Gus Henry Smith
gussmith@cs.washington.edu - justg.us
Education
since 2018
Paul G. Allen Center for Computer Science & Engineering
Pursuing Ph.D.; coadvised by Luis Ceze and Zach Tatlock.
2013–2018
The Schreyer Honor’s College
M.S./B.S. in Computer Science and Engineering. Advised by Vijay Narayanan and John Sampson.
Publications
Specialized Accelerators and Compiler Flows: Replacing Accelerator APIs with a Formal Software/Hardware Interface. Arxiv 2022 (link). Bo-Yuan Huang, Steven Lyubomirsky, Yi Li, Mike He, Thierry Tambe, Gus Henry Smith, Akash Gaonkar, Vishal Canumalla, Gu-Yeon Wei, Aarti Gupta, Zachary Tatlock, Sharad Malik.
Pure Tensor Program Rewriting via Access Patterns (Representation Pearl). MAPS 2021. Gus Henry Smith, Andrew Liu, Steven Lyubomirsky, Scott Davidson, Joseph McMahan, Michael Taylor, Luis Ceze, Zachary Tatlock.
From DSLs to Accelerator-Rich Platform Implementations: Addressing the Mapping Gap. LATTE 2021. Bo-Yuan Huang, Steven Lyubomirsky, Thierry Tambe, Yi Li, Mike He, Gus Smith, Gu-Yeon Wei, Aarti Gupta, Sharad Malik, Zachary Tatlock.
Enumerating Hardware-Software Splits with Program Rewriting. YArch 2020. Gus Smith, Zachary Tatlock, Luis Ceze.
A FerroFET-Based In-Memory Processor for Solving Distributed and Iterative Optimizations via Least-Squares Method. IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2019. Insik Yoon, Muya Chang, Kai Ni, Matthew Jerry, Samantak Gangopadhyay, Gus Henry Smith, Tomer Hamam, Justin Romberg, Vijaykrishnan Narayanan, Asif Khan, Suman Datta, Arijit Raychowdhury.
Designing Processing in Memory Architectures via Static Analysis of Real Programs. MS Thesis, 2018.
Computing With Networks of Oscillatory Dynamical Systems. Proceedings of the IEEE, 2018. Arijit Raychowdhury, Abhinav Parihar, Gus Henry Smith, Vijaykrishnan Narayanan, György Csaba, Matthew Jerry, Wolfgang Porod, Suman Datta.
A FeFET Based Processing-In-Memory Architecture for Solving Distributed Least-Square Optimizations. DRC 2018. Insik Yoon, Muya Chang, Kai Ni, Matthew Jerry, Samantak Gangopadhyay, Gus Smith, Tomer Hamam, Vijayakrishan Narayanan, Justin Romberg, Shih-Lien Lu, Suman Datta, Arijit Raychowdhury.
Third Eye: A Shopping Assistant for the Visually Impaired. IEEE Computer, 2017. Peter A Zientara, Sooyeon Lee, Gus H Smith, Rorry Brenner, Laurent Itti, Mary B Rosson, John M Carroll, Kevin M Irick, Vijaykrishnan Narayanan.
Research Projects
since Fall 2021
Lakeroad
UW SAMPL Lab/UW PLSE Lab/Real-time Machine Learning
Automatically synthesizing FPGA dialect implementations from functional descriptions of FPGA resources using solvers (z3 via Rosette). Exploring potential FPGA dialects using program rewriting.
since Winter 2020
UW SAMPL Lab/Real-time Machine Learning
Designing a pure, binder-free intermediate language for optimizing low-level tensor programs via program rewriting. (See Pure Tensor Program Rewriting via Access Patterns.) Using the language to map computations to custom hardware. (See Specialized Accelerators and Compiler Flows: Replacing Accelerator APIs with a Formal Software/Hardware Interface.)
2018–2020
UW SAMPL Lab
Enabled the exploration of new, nontraditional datatypes (i.e., alternatives to IEEE 754 floating point) with an extension to TVM, a deep learning compiler. My qualifying exam project for my Ph.D.
2017–2018
Static Analysis for Processing in Memory Accelerator Design
PSU Microsystems Design Lab
Given a model of accelerating computation using processing in memory, used LLVM to detect potentially offloadable code sections within workloads. My master’s research.
2014–2018
ThirdEye: Shopping Assistant for the Visually Impaired
PSU Microsystems Design Lab
Built a wearable system to assist the visually impaired in shopping. My undergraduate research.
Industry Experience
Fall 2021–Spring 2022
Student Researcher
Continuing my previous work on an auto-formatter for sparse tensor kernels.
Summer 2021
Software Engineering Intern, MLIR
Designing an auto-formatter for sparse tensor kernels; contributing to the MLIR sparse tensor dialect.
Summer 2019
Microsoft
Research Intern, AI and Advanced Architectures
Statically analyzed deep learning workloads to inform architecture design.
Summer 2018
Software Engineering Intern, Fuchsia
Implemented the RFCOMM protocol for one of Google’s OSes, Fuchsia.
Summer 2017
Software Engineering Intern, Chrome
Helped the Chrome Remote Desktop team identify and implement optimizations for embedded devices such as the Raspberry Pi.
Summer 2016
Software Engineering Intern, Android Internal Tools
Contributed to Java-based Android profiling tools.
Service
- LATTE 2022 Reviewer
- SIGPLAN-M Mentor
- POPL 2021 Artifact Evaluator
- ASPLOS 2020 Artifact Evaluator