4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.AR2022★ 4 cited
A Real Time 1280x720 Object Detection Chip With 585MB/s Memory Traffic
Kuo-Wei Chang, Hsu-Tung Shih, Tian-Sheuan Chang +4
Memory bandwidth has become the real-time bottleneck of current deep learning accelerators (DLA), particularly for high definition (HD) object detection. Under resource constraints…
cs.AR2022
Zebra: Memory Bandwidth Reduction for CNN Accelerators With Zero Block Regularization of Activation Maps
Hsu-Tung Shih, Tian-Sheuan Chang
The large amount of memory bandwidth between local buffer and external DRAM has become the speedup bottleneck of CNN hardware accelerators, especially for activation maps. To reduc…