Information Session | February 1 | 6-7:30 p.m. | Soda Hall, Wozniak Lounge (430)
Meet engineers and recruiters from Xilinx, the company behind many of the hardware and software chip developments that are making deep learning more powerful and possible!
Make sure to bring a paper resume if you would like to be considered for intern or full time positions!
Thai food will be served!
Jim Hwang, Principal Engineer
Jayashree Rangarajan, Senior Director, Interactive Design Tools
Mike Furutani, Senior Technical Recruiter
***Topic: Software programmability of FPGAs***
Deep learning applications are rapidly expanding across a growing number of end markets, at the edge and in the cloud, with computational workloads requiring special purpose processors. FPGAs provide a unique combination of programmability, high performance, low latency, and low power for many applications, including machine learning, embedded vision, genomics, and data analytics. Arguably the largest challenge to deploying FPGAs is the classical design flow consisting of building custom system-on-chip hardware, and then programming software to run on the device. Xilinx is at the forefront in enabling traditional software programming models for FPGAs, providing system compilers that generate FPGA accelerators and systems-on-chip (hardware and software), from programs written in C/C++ and OpenCL. This presentation will provide a brief introduction to FPGAs as deployed in todays datacenters and automobiles (e.g., driver assist and autonomous drive), then focus on software programming models, compilers, and development environments. Sample applications being developed using these tools include custom FPGA systems that combine machine learning and video analytics accelerators with application software written with OpenCV libraries in C++.