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alpaka

The alpaka library is a header-only C++17 abstraction framework designed for computing accelerator development. It enables developers to implement algorithms once and execute them across a range of platforms, including x86, ARM, and RISC-V CPUs, as well as accelerators from NVIDIA, AMD, and Intel.

C++
CPU
CUDA
+ 7

C++
CMake
Shell
+ 2

ISAAC

In Situ Animation of Accelerated Computations

C++
CUDA
Data Visualization
+ 4

C++
HTML
JavaScript
+ 3

PIConGPU

PIConGPU is a relativistic Particle-in-Cell code running on graphic processing units as well as regular multi-core processors. It is Open Source und is freely available for download. It can be used to study plasmas with relativistic dynamics, solving the Maxwell-Vlasov system of equations.

CPU
GPU
heterogeneous computing
+ 3

C++
Python
Shell
+ 5

LLAMA

LLAMA is a cross-platform C++17/C++20 header-only template library for the abstraction of data layout and memory access. It separates the view of the algorithm on the memory and the real data layout in the background.

C++
heterogeneous computing
High performance computing
+ 3

C++
CMake
Shell

cupla

cupla is a simple user interface for the platform-independent parallel kernel acceleration library alpaka. It follows a similar concept as the NVIDIA® CUDA® API by providing a software layer to manage accelerator devices. alpaka is used as a backend for cupla.

C++
heterogeneous computing
High performance computing
+ 3

C++
CMake
Shell
+ 5

mallocMC

This project provides a framework for fast memory managers on many core accelerators. It is based on alpaka to run on many different accelerators and implements the ScatterAlloc algorithm.

CUDA
heterogeneous computing
High performance computing
+ 2

C++
CMake
Shell
+ 4