CNN Accelerator Performance Dependence on Loop Tiling and the Optimum Resource-Constrained Loop Tiling
This paper analyzes the dependence of the convolutional neural network (CNN) accelerator performance on loop tiling. More specifically, based on the closed-form expression of the CNN accelerator performance, the dependence on the tile sizes is characterized by the derivative, the asymptote and the s...
Saved in:
Main Authors: | Chester Sungchung Park, Sungkyung Park |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10849540/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An efficient loop tiling framework for convolutional neural network inference accelerators
by: Hongmin Huang, et al.
Published: (2022-01-01) -
Tilings in topological spaces
by: F. G. Arenas
Published: (1999-01-01) -
A simple beam model to analyse the durability of adhesively bonded tile floorings in presence of shrinkage
by: S. de Miranda, et al.
Published: (2014-07-01) -
Mergeable adaptive tile coding method
by: Meng-yu SHI, et al.
Published: (2015-02-01) -
A Hardware Accelerator for the Inference of a Convolutional Neural network
by: Edwin González, et al.
Published: (2019-11-01)