MultiSky: Dynamic Resource Allocation Framework for High-Throughput CGRA Multitask Execution

Coarse-grained reconfigurable arrays (CGRAs) offer a promising balance between high performance and flexibility, yet dynamic resource allocation in multi-task scenarios remains challenging due to unpredictable task creation/destruction. Existing static approaches lack flexibility, while dynamic methods suffer from high latency or limited applicability. This paper presents MultiSky, a framework for CGRA multi-task dynamic resource allocation, combining a hardware controller and a software pre-mapper. The hardware controller dynamically allocates resources within hundreds of cycles by calculating tile allocation for each task via weighted averaging, and generating tile shapes using a lightweight heuristic algorithm. The software pre-mapper employs incremental compilation to pre-generate configurations, avoiding online transformation overhead. Evaluations on a real-world multi-task scenario demonstrate that MultiSky achieves 1.72× higher throughput than baselines by maintaining 82.7% average resource utilization. The framework scales efficiently with larger CGRAs and task counts, with hardware overhead decreasing to 1% for 16×16 CGRAs. These results highlight MultiSky’s ability to balance flexibility, efficiency, and practicality in dynamic computing environments.

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Publication Details

Journal
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Published
2025-08-11
DOI
https://doi.org/10.1109/tcad.2025.3597525
Citations
2
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
2.97
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article

MultiSky: Dynamic Resource Allocation Framework for High-Throughput CGRA Multitask Execution

Xiyuan Peng, Yufei Yang, Chenhao Xie, Liansheng Liu et al.
2 citations
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Distributed and Parallel Computing Systems
2.97
article

MultiSky: Dynamic Resource Allocation Framework for High-Throughput CGRA Multitask Execution

Xiyuan Peng, Yufei Yang, Chenhao Xie, Liansheng Liu, Rui Wang, Yu Peng
article en
2 citations

Abstract

Coarse-grained reconfigurable arrays (CGRAs) offer a promising balance between high performance and flexibility, yet dynamic resource allocation in multi-task scenarios remains challenging due to unpredictable task creation/destruction. Existing static approaches lack flexibility, while dynamic methods suffer from high latency or limited applicability. This paper presents MultiSky, a framework for CGRA multi-task dynamic resource allocation, combining a hardware controller and a software pre-mapper. The hardware controller dynamically allocates resources within hundreds of cycles by calculating tile allocation for each task via weighted averaging, and generating tile shapes using a lightweight heuristic algorithm. The software pre-mapper employs incremental compilation to pre-generate configurations, avoiding online transformation overhead. Evaluations on a real-world multi-task scenario demonstrate that MultiSky achieves 1.72× higher throughput than baselines by maintaining 82.7% average resource utilization. The framework scales efficiently with larger CGRAs and task counts, with hardware overhead decreasing to 1% for 16×16 CGRAs. These results highlight MultiSky’s ability to balance flexibility, efficiency, and practicality in dynamic computing environments.

IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsVol. 45(3)
Harbin Institute of Technology (CN), Heilongjiang Institute of Technology (CN), Beihang University (CN)
Openalex Percentile: Top 8%
Distributed and Parallel Computing Systems
2.97
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