Optimizing Hybrid Binary-Unary Hardware Accelerators Using Self-Similarity Measures
Author:
Affiliation:
1. University of Minnesota,Department of Electrical and Computer Engineering,Minneapolis,MN,USA
Funder
Cisco Systems, Inc.
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10171436/10171441/10171591.pdf?arnumber=10171591
Reference14 articles.
1. Automatic decoding of input sinusoidal signal in a neuron model: High pass homomorphic filtering
2. Approximate Hybrid Binary-Unary Computing with Applications in BERT Language Model and Image Processing
3. Table-based polynomials for fast hardware function evaluation
4. Designing Custom Arithmetic Data Paths with FloPoCo
Cited by 3 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. SimBU: Self-Similarity-Based Hybrid Binary-Unary Computing for Nonlinear Functions;IEEE Transactions on Computers;2024-09
2. CompressedLUT: An Open Source Tool for Lossless Compression of Lookup Tables for Function Evaluation and Beyond;Proceedings of the 2024 ACM/SIGDA International Symposium on Field Programmable Gate Arrays;2024-04
3. Constant Coefficient Multipliers Using Self-Similarity-Based Hybrid Binary-Unary Computing;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28
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