2016 ~ Present

Parallel Hardware Applications in Science and Technology (PHAST)

Goals

Recent advances in VLSI technology are enabling fast computing systems with tens and hundreds of processing units. These range from field programmable gate arrays (FPGA) to graphics processing units (GPU) to multi-core processors, such as the Intel Xeon Phi. These parallel systems can be used to accelerate applications in wireless communications, image processing, and data science. Current projects focus on signal processing algorithms for 5G base stations for large scale or Massive MIMO wireless communications systems. Parallel programming environments and software tools such as CUDA, OpenMP, OpenCL, and MPI are used on systems from mobile GPU system-on-chip devices (SoCs), to high performance desktop GPUs to supercomputers at the Texas Advanced Computing Center.

Issues Involved or Addressed

Parallel hardware, decentralized algorithms, GPU clusters. Applications include massive multi-user multiple-input multiple output (MUMIMO) antenna arrays.

Methods and Technologies

  • GPU programming
  • FPGA programming
  • Parallel programming
  • Massive MIMO wireless

Academic Majors of Interest

  • Electrical and Computer Engineering
  • Computer Science
  • Computational and Applied Mathematics

Preferred Interests and Preparation

Basic coursework in computer engineering.
Interest in parallel programming.
Circuits, MATLAB, and Verilog experience helpful.