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An SRAM-Based Multibit In-Memory Matrix-Vector Multiplier With a Precision That Scales Linearly in Area, Time, and Power

Authors: Riduan Khaddam-Aljameh; Pier Andrea Francese; Luca Benini; Evangelos Eleftheriou;

An SRAM-Based Multibit In-Memory Matrix-Vector Multiplier With a Precision That Scales Linearly in Area, Time, and Power

Abstract

A novel interleaved switched-capacitor and SRAM-based multibit matrix-vector multiply-accumulate engine for in-memory computing is presented. Its operation principle is based on first converting an SRAM-stored n-bit weight into a proportional voltage using a pipeline D/A converter built from n+1 equally sized stages. A switched-capacitor stage then multiplies these voltages with an m-bit digital input activation. Finally, the output voltages that correspond to the different multiplication results are accumulated along one column by means of charge-sharing. With our proposed architecture, the required circuit area, computation time, and power consumption scale linearly versus the bit resolution of both the inputs and the weights. Analytical formulas are presented for the energy consumption in both capacitors and switches. Moreover, the impact of fabrication mismatch on analog computation accuracy is examined. The full system architecture is described, and the feasibility is demonstrated, via a full macroimplementation study in 14 nm, detailing area and energy consumption, as well as the overall latency. Finally, a specific design of a 128 x 2048 6-bit weight and 6-bit input signed matrix-vector multiplication accelerator system in 14 nm is presented, which runs at 2.43 TOP/s at an efficiency of 16.94 TOP/s/W, while using the nominal supply voltage of 0.8 V. If the operands' precision is considered in the metric, then the efficiency becomes 609.7 TOP/s/W.

IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 29 (2)

ISSN:1063-8210

ISSN:1557-9999

Countries
Italy, Switzerland
Keywords

Analog computation, in-memory computation, multibit weights, in-memory computing, SRAM, Analog computation; hardware accelerator; in-memory computation; multibit weights; SRAM, SRAM, hardware accelerator

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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