6 papers
Benchmarking Large Language Models on Floating-Point Error Classification
Lisa Taldir, Muhammad Ahmad Saeed, David Defour +2
This paper investigates the capability of Large Language Models (LLMs) to detect and classify floating-point errors statically in software code. We introduce InterFLOPBench, a benc…
QMCkl: A Kernel Library for Quantum Monte Carlo Applications
Emiel Slootman, Vijay Gopal Chilkuri, Aurelien Delval +16
Quantum Monte Carlo (QMC) methods deliver highly accurate electronic structure calculations but are computationally intensive. The quantum Monte Carlo kernel library (QMCkl) provid…
Noise Injection for__Performance Bottleneck Analysis
Aurélien Delval, Pablo de Oliveira Castro, William Jalby +1
Bottleneck evaluation plays a crucial part in performance tuning of HPC applications, as it directly influences the search for optimizations and the selection of the best hardware…
Error Analysis of Sum-Product Algorithms under Stochastic Rounding
Pablo de Oliveira Castro, El-Mehdi El Arar, Eric Petit +1
The quality of numerical computations can be measured through their forward error, for which finding good error bounds is challenging in general. For several algorithms and using s…
MLKAPS: Machine Learning and Adaptive Sampling for HPC Kernel Auto-tuning
Mathys Jam, Eric Petit, Pablo de Oliveira Castro +3
Many High-Performance Computing (HPC) libraries rely on decision trees to select the best kernel hyperparameters at runtime,depending on the input and environment. However, finding…
Bounds on non-linear errors for variance computation with stochastic rounding
El-Mehdi El Arar, Devan Sohier, Pablo de Oliveira Castro +1
The main objective of this work is to investigate non-linear errors and pairwise summation using stochastic rounding (SR) in variance computation algorithms. We estimate the forwar…