Jack Unit: An Area- and Energy-Efficient Multiply-Accumulate (MAC) Unit Supporting Diverse Data Formats

Fuente: arXiv
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Hauptverfasser: Noh, Seock-Hwan, Kim, Sungju, Kim, Seohyun, Kim, Daehoon, Kung, Jaeha, Kim, Yeseong
Format: Preprint
Veröffentlicht: 2025
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author Noh, Seock-Hwan
Kim, Sungju
Kim, Seohyun
Kim, Daehoon
Kung, Jaeha
Kim, Yeseong
author_facet Noh, Seock-Hwan
Kim, Sungju
Kim, Seohyun
Kim, Daehoon
Kung, Jaeha
Kim, Yeseong
contents In this work, we introduce an area- and energy-efficient multiply-accumulate (MAC) unit, named Jack unit, that is a jack-of-all-trades, supporting various data formats such as integer (INT), floating point (FP), and microscaling data format (MX). It provides bit-level flexibility and enhances hardware efficiency by i) replacing the carry-save multiplier (CSM) in the FP multiplier with a precision-scalable CSM, ii) performing the adjustment of significands based on the exponent differences within the CSM, and iii) utilizing 2D sub-word parallelism. To assess effectiveness, we implemented the layout of the Jack unit and three baseline MAC units. Additionally, we designed an AI accelerator equipped with our Jack units to compare with a state-of-the-art AI accelerator supporting various data formats. The proposed MAC unit occupies 1.17~2.01x smaller area and consumes 1.05~1.84x lower power compared to the baseline MAC units. On five AI benchmarks, the accelerator designed with our Jack units improves energy efficiency by 1.32~5.41x over the baseline across various data formats.
format Preprint
id arxiv_https___arxiv_org_abs_2507_04772
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Jack Unit: An Area- and Energy-Efficient Multiply-Accumulate (MAC) Unit Supporting Diverse Data Formats
Noh, Seock-Hwan
Kim, Sungju
Kim, Seohyun
Kim, Daehoon
Kung, Jaeha
Kim, Yeseong
Hardware Architecture
In this work, we introduce an area- and energy-efficient multiply-accumulate (MAC) unit, named Jack unit, that is a jack-of-all-trades, supporting various data formats such as integer (INT), floating point (FP), and microscaling data format (MX). It provides bit-level flexibility and enhances hardware efficiency by i) replacing the carry-save multiplier (CSM) in the FP multiplier with a precision-scalable CSM, ii) performing the adjustment of significands based on the exponent differences within the CSM, and iii) utilizing 2D sub-word parallelism. To assess effectiveness, we implemented the layout of the Jack unit and three baseline MAC units. Additionally, we designed an AI accelerator equipped with our Jack units to compare with a state-of-the-art AI accelerator supporting various data formats. The proposed MAC unit occupies 1.17~2.01x smaller area and consumes 1.05~1.84x lower power compared to the baseline MAC units. On five AI benchmarks, the accelerator designed with our Jack units improves energy efficiency by 1.32~5.41x over the baseline across various data formats.
title Jack Unit: An Area- and Energy-Efficient Multiply-Accumulate (MAC) Unit Supporting Diverse Data Formats
topic Hardware Architecture
url https://arxiv.org/abs/2507.04772