SparseAdapt: Runtime Control for Sparse Linear Algebra on a Reconfigurable Accelerator

Author:

Pal Subhankar1,Amarnath Aporva1,Feng Siying2,O'Boyle Michael3,Dreslinski Ronald1,Dubach Christophe4

Affiliation:

1. University of Michigan, United States of America

2. University of Michigan

3. University of Edinburgh, United Kingdom

4. McGill University, Canada

Funder

Defense Advanced Research Projects Agency

Natural Sciences and Engineering Research Council of Canada

Publisher

ACM

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. FEASTA: A Flexible and Efficient Accelerator for Sparse Tensor Algebra in Machine Learning;Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3;2024-04-27

2. Pipestitch: An energy-minimal dataflow architecture with lightweight threads;56th Annual IEEE/ACM International Symposium on Microarchitecture;2023-10-28

3. Spatula: A Hardware Accelerator for Sparse Matrix Factorization;56th Annual IEEE/ACM International Symposium on Microarchitecture;2023-10-28

4. Flexagon: A Multi-dataflow Sparse-Sparse Matrix Multiplication Accelerator for Efficient DNN Processing;Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3;2023-03-25

5. A Reschedulable Dataflow-SIMD Execution for Increased Utilization in CGRA Cross-Domain Acceleration;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2023-03

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