All Projects → sympiler → Nasoq

sympiler / Nasoq

Licence: mit
NASOQ:Numerically Accurate Sparsity Oriented QP Solver

Projects that are alternatives of or similar to Nasoq

Blis
BLAS-like Library Instantiation Software Framework
Stars: ✭ 859 (+2763.33%)
Mutual labels:  linear-algebra, high-performance-computing
Simpeg
Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.
Stars: ✭ 283 (+843.33%)
Mutual labels:  linear-algebra, scientific-computing
Cpp-Examples
Numerical C++ examples.
Stars: ✭ 38 (+26.67%)
Mutual labels:  linear-algebra, scientific-computing
sympiler
Sympiler is a Code Generator for Transforming Sparse Matrix Codes
Stars: ✭ 32 (+6.67%)
Mutual labels:  linear-algebra, high-performance-computing
Mfem
Lightweight, general, scalable C++ library for finite element methods
Stars: ✭ 667 (+2123.33%)
Mutual labels:  scientific-computing, high-performance-computing
hicma
HiCMA: Hierarchical Computations on Manycore Architectures
Stars: ✭ 21 (-30%)
Mutual labels:  linear-algebra, high-performance-computing
brax
Massively parallel rigidbody physics simulation on accelerator hardware.
Stars: ✭ 1,208 (+3926.67%)
Mutual labels:  robotics, physics-simulation
linnea
Linnea is an experimental tool for the automatic generation of optimized code for linear algebra problems.
Stars: ✭ 60 (+100%)
Mutual labels:  linear-algebra, high-performance-computing
Vectorious
Linear algebra in TypeScript.
Stars: ✭ 616 (+1953.33%)
Mutual labels:  linear-algebra, high-performance-computing
Robosuite
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
Stars: ✭ 462 (+1440%)
Mutual labels:  robotics, physics-simulation
Tensor
A library and extension that provides objects for scientific computing in PHP.
Stars: ✭ 146 (+386.67%)
Mutual labels:  linear-algebra, scientific-computing
Edge
Extreme-scale Discontinuous Galerkin Environment (EDGE)
Stars: ✭ 18 (-40%)
Mutual labels:  scientific-computing, high-performance-computing
bandicoot-code
Bandicoot: GPU accelerator add-on for the Armadillo C++ linear algebra library
Stars: ✭ 21 (-30%)
Mutual labels:  linear-algebra, scientific-computing
ign-math
General purpose math library for robot applications.
Stars: ✭ 35 (+16.67%)
Mutual labels:  robotics, linear-algebra
Julia-data-science
Data science and numerical computing with Julia
Stars: ✭ 54 (+80%)
Mutual labels:  linear-algebra, scientific-computing
monolish
monolish: MONOlithic LInear equation Solvers for Highly-parallel architecture
Stars: ✭ 166 (+453.33%)
Mutual labels:  linear-algebra, scientific-computing
Assistive Gym
Assistive Gym, a physics-based simulation framework for physical human-robot interaction and robotic assistance.
Stars: ✭ 150 (+400%)
Mutual labels:  robotics, physics-simulation
NAGPythonExamples
Examples and demos showing how to call functions from the NAG Library for Python
Stars: ✭ 46 (+53.33%)
Mutual labels:  linear-algebra, scientific-computing
Armadillo Code
Armadillo: fast C++ library for linear algebra & scientific computing - http://arma.sourceforge.net
Stars: ✭ 388 (+1193.33%)
Mutual labels:  linear-algebra, scientific-computing
Arraymancer
A fast, ergonomic and portable tensor library in Nim with a deep learning focus for CPU, GPU and embedded devices via OpenMP, Cuda and OpenCL backends
Stars: ✭ 793 (+2543.33%)
Mutual labels:  linear-algebra, high-performance-computing

NASOQ: Numerically Accurate Sparsity Oriented QP Solver

NASOQ is a scalable and efficient Quadratic Programming solver that obtains solutions for requested accuracies. Visit our website for more details: NASOQ Website

Installation

Library requirements

MKL Pardiso or OpenBlas (BLAS), OpenMP and METIS. Cmake handles METIS. If you install OpenBlas in its default location (sudo make install), Cmake will detect it.

Building the project

Given that MKL Pardiso or OpenBlas are installed, install NASOQ using following steps:

mkdir build
cd build
cmake -DMKL_ROOT_PATH=path/to/intel  -DCMAKE_BUILD_TYPE=Release ..
make

A quick script for building and running NASOQ is provided in buildALL.sh. You need to first correct paths to libraries and then you can run it as following:

bash buildAll.sh

Upon successful build you should be able to see data/out.csv and it should be similar to data/out_correct.csv.

For installing on MAc you might need to use GCC so you need to also set the CMAKE compiler flag.

More details are provided in: https://nasoq.github.io/docs/getting-started-nasoq/

Using NASOQ as a Library

More details: https://nasoq.github.io/docs/getting-started-nasoq/

Testing a QP example

To test a QP example you may also use NASOQ-BIN which is a command line interfce for NASOQ. Some small QP problems are available in data folder. For evaluating NASOQ versus other solvers a separate repository is also provided in: https://github.com/sympiler/nasoq-benchmarks More details: https://nasoq.github.io/docs/repository/

Copyright 2020 Kazem Cheshmi

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].