All Projects → janverschelde → PHCpack

janverschelde / PHCpack

Licence: GPL-3.0 license
The primary source code repository for PHCpack, a software package to solve polynomial systems with homotopy continuation methods.

Programming Languages

Ada
118 projects
c
50402 projects - #5 most used programming language
C++
36643 projects - #6 most used programming language
Cuda
1817 projects
python
139335 projects - #7 most used programming language
Macaulay2
6 projects

Projects that are alternatives of or similar to PHCpack

Bohrium
Automatic parallelization of Python/NumPy, C, and C++ codes on Linux and MacOSX
Stars: ✭ 209 (+318%)
Mutual labels:  parallel-computing, gpu-acceleration
QUICK
QUICK: A GPU-enabled ab intio quantum chemistry software package
Stars: ✭ 79 (+58%)
Mutual labels:  parallel-computing, gpu-acceleration
t8code
Parallel algorithms and data structures for tree-based AMR with arbitrary element shapes.
Stars: ✭ 37 (-26%)
Mutual labels:  parallel-computing
gardenia
GARDENIA: Graph Analytics Repository for Designing Efficient Next-generation Accelerators
Stars: ✭ 22 (-56%)
Mutual labels:  parallel-computing
corebench
corebench - run your benchmarks against high performance computing servers with many CPU cores
Stars: ✭ 29 (-42%)
Mutual labels:  parallel-computing
pestpp
tools for scalable and non-intrusive parameter estimation, uncertainty analysis and sensitivity analysis
Stars: ✭ 90 (+80%)
Mutual labels:  parallel-computing
pcluster-manager
Manage AWS ParallelCluster through an easy to use web interface
Stars: ✭ 67 (+34%)
Mutual labels:  parallel-computing
vuo
A realtime visual programming language for interactive media.
Stars: ✭ 103 (+106%)
Mutual labels:  parallel-computing
GoldenSun
A path tracer based on hardware ray tracing
Stars: ✭ 20 (-60%)
Mutual labels:  gpu-acceleration
ClimateTools.jl
Climate science package for Julia
Stars: ✭ 108 (+116%)
Mutual labels:  parallel-computing
CARE
CHAI and RAJA provide an excellent base on which to build portable codes. CARE expands that functionality, adding new features such as loop fusion capability and a portable interface for many numerical algorithms. It provides all the basics for anyone wanting to write portable code.
Stars: ✭ 22 (-56%)
Mutual labels:  gpu-acceleration
ps pytorch
implement distributed machine learning with Pytorch + OpenMPI
Stars: ✭ 47 (-6%)
Mutual labels:  parallel-computing
mango
Parallel Hyperparameter Tuning in Python
Stars: ✭ 241 (+382%)
Mutual labels:  parallel-computing
Crossbow
Crossbow: A Multi-GPU Deep Learning System for Training with Small Batch Sizes
Stars: ✭ 52 (+4%)
Mutual labels:  gpu-acceleration
learn-gpgpu
Algorithms implemented in CUDA + resources about GPGPU
Stars: ✭ 37 (-26%)
Mutual labels:  parallel-computing
brian2cuda
A brian2 extension to simulate spiking neural networks on GPUs
Stars: ✭ 46 (-8%)
Mutual labels:  gpu-acceleration
JUDI.jl
Julia Devito inversion.
Stars: ✭ 71 (+42%)
Mutual labels:  parallel-computing
hpc
Learning and practice of high performance computing (CUDA, Vulkan, OpenCL, OpenMP, TBB, SSE/AVX, NEON, MPI, coroutines, etc. )
Stars: ✭ 39 (-22%)
Mutual labels:  parallel-computing
Apriori-and-Eclat-Frequent-Itemset-Mining
Implementation of the Apriori and Eclat algorithms, two of the best-known basic algorithms for mining frequent item sets in a set of transactions, implementation in Python.
Stars: ✭ 36 (-28%)
Mutual labels:  gpu-acceleration
Lazy
Light-weight header-only library for parallel function calls and continuations in C++ based on Eric Niebler's talk at CppCon 2019.
Stars: ✭ 93 (+86%)
Mutual labels:  parallel-computing

PHCpack

PHCpack is a software package to solve polynomial systems by homotopy continuation methods.

A polynomial system is given as a sequence of polynomials in several variables. Homotopy continuation methods operate in two stages. In the first stage, a family of polynomial systems (the so-called homotopy) is constructed. This homotopy contains a polynomial system with known solutions. In the second stage, numerical continuation methods are applied to track the solution paths defined by the homotopy, starting at the known solutions and leading to the solutions of the given polynomial system.

Version 1.0 of PHCpack has been archived by ACM Transactions of Mathematical Software (ACM TOMS) as Algorithm 795. PHCpack incorporates MixedVol (Algorithm 846 of ACM TOMS by T. Gao, T.Y. Li, and M. Wu) to compute mixed volumes fast. DEMiCs (Dynamic Enumeration of all Mixed Cells, by T. Mizutani, A. Takeda, and M. Kojima), computes mixed volumes at a faster pace than MixedVol for larger systems with many different supports. DEMiCs is also integrated into PHCpack. For its double double and quad double arithmetic, PHCpack contains QDlib of Y. Hida, X.S. Li, and D.H. Bailey. For triple double, and other multiple doubles (penta, octo, deca), code generated from the CAMPARY software is used. CAMPARY is the CudA Multiple Precision ARithmetic librarY, by Mioara Joldes, Olivier Marty, Jean-Michel Muller, Valentina Popescu and Warwick Tucker.

This material is based upon work supported by the National Science Foundation under Grants No. 9804846, 0105739, 0134611, 0410036, 0713018, 1115777, 1440534, and 1854513. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

Executable versions of the code for Linux, MacOS X, and Windows are available at http://www.math.uic.edu/~jan/download.html. Other links:

The restructured text source for the documentation for PHCpack starts at https://github.com/janverschelde/PHCpack/tree/master/src/doc/source and for phcpy at https://github.com/janverschelde/PHCpack/tree/master/src/Python/PHCpy3/doc/source.

To try phcpy in a python or SageMath kernel of a jupyter notebook, visit http://www.phcpack.org.

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].