Chimera: Transparent and High-Performance ISAX Heterogeneous Computing via Binary Rewriting
Jiatai He, Qinglin Pan, Ruilin Zhao, Ji Qi, Kaiwen Liang, Jiahao Xu, Zhiyuan Li, Yuexiang Wang, Jiageng Yu, Yanjun Wu
Abstract
ISAX heterogeneous processors integrate cores that share a common base ISA, with certain cores offering extension ISAs (e.g., vector extension) to accelerate computation. ISAX balances performance and energy efficiency while facilitating the reuse of existing software ecosystems. RISC-V, which adopts the ISAX architecture, has gained extensive attention in both industry and academia. Binary translation via binary rewriting enables transparent ISAX heterogeneous computing by translating extension instructions when migrating a program to cores without extension support. However, current binary rewriting methods still struggle to achieve both high performance and correctness.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get d9934914-db11-41da-9fb0-f55f85fb8cf4Related papers
- Longnail: High-Level Synthesis of Portable Custom Instruction Set Extensions for RISC-V Processors from Descriptions in the Open-Source CoreDSL LanguageJulian Oppermann, Brindusa Mihaela Damian-Kosterhon, Florian Meisel, Tammo Mürmann et al.ASPLOS 2024 · 15 citations
- SCAIE-V: an open-source SCAlable interface for ISA extensions for RISC-V processorsMihaela Damian, Julian Oppermann, Christoph Spang, Andreas KochDAC 2022 · 18 citations
- Flick: Fast and Lightweight ISA-Crossing Call for Heterogeneous-ISA EnvironmentsShenghsun Cho, Han Chen, Sergey Madaminov, Michael Ferdman et al.ISCA 2020 · 11 citations
- BYOC: A "Bring Your Own Core" Framework for Heterogeneous-ISA ResearchJonathan Balkind, Katie Lim, Michael Schaffner, Fei Gao et al.ASPLOS 2020 · 29 citations
- Remote Atomic Extension (RAE) for Scalable High Performance ComputingXi Wang, Brody Williams, John D. Leidel, Alan Ehret et al.DAC 2020 · 8 citations
