AFPR-CIM: An Analog-Domain Floating-Point RRAM -based Compute- In- Memory Architecture with Dynamic Range Adaptive FP-ADC
Author:
Affiliation:
1. University of Electronic Science and Technology of China,Shenzhen Institute for Advanced Study,Shenzhen,China
2. Central Research Institute,Shenzhen,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10546498/10546499/10546882.pdf?arnumber=10546882
Reference16 articles.
1. Bfloat16: The secret to high performance on cloud tpus;Wang;Google Cloud Blog,2019
2. 9.3 A 40nm 4.81TFLOPS/W 8b Floating-Point Training Processor for Non-Sparse Neural Networks Using Shared Exponent Bias and 24-Way Fused Multiply-Add Tree
3. Fp8 versus int8 for efficient deep learning inference;van Baalen;arXiv preprint,2023
4. Fp8 quantization: The power of the exponent;Kuzmin;Advances in Neural Information Processing Systems,2022
5. ISAAC
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