Overview

With the demise of Dennard scaling and the looming end of Moore’s law, architects scale the inefficient single-core CPU to multi-core CPUs to optimize performance. However, even multi-core CPUs are now nearing their performance limits due to the power wall. Therefore, the above limitations have spurred the rapid advancement of accelerators in various domains. Among the prevailing accelerators, Reconfigurable Architecture emerges as a formidable contender due to its post-silicon reconfigurability and the potential to approach application-specific integrated circuit (ASIC)-like energy-efficiency and performance.
In this workshop, we will introduce an open-source development framework for Reconfigurable Architecture, which covers the entire reconfigurable architecture development from the front-end compilation to ASIC implementation, enabling the architecture exploration at different stages in the software toolchain. For the front-end compilation, Fusion has two front-end tools, including: (1) the MLIR-based tool to compile the emerging applications, such as various deep neural networks; (2) the LLVM-based tool for more general-purpose, loop-kernel level compilation. Within the Fusion SoC, there is a RISC-V CPU and a Fused-Grained Reconfigurable Architecture (FGRA), which provides efficient acceleration for different computation-intensive kernels. Moreover, the Fusion SoC is a highly parameterized design, allowing for customization for specific applications through a design space exploration process based on Bayesian optimization. With several innovative optimizations, the Fusion SoC can significantly improve performance for computation-intensive systems.
We hope you enjoy the workshop and look forward to your valuable feedback.
Schedule
| Time | Speaker | Topic |
|---|---|---|
| 8:30 – 9:00 | Refreshments | |
| 9:00 – 9:15 | Prof. Lingli Wang | Introduction |
| 9:15 – 9:50 | Jiahang Lou | The Front-End Tools |
| 9:50 – 10:30 | Yuan Dai | Architecture and Software Optimizations |
| 10:30 – 10:50 | Coffee Break | |
| 10:50 – 11:10 | Jingyuan Li | Fusion DSE flow |
| 11:10 – 12:00 | All the organizers | Live Demo |
References
Core reading
- Y. Dai, X. Gao, Y. Qiu, J. Li, Y. Cao, Y. Mao, S. Chen, W. Yin, W. -S. Luk, L. Wang, “COFFA: A Co-Design Framework for Fused-Grained Reconfigurable Architecture Towards Efficient Irregular Loop Handling,” in IEEE Transactions on Computers, vol. 74, no. 9, pp. 3099-3113, Sept. 2025.
- X. Gao, Y. Qiu, Y. Dai, W. Yin and L. Wang, “A CGRA Front-end Compiler Enabling Extraction of General Control and Dedicated Operators,” 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 799-804, 2024.
- Y. Dai, X. Gao, C. Shen, B. Peng, W. Yin, W.-S. Luk, and L. Wang, “Towards Efficient Data Parallelism on Spatial CGRA via Constraint Satisfaction and Graph Coloring,” 2025 30th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 1023–1030, 2025.
- J. Li, Y. Hu, Y. Dai, H. Kuang and L. Wang, “AUGER: A Multi-Objective Design Space Exploration Framework for CGRAs,” 2023 International Conference on Field Programmable Technology (ICFPT), pp. 88-95, 2023.
- J. Li, Y. Dai, W. Yin, and L. Wang, “MoDAF: A Multi-objective Divide-and-Conquer Parameter Tuning Framework for CGRAs,” ACM Transactions on Design Automation of Electronic Systems, vol. 30, no. 5, pp. 1–28, Sep. 2025.
- J. Lou, Q. Zhu, Y. Dai, Z. Zhong, W. Yin and L. Wang, “Adora Compiler: End-to-End Optimization for High-Efficiency Dataflow Acceleration and Task Pipelining on CGRAs,” 2025 62nd ACM/IEEE Design Automation Conference (DAC), pp. 1-7, 2025.
- Y. Qiu, Y. Mao, X. Gao, S. Chen, J. Li, W. Yin, and L. Wang, “FDRA: A Framework for Dynamically Reconfigurable Accelerator Supporting Multi-Level Parallelism,” ACM Trans. Reconfig. Technol. Syst., vol. 17, no. 1, Art. no. 4, pp. 1–26, Mar. 2024.
- Y. Dai, X. Gao, H. Lin, W. Yin, W. Luk, L. Wang, “Dependency-Aware Data Parallelism on Spatial CGRA via Constraint Satisfaction and Graph Coloring,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), 2025, (Just Accepted).
Additional material
Demo Setup
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Follow the full tutorial
- Step-by-step walkthrough for CNB, Gitpod, and local Docker: Open Tutorial
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Accounts & connectivity
- Reliable internet access and a WeChat or GitHub account (for hosted codespaces)
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Reference materials
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Source repositories
- Github repo: FGRA Repo
- CNB docker repo: FGRA cnb docker repo
- Github docker repo: FGRA github docker repo
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Software requirements
- Docker 28+, must support amd64 Linux images
Organizers
- Prof. Lingli Wang
- Yuan Dai
- Jiahang Lou
- Jingyuan Li
- Huan Lin
- Guibin Zou
- XinYu Cai