TransMap: An Efficient CGRA Mapping Framework via Transformer and Deep Reinforcement Learning
Author:
Affiliation:
1. Fudan University,State Key Laboratory of Integrated Chips and Systems,Shanghai,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10596331/10596332/10596400.pdf?arnumber=10596400
Reference39 articles.
1. A 2.92-Gb/s/W and 0.43-Gb/s/MG Flexible and Scalable CGRA-Based Baseband Processor for Massive MIMO Detection
2. Specializing CGRAs for Light-Weight Convolutional Neural Networks
3. Q2Logic: A Coarse-Grained FPGA Overlay targeting Schrödinger Quantum Circuit Simulations
4. Less for More: Reducing Intra-CGRA Connectivity for Higher Performance and Efficiency in HPC
5. An Architecture-Agnostic Integer Linear Programming Approach to CGRA Mapping
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