All software
AGILE
AGILE is a GPU-accelerated fork of MPI-AMRVAC, a parallel adaptive mesh refinement framework aimed at solving (primarily hyperbolic) partial differential equations by a number of different numerical schemes. The emphasis is on (near) conservation laws and on shock-dominated problems in particular.
- Fortran
- GPU
- High performance computing
- Fortran
- FPP
- Jupyter Notebook
- + 4
ccglib
The Complex Common GEMM Library (ccglib) provides mixed-precision matrix-matrix multiplication kernels for complex data.
- CUDA
- GPU
- High performance computing
- + 1
- C
- C++
- CMake
- + 3
Compas Toolkit
The Compas Toolkit is a high-performance C++ library offering GPU-accelerated functions for use in quantitative MRI research.
- GPU
- High performance computing
- MRI
- C
- C++
- CMake
- + 4
cudawrappers
The cudawrappers library is a C++ wrapper for the Nvidia C libraries such as the CUDA driver, NVRTC, and cuFFT.
- accelerators
- CUDA
- GPU
- C
- C++
- CMake
- + 2
Eigencuda
Offload Eigen matrix-matrix multiplications to an Nvidia GPU
- GPU
- High performance computing
- C++
- CMake
FLAME GPU
FLAME GPU is a GPU accelerated simulator for domain independent complex systems simulations. FLAME GPU provides a mapping between a simple description of an agent and its interactions into optimised GPU code. The software abstracts the details and complexity of the GPU away from modellers.
- GPU
- High performance computing
- Multi-scale & multi model simulations
- + 2
hipDecomp
hipDecomp is an Adaptive Pencil Decomposition Library for AMD GPUs.
- GPU
- High performance computing
- HIP
- C
- C++
- CMake
- + 3
Kernel Float
C++ Header-only library for CUDA that simplifies working with vector types and reduced precision floating-point arithmetic in GPU code.
- AI
- Big data
- GPU
- + 1
- C
- C++
- CMake
- + 3
KMM
KMM is a lightweight C++ middleware for accelerated computing.
- GPU
- High performance computing
- C++
- CMake
- Cuda
- + 1
PartitionedArrays.jl
This package provides distributed (a.k.a. partitioned) vectors and sparse matrices like the ones needed in distributed finite differences, finite volumes, or finite element computations.
- GPU
- High performance computing
- Julia Package
- Julia
- Shell
prfmodel
A modern Python implementation for population receptive field modelling.
- GPU
- neuroimaging
- Neuroscience
- + 2
- Python
PyTorch Performance Analysis
Lessons on PyTorch Performance Analysis: from Profiling to Optimization
- deep learning
- GPU
- High performance computing
- + 3
- Jupyter Notebook
- Python