New developments in PySDM and PySDM-examples v2
New developments in PySDM and PySDM-examples v2: collisional breakup, immersion freezing, dry aerosol initialization, and adaptive time-stepping - Published in JOSS (2023)
prysm
prysm: A Python optics module - Published in JOSS (2019)
PetIBM
PetIBM: toolbox and applications of the immersed-boundary method on distributed-memory architectures - Published in JOSS (2018)
Disimpy
Disimpy: A massively parallel Monte Carlo simulator for generating diffusion-weighted MRI data in Python - Published in JOSS (2020)
fluidx3d
The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs and CPUs via OpenCL. Free for non-commercial use.
scimlbook
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
montecarlomeasurements.jl
Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
https://github.com/cans-world/cans
A code for fast, massively-parallel direct numerical simulations (DNS) of canonical flows
opencl-benchmark
A small OpenCL benchmark program to measure peak GPU/CPU performance.
pararealgpu.jl
A distributed and GPU-based implementation of the Parareal algorithm for parallel-in-time integration of equations of motion.
https://github.com/google/tf-quant-finance
High-performance TensorFlow library for quantitative finance.
https://github.com/conradsnicta/bandicoot-code
Bandicoot: C++ library for GPU linear algebra & scientific computing - https://coot.sourceforge.io
cudawrappers
C++ wrapper for the Nvidia/HIP C libraries (e.g. CUDA driver, nvrtc, hiprtc, cuFFT, hipFFT, etc.)
predictive-analytics
A self-driven exploratory report on predictive data analytics employing a range of machine learning techniques
dplasma
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.
https://github.com/beehive-lab/docker-tornadovm
Docker build scripts for TornadoVM on GPUs: https://github.com/beehive-lab/TornadoVM
https://github.com/cair/fast-tsetlin-machine-in-cuda-with-imdb-demo
A CUDA implementation of the Tsetlin Machine based on bitwise operators
reproducible-research-with-gpu-jupyter
This repository demonstrates how to use GPU-Jupyter for reproducible deep learning research with minimal setup effort..
Ginkgo
Ginkgo: A high performance numerical linear algebra library - Published in JOSS (2020)
https://github.com/cea-metrocarac/pyvsnr
A Python library for computing the VSNR in 2D images. It provides both CPU and GPU implementations.
parsec
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.
https://github.com/beehive-lab/tornadovm
TornadoVM: A practical and efficient heterogeneous programming framework for managed languages
babelviscofdtd
Software library for FDTD of viscoelastic equation using a staggered grid arrangement with support for GPU and CPU backends
https://github.com/cluebbers/using_r_for_hpda
Exploring R for high-performance data analytics, including memory management, GPU computing, parallel processing, benchmarks, case studies, and comparisons with Python.