I am a Member of Technical Staff at AMD Research. I received my PhD in computer science at the University of Washington. At UW, I was part of the architecture group and was advised by Mark Oskin.

I am interested in understanding and improving the performance of complex architectures. During graduate school, I focused on making complex architectures easier to program while maintaining high performance. I have worked on code generation targetting various parallel architectures and have created methodologies and built tools to better understand the behavior and performance of GPUs. My thesis work focused on generating code for graph applications on a manycore architecture that utilizes high bandwidth memory.

More information: curriculum vitae, email


Taming the Zoo: The Unified GraphIt Compiler Framework for Novel Architectures.
Ajay Brahmakshatriya, Emily Furst, Victor Ying, Claire Hsu, Changwan Hong, Max Ruttenberg, Yunming Zhang, Dai Cheol Jung, Dustin Richmond, Michael Taylor, Julian Shun, Mark Oskin, Daniel Sanchez, Saman Amarasinghe.
In Intl. Symposium on Computer Architecture (ISCA) (2021).
paper (pdf), bibtex

Profiling A GPU Database Implementation.
Emily Furst, Mark Oskin, Bill Howe.
In DaMoN (2017).
paper (pdf), bibtex

Parallelizing Instance-Based Data Classifiers.
Imad Rahal, Emily Furst, Ramzi Haraty.
In Intl. Florida Artificial Intelligence Research Society Conference (FLAIRS) (2016).