kadircs Goto Github PK

2021-04_ecp-tutorial

Tutorial workflow

a1

Argonne 1-sided (A1)

amrex

AMReX: Software Framework for Block Structured AMR

cagnet

conflux

Distributed Communication-Optimal LU-factorization Algorithm

coralgemm

cuda-samples

Samples for CUDA Developers which demonstrates features in CUDA Toolkit

cudalibrarysamples

CUDA Library Samples

cugraph

cuGraph - RAPIDS Graph Analytics Library

cuhornet

dagp

Multilevel Directed Acyclic Graph Partitioner

darknet

YOLOv4 - Neural Networks for Object Detection (Windows and Linux version of Darknet )

dcgs2

Delayed Classical Gram Schmidt with Reorthogonalization

docker101

ecp-e4s-examples

ECP examples utilizing spack and E4S caches

fast-hash

Fast hash function learned using genetic programming

folly

An open-source C++ library developed and used at Facebook.

gaugan

Photorealistic landscape drawings using the Nvidia SPADE model

git-tutorial

For learning

gmhc

GPU-accelerated Mahalanobis-average hierarchical clustering

googletest

GoogleTest - Google Testing and Mocking Framework

gpcnet

gptune

hicma

HiCMA: Hierarchical Computations on Manycore Architectures

hiop

HPC solver for nonlinear optimization problems

hmglib

Simple H matrix implementation on GPU

hyperdag_db

A database of HyperDAGs derived from various application areas. HyperDAG data are licensed CC-BY, tools are licensed Apache 2.0.

icl-parsec-course

Short course for teaching ICL Parsec's PTG DSL.

ka-bib

BibTeX bibliography of Kadir

kahypar

KaHyPar (Karlsruhe Hypergraph Partitioning) is a multilevel hypergraph partitioning framework providing direct k-way and recursive bisection based partitioning algorithms that compute solutions of very high quality.