opendacs
/
DeepBurning-MixQ
forked from liucheng/DeepBurning-MixQ
9
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

update readme

This commit is contained in:
fffasttime 2023-05-17 15:34:48 +08:00
parent 587637c4fc
commit 98e9efffde
1 changed files with 4 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

9
readme.md
View File

@ -1,9 +1,8 @@
# AnyPackingNet
# AnyPacking Serach & Train & Export
This is the training model source code of the paper:
This is the training model source code for NAS packing.
Mixed-precision Neural Network Quantization and
Implementation Co-optimization for FPGAs
Our paper is under submission.
## Classification Model
@ -123,4 +122,4 @@ python simulate_hls.py [--model [UltraNet_Bypass_FixQ | SkyNet_FixQ | SkyNetk5_F
- https://github.com/xliu0709/DACSDC2021 iSmart team, 2nd place of 2021 DAC-SDC design, UltraNet with optimized packing method
- https://github.com/heymesut/SJTU_microe 3rd place of 2021 DAC-SDC design by SJTU, a variant of UltraNet with bypass
- https://github.com/jgoeders/dac_sdc_2022_designs Winner designs of 2022 DAC-SDC contest
- https://github.com/MatthewLuo7/InvolutionNet 3rd place of 2022 DAC-SDC design (ours), without anypacking design
- https://github.com/MatthewLuo7/InvolutionNet 3rd place of 2022 DAC-SDC design, without anypacking design