A paper describing the synthesis of a deep convolutional neural network (CNN) inference accelerator from C software with LegUp HLS will appear at the 2017 IEEE International System-on-Chip Conference (SOCC), at Munich, Germany, in September 2017. The work showcases the use of LegUp’s unique Pthreads flow to convert parallel software threads into spatial hardware parallelism. The accelerator incorporates a novel approach for zero-weight skipping, leveraging the ability to prune CNN weights with little inference accuracy loss.
J. H. Kim, B. Grady, R. Lian, J. Brothers, J.H. Anderson, “FPGA-Based CNN Inference Accelerator Synthesized from Multi-Threaded C Software,” IEEE SOCC, 2017 (PDF).
We are pleased to announce that LegUp 5.1 has been released!
This release is a culmination of more than 25 man-years of research and development. Prior to this release, LegUp has had 4 major releases for academic research. During these years, LegUp has been used by thousands of researchers around the world, making it the de-facto standard in high-level synthesis (HLS) research. In 2014, LegUp won the Community Award at the International Conference on Field Programmable Logic (FPL) for contributions to HLS research. LegUp has also been shown to produce state-of-the-art hardware.
We have brought all of the best features from our previous releases, and made it even better by adding new features, as well as improving the quality of the generated hardware.
Here are just some of the highlights of what we have added for this release.
- LegUp IDE which provides a complete development environment with a debugger and a profiler.
- Support for Xilinx, Lattice, Microsemi, and Achronix FPGAs (LegUp previously only supported Altera FPGAs).
- Windows OS support (LegUp previously only supported Linux OS).
- Improved pipelining.
- Improved memory architecture.
- Improved user messages.
LegUp 5.1 comes with a 30-day free trial period so that you can freely try out the tool. Please note that during the trial period, you may only use LegUp for evaluation purposes only, and the generated hardware cannot be used in a product. To purchase a full license, please contact us at email@example.com.