Example node images for use with Warewulf 4

Open source web based reporting and monitoring tool for Bacula

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

Massively parallel multidimensional scaling

PyJAGS: The Python Interface to JAGS

This version extend from cudaminer which is the fastest Litecoin miner for NVIDIA GPUs. I customize code to run cuda on maximum GPU performance

ASIC and FPGA miner in c for bitcoin

Ethereum miner with OpenCL, CUDA and stratum support

Evoplex is a fast, robust and extensible platform for developing agent-based models and multi-agent systems on networks. It's available for Windows, Linux and macOS.

Efficient GPU kernels for block-sparse matrix multiplication and convolution

Tutorial for building a custom CUDA function for Pytorch

CUDA FFT convolution

ATen: A TENsor library for C++11

[ARCHIVED] The C++ parallel algorithms library. See https://github.com/NVIDIA/cccl

CUDA Data Parallel Primitives Library

Matrix-Vector Multiplication Using Shared and Coalesced Memory Access

🦮 An introduction to our Answer Set Programming tools focusing on gringo, clingo, and clasp.

GoogleTest - Google Testing and Mocking Framework

OpenPDF is a free Java library for creating and editing PDF files, with a LGPL and MPL open source license. OpenPDF is based on a fork of iText. We welcome contributions from other developers. Plea…

A 2D chart library for Java applications (JavaFX, Swing or server-side).

An entirely open source driver and user-space daemon that allows you to manage your Razer peripherals on GNU/Linux

Macros in Python: quasiquotes, case classes, LINQ and more!

Neural and Synaptic Array Transceiver

The gflags package contains a C++ library that implements commandline flags processing. It includes built-in support for standard types such as string and the ability to define flags in the source …

Version of DAOOPT with implementations of dynamic heuristics and best-first search.

Tensorflow prebuilt binary for Windows

Tensors and Dynamic neural networks in Python with strong GPU acceleration