforms the best tiled layout by 19 percent.
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ISSN:0018-9340
1557-9956
DOI:10.1109/TC.2018.2868368