Xilinx develops highly flexible and adaptive processing platforms that enable rapid innovation across a variety of technologies - from the endpoint to the edge to the cloud. Xilinx is the inventor of the FPGA, hardware programmable SoCs and the ACAP (Adaptive Compute Acceleration Platform), designed to deliver the most dynamic processor technology in the industry and enable the adaptable, intelligent and connected world of the future in a multitude of markets including Data Center (Compute, Storage and Networking); Wireless/5G and Wired Communications; Automotive/ADAS; Emulation & Prototyping; Aerospace & Defense; Industrial Scientific & Medical, and others. Xilinx's core strengths simultaneously address major industry trends including the explosion of data, heterogeneous computing after Moore's Law, and the dawn of artificial intelligence (AI).
The research intern position is with Xilinx Labs at the Xilinx Asia-Pacific headquarters in Singapore. Xilinx Labs, part of the CTO Office at Xilinx, is concerned with innovation, differentiation, and the de-risking of technology. Goals are to: enable new users; provide a ‘more than Moore’ roadmap; seed new market opportunities; and win the mindshare of startup and research communities.
The research intern will participate in distributed system related projects that span research and development in the areas of hardware, software and applications. The technical focus will be on network-attached or PCIe-attached FPGA/MPSoC based distributed acceleration Systems, e.g., SmartNIC, Adaptive Network, blockchain, distributed applications on ML/DL/Big Data, etc. Candidates with strong experience in FPGA based RTL design, FPGA based acceleration of cloud applications, and hardware/software co-design should apply. The research intern will gain research and development experience in FPGA based heterogenous computing and distributed system.
Master or Ph.D. student in Computer Engineering, Computer Science, or Electrical Engineering.
Strong Hands-on coding skills, eg., C/C++, Verilog HDL, Python, etc..
Research experience and publications on related areas (e.g., computing system, networking, storage, blockchain, big data, AI, etc.) are preferable.