Shift-CIM: In-SRAM Alignment To Support General-Purpose Bit-level Sparsity Exploration in SRAM Multiplication

Multiplication plays a critical role in SRAM-based Computing-in-Memory (CIM) architectures. However, current SRAM-based CIMs face three major limitations. First, they do not fully exploit bit-level sparsity, resulting in unnecessary overhead in both latency and energy consumption. Second, the generation of numerous zero-dot products is superfluous. Third, the irregular organization of SRAM complicates the implementation. To address these issues, we propose Shift-CIM, a general-purpose approach that fully leverages bit-level sparsity within SRAM-based multiplications. Shift-CIM aligns the multipliers within the SRAM array, accumulating only the required dot products based on the non-zero bits of the multipliers. Shift-CIM achieves a regular SRAM organization by assembling two irregular SRAM arrays in a transposed manner. Our evaluations show that Shift-CIM is highly efficient, operating at a supply voltage of 0.9 V and a frequency of 833 MHz, while incurring only a 4.8% area overhead. Despite these modest requirements, Shift-CIM significantly accelerates multiplication operations, achieving up to 3.08× the performance improvement and a 60% reduction in energy consumption compared to state-of-the-art designs.

Authors

Institutions

Publication Details

Journal
ACM Transactions on Architecture and Code Optimization
Published
2025-03-01
DOI
https://doi.org/10.1145/3719654
Primary Topic
Advanced Data Storage Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Shift-CIM: In-SRAM Alignment To Support General-Purpose Bit-level Sparsity Exploration in SRAM Multiplication

Rongzhen Lin, Qiuran Li, Guomin Zhao, Yaohua Wang
ACM Transactions on Architecture and Code Optimization
Advanced Data Storage Technologies
article

Shift-CIM: In-SRAM Alignment To Support General-Purpose Bit-level Sparsity Exploration in SRAM Multiplication

Rongzhen Lin, Qiuran Li, Guomin Zhao, Yaohua Wang
article en

Abstract

Multiplication plays a critical role in SRAM-based Computing-in-Memory (CIM) architectures. However, current SRAM-based CIMs face three major limitations. First, they do not fully exploit bit-level sparsity, resulting in unnecessary overhead in both latency and energy consumption. Second, the generation of numerous zero-dot products is superfluous. Third, the irregular organization of SRAM complicates the implementation. To address these issues, we propose Shift-CIM, a general-purpose approach that fully leverages bit-level sparsity within SRAM-based multiplications. Shift-CIM aligns the multipliers within the SRAM array, accumulating only the required dot products based on the non-zero bits of the multipliers. Shift-CIM achieves a regular SRAM organization by assembling two irregular SRAM arrays in a transposed manner. Our evaluations show that Shift-CIM is highly efficient, operating at a supply voltage of 0.9 V and a frequency of 833 MHz, while incurring only a 4.8% area overhead. Despite these modest requirements, Shift-CIM significantly accelerates multiplication operations, achieving up to 3.08× the performance improvement and a 60% reduction in energy consumption compared to state-of-the-art designs.

ACM Transactions on Architecture and Code OptimizationVol. 22(2)
National Defense University (US), National University of Defense Technology (CN)
Openalex Percentile: Top 97%
Advanced Data Storage Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.