Explore @HPAC Open Source projects

High-Performance and Automatic Computing (@HPAC)

HPAC

Stars
380
Global Org. Rank 28,179 (Top 9 %)
Registered about 9 years ago
Most used languages

Python
35.3 %

C
35.3 %

C++
17.6 %

Julia
5.9 %

Jupyter Notebook
5.9 %
Location 🇩🇪 Germany
Country Total Rank 3,942
Country Ranking

Julia
276

Python
694

C
705

Jupyter Notebook
2,369

C++
2,671

matchpy

A library for pattern matching on symbolic expressions in Python.

linnea

Linnea is an experimental tool for the automatic generation of optimized code for linear algebra problems.

ReLAPACK

Recursive LAPACK Collection

tccg

Tensor Contraction Code Generator

TTC

TTC: A high-performance Compiler for Tensor Transpositions

ELAPS

Experimental Linear Algebra Performance Studies

lammps-tersoff-vector

A Vectorized Implementation of the Tersoff Potential for the LAMMPS Molecular Dynamics Software

RElem

R package for distributed parallel computation using Elemental

LinearAlgebra-Awareness-Benchmark

LAMP_benchmark

Benchmarks that evaluate whether high-level linear algebra languages solve the Linear Algebra Mapping Problem (LAMP).

Jupyter Notebook

CP-CALS

Software for computing the Canonical Polyadic Decomposition (CPD), using the Concurrent Alternating Least Squares Algorithm (CALS).

MD-modeling

https://arxiv.org/abs/1608.04694

pmrrr

Automatically exported from code.google.com/p/pmrrr

TTC-C

C wrapper library for TTC

MatrixGeneratorCpp

pmrrr-extended

MatrixGenerator.jl