About
I am a Principal Researcher in the RiSE group at Microsoft Research,
and an Associate Professor (on leave) at UC Santa Cruz. My research focuses on concurrency: programming,
modeling, testing, and architecture, with the goal of enabling correct and efficient applications on
emerging architectures. I explore these ideas primarily through GPGPU programming.
Previously, I was a postdoc at Princeton with Margaret Martonosi
and received my PhD from Imperial College London advised by Alastair Donaldson.
π’ News
- 2026: Parallel X accepted to SIGCSE 2026!
- 2025: BetterTogether wins Best Paper Award at IISWC 2025!
Agentic Workflows
I am experimenting with agentic workflows. Enjoy!
Did You Know? (daily fact mined from my papers)
Did you know? Traditional simultaneous multithreading (SMT) designs must choose between out-of-order (OoO) threads (for instruction-level parallelism) or in-order (InO) threads (for thread-level parallelism) β but SHADOW is the first CPU architecture to run both kinds of threads concurrently on the same core, dynamically stealing work between them. On memory-bound sparse workloads like those found in deep learning and graph processing, SHADOW achieves up to 3.16Γ speedup and 1.33Γ average improvement over a standard OoO CPU, with only 1% area and power overhead. (from: SHADOW: Simultaneous Multi-Threading Architecture with Asymmetric Threads)
Research Idea (daily idea mined from my papers and related works on arXiv)
Placeholder: check back soon β an agent will populate this with a research idea inspired by my papers and recent arXiv publications.
Publications
All papers are provided in full markdown and summary markdown formats to make them easier for agents and LLMs to process. See the [Markdown Full] and [Markdown Summary] links next to each paper, or browse the combined index.
Papers
2026 (2 papers)
Parallel X: Redesigning of a Parallel Programming Educational Game with Semantic Foundations and Transfer Learning
D. McKee, Z. Lin, B. Fox, J. Li, J. Zhu, M. Seif El-Nasr, T. Sorensen
SIGCSE, 2026
[PDF]
[Markdown Full] [Markdown Summary]
2025 (5 papers)
SafeRace: Assessing and Addressing WebGPU Memory Safety in the Presence of Data Races
R. Levine, A. Lee, N. Abbas, K. Little, T. Sorensen
OOPSLA, 2025
[PDF]
[Markdown Full] [Markdown Summary]
SHADOW: Simultaneous Multi-Threading Architecture with Asymmetric Threads
I. Chaturvedi, B. R. Godala, T. Sorensen, A. Gangavaram, T. M. Aamodt, D. Flyer, D. I. August
MICRO, 2025
[PDF]
[Markdown Full] [Markdown Summary]
PEAK: A Performance Engineering AI-Assistant for GPU Kernels Powered by Natural Language Transformation
M. U. Tariq, A. Jangda, A. Moreira, M. Musuvathi, T. Sorensen
ArXiv, 2025
[PDF]
[Markdown Full] [Markdown Summary]
BetterTogether: An Interference-Aware Framework for Fine-grained Software Pipelining on Heterogeneous SoCs
Y. Xu, R. Sharma, Z. Chen, S. Mistry, T. Sorensen
IISWC, 2025
π Best Paper Award
[PDF]
[Markdown Full] [Markdown Summary]
2024 (3 papers)
GhOST: a GPU Out-of-Order Scheduling Technique for Stall Reduction
I. Chaturvedi, B. R. Godala, Y. Wu, Z. Xu, K. Iliakis, P.-E. Eleftherakis, S. Xydis, D. Soudris, T. Sorensen, S. Campanoni, T. M. Aamodt, D. I. August
ISCA, 2024
[PDF]
[Markdown Full] [Markdown Summary]
Mix Testing: Specifying and Testing ABI Compatibility of C/C++ Atomics Implementations
L. Geeson, J. Brotherston, W. Dijkstra, A. F. Donaldson, L. Smith, T. Sorensen, J. Wickerson
OOPSLA, 2024
[PDF]
[Markdown Full] [Markdown Summary]
2023 (3 papers)
GPUHarbor: Testing GPU Memory Consistency at Large (Experience Paper)
R. Levine, M. Cho, D. McKee, A. Quinn, T. Sorensen
ISSTA, 2023
π Distinguished Artifact Award
[PDF]
[Markdown Full] [Markdown Summary]
MC Mutants: Evaluating and Improving Testing for Memory Consistency Specifications
R. Levine, T. Guo, M. Cho, A. Baker, R. Levien, D. Neto, A. Quinn, T. Sorensen
ASPLOS, 2023
π Distinguished Paper Award, Distinguished Artifact Award
[PDF]
[Markdown Full] [Markdown Summary]
2021 (3 papers)
GraphAttack: Optimizing Data Supply for Graph Applications on In-Order Multicore Architectures
A. Manocha, T. Sorensen, E. Tureci, O. Mathews, J. L. AragΓ³n, M. Martonosi
TACO, 2021
[PDF]
[Markdown Full] [Markdown Summary]
2020 (3 papers)
MosaicSim: A Lightweight, Modular Simulator for Heterogeneous Systems
O. Matthews, A. Manocha, D. Giri, M. Orenes-Vera, E. Tureci, T. Sorensen, T. Ham, J. L. AragΓ³n, L. Carloni, M. Martonosi
ISPASS, 2020
π Best Paper Nomination
[PDF]
[Markdown Full] [Markdown Summary]
2019 (1 paper)
2018 (2 papers)
2017 (2 papers)
2016 (2 papers)
2015 (1 paper)
Workshop Papers
Workshop Papers (5)
A Simulator and Compiler Framework for Agile Hardware-Software Co-design Evaluation and Exploration
T. Sorensen, A. Manocha, E. Tureci, M. Orenes-Vera, J. L. AragΓ³n, M. Martonosi
ICCAD, 2020 (Invited)
[PDF]
[Slides]
[Markdown Full] [Markdown Summary]
Theses
Theses (3)
Device-wide Barrier Synchronisation on Graphics Processing Units
T. Sorensen (Adviser: A. F. Donaldson)
PhD Thesis, Imperial College London, 2018
[PDF]
Testing and Exposing Weak GPU Memory Models
T. Sorensen (Advisers: G. Gopalakrishnan, Z. Rakamaric)
MS Thesis, University of Utah, 2014
[PDF]
Towards Shared Memory Consistency Models for GPUs
T. Sorensen (Adviser: G. Gopalakrishnan)
BS Thesis, University of Utah, 2012
[PDF]
Teaching
I have taught classes at UCSC on compilers and parallel programming.
- CSE 280O-01: Language Systems and Data (LSD) Seminar (co-organized with Lindsey Kuper) -
Fall 2023
- CSE 211: Graduate Compiler Design -
Fall 2023
- CSE 113: Concurrent and Parallel Programming -
Winter 2023
- CSE 110A: Fundamentals of Compiler Design I -
Spring 2023
Alumni
I've had the privilege of working with the following students at UCSC who have gone on to really great things!
- Devon McKee - MS β Samsung
- Sanya Srivastava - MS β PhD student at Duke
- Christian Lei - MS β Microsoft
- Kiefer Selmon - MS β Nvidia
- Mingun Cho - UG β PhD student at UC Davis
- Chris Liu - UG β PhD student at UCLA
- Naomi Rehman - UG β PhD student at UC Santa Barbara
- Sean Siddens - UG β PhD student at University of Washington
- Ananthajit Srikanth - UG β PhD student at EPFL
Acknowledgements
I would like to thank various organizations for supporting my work,
either through employment, contracting, or research funding:
Microsoft, Trail of Bits, NSF, Google, DARPA, and the Khronos Group.