Michel Steuwer

Registered user since Fri 31 Mar 2017

Name: Michel Steuwer

Bio: I am a lecturer (assistant professor) in the School of Computing Science at the University of Glasgow in Scotland. I am a member of the the GLAsgow Systems Section (GLASS), the Glasgow Parallelism Group (GPG), an associated member of the Formal Analysis, Theory and Algorithms (FATA) section, and a visiting member of the Compiler and Architecture Design Group (CArD) at the University of Edinburgh.

Before joining Glasgow I was a postdoctoral researcher at the School of Informatics at the University of Edinburgh. I received my PhD from the University of Münster in Germany.

I am interested in all aspects of parallel programming. Particular research interests of mine include performance portability, structured parallel programming, heterogeneous and GPU computing, and novel compilation techniques for high-level languages.

Country: United Kingdom

Affiliation: University of Glasgow

Personal website: http://michel.steuwer.info/

Research interests: Parallel Programming, Structured Parallel Programming, Heterogeneous and GPU Computing, Novel Functional Compilation Techniques

Contributions

LCTES 2019Committee Member in Program Committee within the LCTES 2019-track
Artifact Evaluation Chair in Organizing Committee within the LCTES 2019-track
Committee Member in Artifact Evaluation Committee within the LCTES 2019-track
LCTES 2018Artifact Evaluation Chair in Organizing Committee
Committee Member in Program Committee
MoreVMs 2017Author of OpenCL JIT Compilation for Dynamic Programming Languages within the MoreVMs 2017-track
SYCL 2017Committee Member in Program Committee within the SYCL 2017-track
ICFP 2017Committee Member in Artifact Evaluation Committee within the Research Artifacts-track
VEE 2017Author of Just-In-Time GPU Compilation for Interpreted Languages with Partial Evaluation within the Session 2-track
GPGPU-9Author of Multi-Stage Programming for GPUs in Modern C++ using PACXX within the GPGPU-9-track
Author of Performance Portable GPU Code Generation for Matrix Multiplication within the GPGPU-9-track