Scientific Software
Updated 6 months ago

New developments in PySDM and PySDM-examples v2 — Peer-reviewed • Rank 18.2 • Science 95%

New developments in PySDM and PySDM-examples v2: collisional breakup, immersion freezing, dry aerosol initialization, and adaptive time-stepping - Published in JOSS (2023)

Scientific Software
Updated 6 months ago

prysm — Peer-reviewed • Rank 14.2 • Science 95%

prysm: A Python optics module - Published in JOSS (2019)

Scientific Software
Updated 6 months ago

PetIBM — Peer-reviewed • Rank 6.5 • Science 95%

PetIBM: toolbox and applications of the immersed-boundary method on distributed-memory architectures - Published in JOSS (2018)

Scientific Software
Updated 6 months ago

Disimpy — Peer-reviewed • Rank 7.5 • Science 93%

Disimpy: A massively parallel Monte Carlo simulator for generating diffusion-weighted MRI data in Python - Published in JOSS (2020)

Mathematics
Scientific Software · Peer-reviewed
Updated 6 months ago

ExaAdmm • Rank 6.1 • Science 64%

Julia implementation of ADMM solver on multiple GPUs

Updated 6 months ago

cunessie.jl • Rank 0.7 • Science 57%

CUDA-accelerated Nonlocal Electrostatics in Structured Solvents

Updated 6 months ago

matx • Rank 10.7 • Science 44%

An efficient C++17 GPU numerical computing library with Python-like syntax

Updated 6 months ago

opencl-benchmark • Rank 5.5 • Science 44%

A small OpenCL benchmark program to measure peak GPU/CPU performance.

Updated 6 months ago

cudawrappers • Science 54%

C++ wrapper for the Nvidia/HIP C libraries (e.g. CUDA driver, nvrtc, hiprtc, cuFFT, hipFFT, etc.)

Updated 6 months ago

predictive-analytics • Science 44%

A self-driven exploratory report on predictive data analytics employing a range of machine learning techniques

Updated 6 months ago

dplasma • Science 57%

DPLASMA is a highly optimized, accelerator-aware, implementation of a dense linear algebra package for distributed heterogeneous systems. It is designed to deliver sustained performance for distributed systems where each node featuring multiple sockets of multicore processors, and if available, accelerators, using the PaRSEC runtime as a backend.

Updated 5 months ago

https://github.com/beehive-lab/docker-tornadovm • Science 26%

Docker build scripts for TornadoVM on GPUs: https://github.com/beehive-lab/TornadoVM

Updated 6 months ago

eigencuda • Science 49%

Offload Eigen operations to GPUs

Updated 6 months ago

reproducible-research-with-gpu-jupyter • Science 67%

This repository demonstrates how to use GPU-Jupyter for reproducible deep learning research with minimal setup effort..

Scientific Software
Updated 6 months ago

Ginkgo — Peer-reviewed • Science 100%

Ginkgo: A high performance numerical linear algebra library - Published in JOSS (2020)

Updated 5 months ago

https://github.com/cea-metrocarac/pyvsnr • Science 26%

A Python library for computing the VSNR in 2D images. It provides both CPU and GPU implementations.

Updated 6 months ago

parsec • Science 44%

PaRSEC is a generic framework for architecture aware scheduling and management of micro-tasks on distributed, GPU accelerated, many-core heterogeneous architectures. PaRSEC assigns computation threads to the cores, GPU accelerators, overlaps communications and computations and uses a dynamic, fully-distributed scheduler based on architectural features such as NUMA nodes and algorithmic features such as data reuse.

Updated 5 months ago

https://github.com/beehive-lab/tornadovm • Science 67%

TornadoVM: A practical and efficient heterogeneous programming framework for managed languages

Updated 6 months ago

latentrees • Science 44%

Latent variable hierarchical model

Updated 6 months ago

plus • Science 54%

More versatile and extensible GPU-accelerated micromagnetic simulator

Updated 6 months ago

babelviscofdtd • Science 39%

Software library for FDTD of viscoelastic equation using a staggered grid arrangement with support for GPU and CPU backends

Updated 5 months ago

https://github.com/cluebbers/using_r_for_hpda • Science 13%

Exploring R for high-performance data analytics, including memory management, GPU computing, parallel processing, benchmarks, case studies, and comparisons with Python.