3 papers
cs.PL2026
Enhancing the Power of Polyhedral-Based Optimizations with Coordinate-Based Hill Climbing
Gaurav Verma, Michael Canesche, Fernando Magno Quintão Pereira
This paper describes our experience extending the polyhedral compiler Pluto with a lightweight, coordinate-wise hill-climbing tuner that adjusts numeric transformation parameters,…
cs.LG2024
Explore as a Storm, Exploit as a Raindrop: On the Benefit of Fine-Tuning Kernel Schedulers with Coordinate Descent
Michael Canesche, Gaurav Verma, Fernando Magno Quintao Pereira
Machine-learning models consist of kernels, which are algorithms applying operations on tensors -- data indexed by a linear combination of natural numbers. Examples of kernels incl…
cs.DL2023
Preparing Reproducible Scientific Artifacts using Docker
Michael Canesche, Roland Leissa, Fernando Magno Quintão Pereira
The pursuit of scientific knowledge strongly depends on the ability to reproduce and validate research results. It is a well-known fact that the scientific community faces challeng…