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DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space
  for DNN Accelerators through Analytical Modeling

DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling

10 December 2022
L. Mei
Koen Goetschalckx
Arne Symons
Marian Verhelst
ArXivPDFHTML

Papers citing "DeFiNES: Enabling Fast Exploration of the Depth-first Scheduling Space for DNN Accelerators through Analytical Modeling"

3 / 3 papers shown
Title
MAS-Attention: Memory-Aware Stream Processing for Attention Acceleration on Resource-Constrained Edge Devices
MAS-Attention: Memory-Aware Stream Processing for Attention Acceleration on Resource-Constrained Edge Devices
Mohammadali Shakerdargah
Shan Lu
Chao Gao
Di Niu
70
0
0
20 Nov 2024
DNNFuser: Generative Pre-Trained Transformer as a Generalized Mapper for
  Layer Fusion in DNN Accelerators
DNNFuser: Generative Pre-Trained Transformer as a Generalized Mapper for Layer Fusion in DNN Accelerators
Sheng-Chun Kao
Xiaoyu Huang
T. Krishna
AI4CE
33
9
0
26 Jan 2022
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
950
20,561
0
17 Apr 2017
1