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Christophe Dubach

Associate Academic Member
Associate Professor, McGill University, Canada CIFAR AI Chair

Christophe Dubach is an Associate Professor jointly appointed in the department of Electrical and Computer (ECE) and the school of Computer Science (CS) at McGill University (starting January 2020). Prior to that, he was a Reader (Associate Professor) at the University of Edinburgh.

His research interests include data-parallel language design and implementation, high-level code generation and optimisation for parallel hardware (e.g. GPU, FPGAs), architecture design space exploration, and the use of machine-learning techniques applied to all these topics.



SparseAdapt: Runtime Control for Sparse Linear Algebra on a Reconfigurable Accelerator
Subhankar Pal, Aporva Amarnath, Siying Feng, Michael O'Boyle, Ronald Dreslinski and Christophe Dubach
MICRO 2021
GPU acceleration of finite state machine input execution: Improving scale and performance
Vanya Yaneva, Ajitha Rajan and Christophe Dubach
Software Testing, Verification & Reliability


Generating high performance code for irregular data structures using dependent types
Federico Pizzuti, Michel Steuwer and Christophe Dubach
Proceedings of the 9th ACM SIGPLAN International Workshop on Functional High-Performance and Numerical Computing


Code Generation for Room Acoustics Simulations with Complex Boundary Conditions
Larisa Stoltzfus, Brian Hamilton, Michel Steuwer, Lu Li and Christophe Dubach
IPDPS 2021


Fast Optimisation of Convolutional Neural Network Inference using System Performance Models
Rik Mulder, Valentin Radu and Christophe Dubach


Central Bank Digital Currency with Asymmetric Privacy
Katrin Tinn and Christophe Dubach
Social Science Research Network


DelayRepay: delayed execution for kernel fusion in Python
John Magnus Morton, Kuba Kaszyk, Lu Li, Jiawen Sun, Christophe Dubach, Michel Steuwer, Murray Cole and Michael F. P. O'Boyle
DLS 2020


Optimising the Performance of Convolutional Neural Networks across Computing Systems using Transfer Learning.
Rik Mulder, Valentin Radu and Christophe Dubach
arXiv preprint arXiv:2010.10621


Binary Ostensibly‐Implicit Trees for Fast Collision Detection
Floyd M. Chitalu, Christophe Dubach and Taku Komura


Automatic generation of specialized direct convolutions for mobile GPUs
Naums Mogers, Valentin Radu, Lu Li, Jack Turner, Michael O'Boyle and Christophe Dubach
PPOPP 2020
High-level hardware feature extraction for GPU performance prediction of stencils
Toomas Remmelg, Bastian Hagedorn, Lu Li, Michel Steuwer, Sergei Gorlatch and Christophe Dubach
PPOPP 2020
Generating fast sparse matrix vector multiplication from a high level generic functional IR
Federico Pizzuti, Michel Steuwer and Christophe Dubach
CC 2020
Replication Packager for 'Generating Fast Sparse Matrix Vector Multiplicationfrom a High Level Generic Functional IR'
Federico Pizzuti, Michel Steuwer and Christophe Dubach
Artifact Digital Object Group


Tiling Optimizations for Stencil Computations Using Rewrite Rules in Lift
Larisa Stoltzfus, Bastian Hagedorn, Michel Steuwer, Sergei Gorlatch and Christophe Dubach
ACM Transactions on Architecture and Code Optimization

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