Dr. Peter Thoman- Assistant Professor

Hi, my name is Peter Thoman and I’m an Assistant Professor at the University of Innsbruck, with the Distributed and Parallel Systems group. My research interests include everything that has to do with achiving high performance on parallel hardware, with a particular focus on GPU computing on one end of the spectrum and fine-grained task parallelism on the other. I’m also very keen on research aiming at improving the programmability/performance tradeoff, including API design as well as compilers and tool support.
This page provides a short overview of my current projects, teaching, and some recent publications, with links to more complete information elsewhere.
Research Interests. GPU Computing, Parallel Runtime Systems, Compilers for HPC

Projects

Celerity - High Level C++ for Accelerator Clusters
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Celerity is a high-level C++ API, closely based on the Khronos SYCL standard, which allows targeting GPU compute clusters rather than just individual GPUs. The only additional requirement compared to a normal SYCL program is providing a functor which maps a kernel’s compute range to its data requirements. In the background, Celerity maintains data residence information, and constructs and optimizes task and command graphs for distributing the work in the cluster.
Insieme Compiler and Runtime System
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In the Insieme project, we explore the possibilities afforded by using a high-level intermediate compiler representation inherently designed for parallelism, INSPIRE. Insieme supports C/C++ source code and several parallelism APIs including OpenMP and Cilk as input, and generates code targeting its high-performance runtime system.
INPACT

Together with our project partner Tofmotion we investigate the potential for parallelization in the field of time-of-flight imaging. This research ranges from high-end GPU-accelerated simulation to realtime- and temperature-constrained on-device processing.

Teaching

Advanced C++

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A graduate-level course on modern, advanced C++. Tries to tie together language theory and background with practical advice for working in large-scale C++ software projects.
Prerequisites: Good understanding of C, familiarity with object-oriented programming.
GPU Computing

[LFU]
An introductory course to GPU computing. Introduces the differences between GPU and CPU hardware, GPU paradigms and APIs, and discusses how several algorithms can be efficiently parallelized on GPUs. Prerequisites: Basic C knowledge.

For more in-depth information about my current courses, please visit the course repository of the University of Innsbruck.

Selected Recent Publications

RTX-RSim: Accelerated Vulkan Room Response Simulation for Time-of-Flight Imaging, IWOCL'20: Proceedings of the International Workshop on OpenCL. Peter Thoman, Markus Wippler, Robert Hranitzky, Thomas Fahringer
The Allscale Framework Architecture, Parallel Computing, Elsevier, May 2020. Herbert Jordan, Philipp Gschwandtner, Peter Thoman, Peter Zangerl, Alexander Hirsch, Thomas Fahringer, Thomas Heller, Dietmar Fey
Celerity: High-Level C++ for Accelerator Clusters, Euro-Par 2019: Parallel Processing.
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Peter Thoman, Philip Salzmann, Biagio Cosenza, Thomas Fahringer
A Taxonomy of Task-based Parallel Programming Technologies for High-performance Computing, The Journal of Supercomputing, Springer, April 2018. Peter Thoman, Kiril Dichev, Thomas Heller, Roman Iakymchuk, Xavier Aguilar, et al.

For a complete list of publications, consult my Google Scholar profile.