SAHM: State-Aware Heterogeneous Multicore for Single-Thread Performance

Fuente: arXiv
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Autori principali: Wadle, Shayne, Sankaralingam, Karthikeyan
Natura: Preprint
Pubblicazione: 2025
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author Wadle, Shayne
Sankaralingam, Karthikeyan
author_facet Wadle, Shayne
Sankaralingam, Karthikeyan
contents Improving single-thread performance remains a critical challenge in modern processor design, as conventional approaches such as deeper speculation, wider pipelines, and complex out-of-order execution face diminishing returns. This work introduces SAHM-State-Aware Heterogeneous Multicore-a novel architecture that targets performance gains by exploiting fine-grained, time-varying behavioral diversity in single-threaded workloads. Through empirical characterization of performance counter data, we define 16 distinct behavioral states representing different microarchitectural demands. Rather than over-provisioning a monolithic core with all optimizations, SAHM uses a set of specialized cores tailored to specific states and migrates threads at runtime based on detected behavior. This design enables composable microarchitectural enhancements without incurring prohibitive area, power, or complexity costs. We evaluate SAHM in both single-threaded and multiprogrammed scenarios, demonstrating its ability to maintain core utilization while improving overall performance through intelligent state-driven scheduling. Experimental results show opportunity for 17% speed up in realistic scenarios. These speed ups are robust against high-cost migration, decreasing by less than 1%. Overall, state-aware core specialization is a new path forward for enhancing single-thread performance.
format Preprint
id arxiv_https___arxiv_org_abs_2509_22405
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle SAHM: State-Aware Heterogeneous Multicore for Single-Thread Performance
Wadle, Shayne
Sankaralingam, Karthikeyan
Performance
Hardware Architecture
Improving single-thread performance remains a critical challenge in modern processor design, as conventional approaches such as deeper speculation, wider pipelines, and complex out-of-order execution face diminishing returns. This work introduces SAHM-State-Aware Heterogeneous Multicore-a novel architecture that targets performance gains by exploiting fine-grained, time-varying behavioral diversity in single-threaded workloads. Through empirical characterization of performance counter data, we define 16 distinct behavioral states representing different microarchitectural demands. Rather than over-provisioning a monolithic core with all optimizations, SAHM uses a set of specialized cores tailored to specific states and migrates threads at runtime based on detected behavior. This design enables composable microarchitectural enhancements without incurring prohibitive area, power, or complexity costs. We evaluate SAHM in both single-threaded and multiprogrammed scenarios, demonstrating its ability to maintain core utilization while improving overall performance through intelligent state-driven scheduling. Experimental results show opportunity for 17% speed up in realistic scenarios. These speed ups are robust against high-cost migration, decreasing by less than 1%. Overall, state-aware core specialization is a new path forward for enhancing single-thread performance.
title SAHM: State-Aware Heterogeneous Multicore for Single-Thread Performance
topic Performance
Hardware Architecture
url https://arxiv.org/abs/2509.22405