1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.DC2026
Mind the Gap: The Disconnect Between Synthetic and Natural Edge Weights in Parallel Single-Source Shortest Path
Marco D'Antonio, Thai Son Mai, Hans Vandierendonck
Scientific research works often evaluate Parallel Single-Source Shortest Path (SSSP) algorithms using synthetic, uniformly distributed edge weights. However, real-world graphs exhi…
cs.DS2025
Less is More: Faster Maximum Clique Search by Work-Avoidance
Hans Vandierendonck
The maximum clique (MC) problem is a challenging graph mining problem which, due to its NP-hard nature, can take a substantial amount of execution time. The MC problem is dominated…
cs.AR2025★ 1 cited
MARVEL: An End-to-End Framework for Generating Model-Class Aware Custom RISC-V Extensions for Lightweight AI
Ajay Kumar M, Cian O'Mahoney, Pedro Kreutz Werle +5
Deploying deep neural networks (DNNs) on resource-constrained IoT devices remains a challenging problem, often requiring hardware modifications tailored to individual AI models. Ex…