Multi: Reduce Energy Overhead of Criticality-Aware Dynamic Instruction Scheduling for Energy Efficiency

Criticality-aware dynamic instruction scheduling (DIS) focuses on prioritizing the execution of critical instructions, thereby significantly improving performance. However, criticality-aware DIS is energy-intensive. Energy overhead mainly comes from the design of DIS strategy and the multi-port tables used for extracting critical instruction slices. In this study, Multi is proposed, which develops an energy-efficient DIS strategy and an adaptive multi-port table coordinated with the DIS strategy to reduce the energy overhead of criticality-aware DIS. Evaluation on the SPEC CPU2017 benchmark shows that Multi outperforms the state-of-the-art work in terms of core energy consumption with a geometric mean reduction of 5.9%. Moreover, post-layout simulation results demonstrate a 61.2% reduction in energy consumption of the proposed adaptive multi-port table. It also proves the applicability of Multi in ultra-wide processors with unified or distributed schedulers, contributing to enhanced energy efficiency.

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Publication Details

Published
2024-11-18
DOI
https://doi.org/10.1109/iccd63220.2024.00020
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
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article

Multi: Reduce Energy Overhead of Criticality-Aware Dynamic Instruction Scheduling for Energy Efficiency

Xianhua Liu, Honglan Zhan, Xin Wang, Cheng Xu et al.
Parallel Computing and Optimization Techniques
article

Multi: Reduce Energy Overhead of Criticality-Aware Dynamic Instruction Scheduling for Energy Efficiency

Xianhua Liu, Honglan Zhan, Xin Wang, Cheng Xu, Chenxi Wang, Chun Yang
article en

Abstract

Criticality-aware dynamic instruction scheduling (DIS) focuses on prioritizing the execution of critical instructions, thereby significantly improving performance. However, criticality-aware DIS is energy-intensive. Energy overhead mainly comes from the design of DIS strategy and the multi-port tables used for extracting critical instruction slices. In this study, Multi is proposed, which develops an energy-efficient DIS strategy and an adaptive multi-port table coordinated with the DIS strategy to reduce the energy overhead of criticality-aware DIS. Evaluation on the SPEC CPU2017 benchmark shows that Multi outperforms the state-of-the-art work in terms of core energy consumption with a geometric mean reduction of 5.9%. Moreover, post-layout simulation results demonstrate a 61.2% reduction in energy consumption of the proposed adaptive multi-port table. It also proves the applicability of Multi in ultra-wide processors with unified or distributed schedulers, contributing to enhanced energy efficiency.

Anhui University (CN), Peking University (CN)
Affordable and clean energy
Openalex Percentile: Top 73%
Parallel Computing and Optimization Techniques
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