# Nicolas Renaud

## Kernel Tuner

Kernel Tuner greatly simplifies the development of highly-optimized and auto-tuned CUDA, OpenCL, and C code, supporting many advanced use-cases and optimization strategies that speed up the auto-tuning process.

- Big data
- GPU
- High performance computing
- + 3

- Python

## DeepRank

Deep learning framework for data mining protein-protein interactions using CNN

- Big data
- Machine learning
- Optimized data handling

- Python
- R
- C
- + 2

## DeepRank GNN

DeepRank-GNN is the graph neural network of our DeepRank package. DeepRank GNN allows to train graph neural networks to classify protein-protein interface

- Python

## iScore

A framework and predictor based on support vector machine and random walk graph kernel for scoring protein-protein interfaces.

- Big data
- Machine learning

- Python
- Cuda
- Makefile
- + 1

## pdb2sql

Fast and versatile Python package that leverages SQL queries to parse, manipulate and process biomolecular structure files. The structure files should be in the PDB format and are available on www.rcsb.org.

- Big data
- Optimized data handling

- Python
- TeX
- Makefile

## MPET

This software is designed to run simulations of batteries with porous electrodes using porous electrode theory, which is a volume-averaged, multiscale approach to capture the coupled behavior of electrolyte and active material within electrodes

- Python

## HPGEM

hpGEM is a C++ partial differential equation solver. It is intended for Discontinuous Galerkin Finite Element Methods, but can also do normal (conforming) Finite Element Methods and Finite Volume.

- Finite Element
- High performance computing

- C++
- CMake
- TeX
- + 6

## QMCBlip

QMCBlip allows to couple Quantum Monte Carlo Simulations with Machine Learning Force Fields to accelerate Molecular Dynamics simulations

- Python

## Davidson diagonalization in Fortran

This package contains a Modern Fortran implementation of the Davidson diagonalization algorithms to compute several eigenvalue-eigenvector pairs of a symmetric matrix

- High performance computing

- Fortran
- CMake
- Python

## Eigencuda

Offload Eigen matrix-matrix multiplications to an Nvidia GPU

- GPU
- High performance computing

- C++
- CMake

## QMCTorch

Use and design neural network ansatz wave function for real-space quantum Monte Carlo simulations of molecular systems.

- Computational Chemistry
- GPU
- High performance computing
- + 2

- Python
- TeX

## Ceiba

Ceiba and its command-line interface Ceiba-cli solve the problem of computing, storing, and securely sharing computationally expensive simulation results.

- Optimized data handling

- Python
- TeX
- Shell
- + 1