Stars
Precisely measure energy consumption of specific functions in x86-64 binaries
This repository contains slides from the MS177: Sustainable Computing with the Help of Tools, Mixed-Precision, and Optimistic Error Estimates at SIAM CSE 2023, Amsterdam, The Netherlands
A tool for debugging and assessing floating point precision and reproducibility.
Error-Free Transformations as building blocks for compensated algorithms
MLKAPS: Machine Learning for Kernel Accuracy and Performance Studies
Une extension pour navigateur qui permet de lire les articles de presse en ligne sur le compte de bibliothèques ayant souscrit à europresse
Stochastic Arithmetic to diagnose Floating-Point problems in Julia
A fuzzy ecosystem for evaluating the stability of your computational tools.
amc2moodle, is an automatic tool to convert multiple choice quiz between auto-muliple-choice LaTeX format and moodle XML format.
IRVM: A Virtual Machine for Andrew W. Appel's Tree Intermediate Representation
MPIre is a library to replay a single rank in an MPI application. But don't forget MPIre strikes back !
NAS Parallel Benchmarks 3.0 OpenMP C version
Configuration for http://llvm-jenkins.debian.net/
A community-driven Emacs distribution - The best editor is neither Emacs nor Vim, it's Emacs *and* Vim!
Coinorama, monitor of Bitcoin markets, network and blockchain
The Monte Carlo Arihmetic Library - A tool for automated rounding error analysis of floating point software
Adaptive Sampling Kit: Adaptive Sampling Kit (ASK) is a toolkit for sampling big experimental spaces.
clang with OpenMP 3.1 and some elements of OpenMP 4.0 support
organix / pijFORTHos
Forked from M2IHP13-admin/JonesForth-armA bare-metal FORTH operating system for Raspberry Pi
A tool that automatically formats Python code to conform to the PEP 8 style guide.
A parser for Google Scholar, written in Python
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)