CIMFormer: A 38.9TOPS/W-8b Systolic CIM-Array Based Transformer Processor with Token-Slimmed Attention Reformulating and Principal Possibility Gathering
Author:
Affiliation:
1. Tsinghua University,BNRist,Beijing,China
Funder
NSFC
National Key Research and Development Program
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10347557/10347908/10347930.pdf?arnumber=10347930
Reference6 articles.
1. DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification;Rao;NeurIPS,2021
2. 15.1 A Programmable Neural-Network Inference Accelerator Based on Scalable In-Memory Computing
3. A 28nm 27.5TOPS/W Approximate-Computing-Based Transformer Processor with Asymptotic Sparsity Speculating and Out-of-Order Computing
4. A 6.54-to-26.03 TOPS/W Computing-In-Memory RNN Processor using Input Similarity Optimization and Attention-based Context-breaking with Output Speculation
5. A 28nm 15.59uJ/Token Fully-Digital Bitline-Transpose CIM-based Sparse Transformer Accelerator with Pipeline/Parallel Reconfigurable Modes;Tu,2022
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