3 citations · 4 across the 6 of their papers we have counts for
7 papers
Constraint-aware Optimization in Auto-Tuning
Floris-Jan Willemsen, Stijn Heldens, Rob V. van Nieuwpoort +1
Automatic performance tuning, or auto-tuning, is a key technique in high-performance computing, enabling applications to adapt to complex and evolving hardware architectures. A cen…
Bringing Auto-tuning to HIP: Analysis of Tuning Impact and Difficulty on AMD and Nvidia GPUs
Milo Lurati, Stijn Heldens, Alessio Sclocco +1
Many studies have focused on developing and improving auto-tuning algorithms for Nvidia Graphics Processing Units (GPUs), but the effectiveness and efficiency of these approaches o…
Kernel Launcher: C++ Library for Optimal-Performance Portable CUDA Applications
Stijn Heldens, Ben van Werkhoven
Graphic Processing Units (GPUs) have become ubiquitous in scientific computing. However, writing efficient GPU kernels can be challenging due to the need for careful code tuning. T…
Lightning: Scaling the GPU Programming Model Beyond a Single GPU
Stijn Heldens, Pieter Hijma, Ben van Werkhoven +2
The GPU programming model is primarily aimed at the development of applications that run one GPU. However, this limits the scalability of GPU code to the capabilities of a single G…
The LDBC Graphalytics Benchmark
Alexandru Iosup, Ahmed Musaafir, Alexandru Uta +15
In this document, we describe LDBC Graphalytics, an industrial-grade benchmark for graph analysis platforms. The main goal of Graphalytics is to enable the fair and objective compa…
Rocket: Efficient and Scalable All-Pairs Computations on Heterogeneous Platforms
Stijn Heldens, Pieter Hijma, Ben van Werkhoven +3
All-pairs compute problems apply a user-defined function to each combination of two items of a given data set. Although these problems present an abundance of parallelism, data reu…