artiq VS hpipm

Compare artiq vs hpipm and see what are their differences.

artiq

A leading-edge control system for quantum information experiments (by m-labs)

hpipm

High-performance interior-point-method QP and QCQP solvers (by giaf)
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artiq hpipm
2 2
403 473
1.0% -
9.6 7.7
7 days ago about 1 month ago
Python C
GNU Lesser General Public License v3.0 only GNU General Public License v3.0 or later
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.

artiq

Posts with mentions or reviews of artiq. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-06.

hpipm

Posts with mentions or reviews of hpipm. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-17.

What are some alternatives?

When comparing artiq and hpipm you can also consider the following projects:

quantumcat - quantumcat is a platform-independent, open-source, high-level quantum computing library, which allows the quantum community to focus on developing platform-independent quantum applications without much effort.

blasfeo - Basic linear algebra subroutines for embedded optimization

py2many - Transpiler of Python to many other languages

OpenBLAS - OpenBLAS is an optimized BLAS library based on GotoBLAS2 1.13 BSD version.

acados - Fast and embedded solvers for nonlinear optimal control

Octavian.jl - Multi-threaded BLAS-like library that provides pure Julia matrix multiplication

PhysAI - PhysAI is an open-source AI project that aims to link quantum mechanics and general relativity by generating, testing, and improving physical equations. It leverages machine learning, integrates with existing research, generates LaTeX documents, and encourages collaborative learning. It relies on community-driven contributions to improve accuracy.

StaticCompiler.jl - Compiles Julia code to a standalone library (experimental)

cqasm_development_interface - Framework for writing and running cQASM files against any Quantum Inspire's emulator backend via their API

prometeo - An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing