Search Results for "code::blocks"

* Fast GPU linear algebra library (matrix maths) for the C++ language, aiming towards a good balance between speed and ease of use * Provides high-level syntax and functionality deliberately similar to Matlab * Provides an API that is aiming to be compatible with Armadillo for easy transition between CPU and GPU linear algebra code * Useful for algorithm development directly in C++, or quick conversion of research code into production environments * Distributed under the permissive Apache 2.0 license, useful for both open-source and proprietary (closed-source) software * Can be used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc * Downloads: http://coot.sourceforge.io/download.html * Documentation: http://coot.sourceforge.io/docs.html * Bug reports: http://coot.sourceforge.io/faq.html * Git repo: https://gitlab.com/conradsnicta/bandicoot-code...

...It contains a collection of concurrent data structures: queues, stacks, sets, maps, etc, and safe memory reclamation schema for concurrent containers - Hazard Pointer and user-space RCU. See doxygen doc http://libcds.sourceforge.net/doc/cds-api/index.html. The source code repo for libcds 2.x has been moved to https://github.com/khizmax/libcds

This project comprises two main parts: 1. The classic "Rodney" as described in David L. Heisermann's book "How to build your own self-programming robot", with the original Intel 8085 code. In all likelihood, this is for reference only. I don't expect many people are going to build it 2. An updated version, running on more modern hardware, but remaining true to the algorithms published in his book. The end result will be at least three sets of code, for the Alpha, Beta and Gamma versions of Rodney. We would also like to experiment with a "Delta" version which could use either bare RF or WiFi to exchange state data between machines. ...

Project provides a set of concurrent building blocks (Java & C/C++) that can be used to develop parallel/multi-threaded applications. Components are grouped into 4 categories: 1.Data Structures 2. Parallel Patterns 3.Parallel functions 4.Atomics and STM