arbor VS ginkgo

Compare arbor vs ginkgo and see what are their differences.

arbor

The Arbor multi-compartment neural network simulation library. (by arbor-sim)
neuroscience HPC Cuda GPU Mpi modern-cpp Hip
Source Code
arbor-sim.org
Suggest alternative
Edit details

ginkgo

Numerical linear algebra software package (by ginkgo-project)
Linear Algebra HPC gpu-computing Cuda krylov-methods preconditioning sparse-linear-systems spmv Hip Oneapi Dpcpp Openmp
Source Code
ginkgo-project.github.io
Suggest alternative
Edit details
InfluxDB
Our great sponsors
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • WorkOS - The modern identity platform for B2B SaaS
  • SaaSHub - Software Alternatives and Reviews
Our great sponsors
arbor ginkgo
2 2
101 373
1.0% 3.2%
8.1 9.8
12 days ago about 15 hours ago
C++ C++
BSD 3-clause "New" or "Revised" License BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

arbor

Posts with mentions or reviews of arbor. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-17.

ginkgo

Posts with mentions or reviews of ginkgo. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-26.
  • AMD HIP + Cuda in same program
    3 projects | /r/CUDA | 26 Aug 2022
  • Incorporating abidiff into CI?
    1 project | /r/cpp | 28 Nov 2021
    I had exactly the same thought after watching the video (though I wanted to do this for a while anyways) and did exactly that :) I found it interesting to see how different changes impact the ABI of our library, even though we don't promise ABI compatibility or anything. We add the head of the diff part to a PR comment, and store everything else as a build artifact. See the corresponding PR here: https://github.com/ginkgo-project/ginkgo/pull/922

What are some alternatives?

When comparing arbor and ginkgo you can also consider the following projects:

alpaka - Abstraction Library for Parallel Kernel Acceleration :llama:

HIP - HIP: C++ Heterogeneous-Compute Interface for Portability

HPCInfo - Information about many aspects of high-performance computing. Wiki content moved to ~/docs.

AdaptiveCpp - Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!

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

ArrayFire - ArrayFire: a general purpose GPU library.

stdgpu - stdgpu: Efficient STL-like Data Structures on the GPU

mixbench - A GPU benchmark tool for evaluating GPUs and CPUs on mixed operational intensity kernels (CUDA, OpenCL, HIP, SYCL, OpenMP)

Halide - a language for fast, portable data-parallel computation

arbor vs alpaka ginkgo vs HIP arbor vs HPCInfo ginkgo vs alpaka arbor vs AdaptiveCpp ginkgo vs MatX arbor vs ArrayFire ginkgo vs stdgpu arbor vs stdgpu ginkgo vs AdaptiveCpp arbor vs mixbench ginkgo vs Halide