216 citations · 239 across the 5 of their papers we have counts for
6 papers
Equality Saturation for Optimizing High-Level Julia IR
Jules Merckx, Tim Besard, Bjorn De Sutter
Compilers are indispensable for transforming code written in high-level languages into performant machine code, but their general-purpose optimizations sometimes fall short. Domain…
Automated Translation and Accelerated Solving of Differential Equations on Multiple GPU Platforms
Utkarsh Utkarsh, Valentin Churavy, Yingbo Ma +8
We demonstrate a high-performance vendor-agnostic method for massively parallel solving of ensembles of ordinary differential equations (ODEs) and stochastic differential equations…
Flexible Performant GEMM Kernels on GPUs
Thomas Faingnaert, Tim Besard, Bjorn De Sutter
General Matrix Multiplication or GEMM kernels take centre place in high performance computing and machine learning. Recent NVIDIA GPUs include GEMM accelerators, such as NVIDIA's T…
Dynamic Automatic Differentiation of GPU Broadcast Kernels
Jarrett Revels, Tim Besard, Valentin Churavy +2
We show how forward-mode automatic differentiation (AD) can be employed within larger reverse-mode computations to dynamically differentiate broadcast operations in a GPU-friendly…
Effective Extensible Programming: Unleashing Julia on GPUs
Tim Besard, Christophe Foket, Bjorn De Sutter
GPUs and other accelerators are popular devices for accelerating compute-intensive, parallelizable applications. However, programming these devices is a difficult task. Writing eff…
High-level GPU programming in Julia
Tim Besard, Pieter Verstraete, Bjorn De Sutter
GPUs are popular devices for accelerating scientific calculations. However, as GPU code is usually written in low-level languages, it breaks the abstractions of high-level language…