Name
Title | ||
|---|---|---|
MP-OPU: A Mixed Precision FPGA-based Overlay Processor for Convolutional Neural Networks |
Abstract | ||
|---|---|---|
Low precision quantization in convolutional neural network (CNN) inference has been proved effective for reducing computation complexity and bandwidth requirement. Mixed precision CNNs manage to benefit from low precision while maintaining accuracy. In this paper, we propose a Mixed Precision FPGA-based Overlay Processor (MP-OPU) to fully leverage the advantages of mixed precision for both convent... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/FPL53798.2021.00014 | 2021 31st International Conference on Field-Programmable Logic and Applications (FPL) |
Keywords | DocType | ISSN |
Quantization (signal),Processor scheduling,Bandwidth,Computer architecture,Throughput,Hardware,Computational efficiency | Conference | 1946-1488 |
ISBN | Citations | PageRank |
978-1-6654-3759-2 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Wu | 1 | 69 | 6.20 |
| Jinming Zhuang | 2 | 0 | 0.34 |
| Kun Wang | 3 | 425 | 56.96 |
| Lei He | 4 | 16 | 7.77 |