What is it about?
The Problem: Coarse-Grained Reconfigurable Arrays (CGRAs) are powerful computing chips that balance high performance with energy efficiency. However, existing software compilers often act like inefficient traffic controllers: they try to route data tasks one by one, ignoring how they relate to each other. This leads to "traffic jams" on the chip, causing slow performance and long waiting times. The Solution: We introduce "Rewire," a smarter mapping approach that processes multiple data tasks in one shot. Instead of looking at individual tasks in isolation, Rewire analyzes their inter-dependencies and routes them together as a group. It innovatively uses shared routing information to find the perfect spot for multiple tasks simultaneously, eliminating bottlenecks.
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Why is it important?
Unlocking Hardware Potential: Even the fastest chip is useless without good software to run it. Rewire significantly closes the gap between hardware capability and software efficiency. Quantifiable Success: Our evaluation shows that Rewire is not just a theoretical improvement—it delivers a 2.1x boost in execution performance and cuts the time required to compile programs by up to 13.5x compared to popular existing tools. Industry Relevance: For the semiconductor and AI industries, this paradigm shift means we can design specialized chips that are faster to program and more efficient to run, accelerating the deployment of high-performance computing applications.
Perspectives
Refining the Compiler Landscape: For a long time, the potential of CGRAs was limited not by the hardware itself, but by the inefficiency of the software mapping process. With Rewire, my goal was to challenge the conventional "node-by-node" compilation strategy that has dominated our field. I believe that by shifting to a consolidated routing paradigm, we are finally breaking the dependency bottlenecks that slowed down development. This work is a crucial step toward making domain-specific architectures practically usable for the next generation of AI and data-intensive applications, bridging the gap between theoretical peak performance and real-world efficiency.
Dr Huize Li
University of Central Florida
Read the Original
This page is a summary of: Rewire: Advancing CGRA Mapping Through a Consolidated Routing Paradigm, June 2025, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/dac63849.2025.11133240.
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