Flex-SFU: Accelerating DNN Activation Functions by Non-Uniform Piecewise Approximation

Modern DNN workloads increasingly rely on activation functions consisting of computationally complex operations. This poses a challenge to current accelerators optimized for convolutions and matrix-matrix multiplications. This work presents Flex-SFU, a lightweight hardware accelerator for activation...

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Bibliographic Details

Published in:	2023 60th ACM/IEEE Design Automation Conference (DAC) pp. 1 - 6
Main Authors:	Reggiani, Enrico, Andri, Renzo, Cavigelli, Lukas
Format:	Conference Proceeding
Language:	English
Published:	IEEE 09.07.2023
Subjects:	Computational modeling Computer vision Decoding Design automation Heuristic algorithms Interpolation Natural language processing
Online Access:	Get full text
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