New Flexible Multiple-Precision Multiply-Accumulate Unit for Deep Neural Network Training and Inference

Author:

Zhang HaoORCID,Chen Dongdong,Ko Seok-BumORCID

Funder

Natural Sciences and Engineering Research Council of Canada

University of Saskatchewan

R&D program of MOTIE/KEIT

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software

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1. ABS: Accumulation Bit-Width Scaling Method for Designing Low-Precision Tensor Core;IEEE Transactions on Very Large Scale Integration (VLSI) Systems;2024-09

2. A Case for Low Bitwidth Floating Point Arithmetic on FPGA for Transformer Based DNN Inference;2024 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW);2024-05-27

3. A Reconfigurable Fused Multiply-Accumulate For Miscellaneous Operators in Deep Neural Network;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19

4. Adaptive approximate computing in edge AI and IoT applications: A review;Journal of Systems Architecture;2024-05

5. Design of an Efficient Deep Neural Network Accelerator Based on Block Posit Number Representation;2024 International VLSI Symposium on Technology, Systems and Applications (VLSI TSA);2024-04-22

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