MATDaemon.jl VS pyhpc-benchmarks

Compare MATDaemon.jl vs pyhpc-benchmarks and see what are their differences.

pyhpc-benchmarks

A suite of benchmarks for CPU and GPU performance of the most popular high-performance libraries for Python :rocket: (by dionhaefner)
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MATDaemon.jl pyhpc-benchmarks
2 6
24 301
- -
5.6 3.2
2 months ago 4 months ago
Julia Python
MIT License The Unlicense
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.

MATDaemon.jl

Posts with mentions or reviews of MATDaemon.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-08.

pyhpc-benchmarks

Posts with mentions or reviews of pyhpc-benchmarks. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-05.

What are some alternatives?

When comparing MATDaemon.jl and pyhpc-benchmarks you can also consider the following projects:

Oceananigans.jl - 🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs

tf-quant-finance - High-performance TensorFlow library for quantitative finance.

XLA.jl - "Maybe we have our own magic."

pyopencl - OpenCL integration for Python, plus shiny features

Mex.jl - Embedding Julia in the MATLAB process.

sqloxide - Python bindings for sqlparser-rs

julia - The Julia Programming Language

3d-ken-burns - an implementation of 3D Ken Burns Effect from a Single Image using PyTorch

XLA.jl - Julia on TPUs

PSyclone - Domain-specific compiler and code transformation system for Finite Difference/Volume/Element Earth-system models in Fortran

torchquad - Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX