email: wysem at cs dot washington dot edu
I am a Ph.D. student in the Paul G. Allen School of Computer Science & Engineering at the University of Washington. I am a member of the Sampa group and am advised by Mark Oskin. My research is in the field of computer architecture, and my specfic interests include open-source processor design, hardware specialization, and GPU architecture. I also enjoy teaching and was the instructor for CSE 351: The Hardware/Software Interface during the Winter 2018 quarter.
I spent all of 2017 on leave from UW CSE, working as a Post-Grad Scholar at AMD Research. My work at AMD focused on GPU architecture and microarchitecture optimizations for accelerating GPGPU applications.
I received my M.S. Computer Science and Engineering and B.S. Computer Engineering from the Dept. of Computer Science & Engineering at the University of Washington in December 2015 and June 2014, respectively.
My (hopefully, but often not, up-to-date) CV can be found here.
My research interests are in the field of computer architecture and revolve around (a) general purpose parallel computing (e.g., GPGPU-styled architectures), (b) open-source hardware design, and (c) hardware specialization. In the context of GPGPU architecutre, I am interested in the problem of memory divergence, or more generally efficient gather and scatter operations in parallel computing architectures. I am also interested in evaluating and re-architecting data parallel compute architectures in the context of scientific applications and the use of specialized accelerators within heterogeneous architectures and systems. In the scope of open-source hardware design, I am working on the design of a fully open-source, in-order RISC-V processor implementation. Accelerating the adoption of open-source hardware requires not only an open ISA, but also open-source implementations that can be easily taken from RTL to tapeout.
Aside from technical research, I also have interests related to computer engineering education and curricula. As the underlying technology of computing systems changes, how should that change the curriculum we provide and teach?
My past research has spanned a variety of topics, including data processing for novel DNA sequencing technology, modeling approximate computing techniques (see REACT), and the evaluation and comparison of a neural network accelerator on reconfigurable hardware using high level synthesis (see SNNAP).