Search Results for "parallel computing"
Sort By:
Showing 76 open source projects for "parallel computing"
View related business solutions-
Earn up to 15% annual interest with Nexo.Put idle assets to work with competitive interest rates, borrow without selling, and trade with precision. All in one platform. Geographic restrictions, eligibility, and terms apply.
-
Earn up to 15% annual interest with Nexo.Generate interest, borrow against your crypto, and trade a range of cryptocurrencies — all in one platform. Geographic restrictions, eligibility, and terms apply.
-
1
dispy
Distributed and Parallel Computing with/for Python.
dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing. -
2
Cuda Simulated Annealing GPU Route Plan
An Optimized GPU-Accelerated Route Planning of Multi-UAV Systems Using
An Optimized GPU-Accelerated Route Planning of Multi-UAV Systems Using Simulated Annealing Article CUDA CODE Usage of multiple unmanned aerial vehicles (UAV) in a certain mission makes flight route planning more complicated and slower. In order to obtain better performance, in the literature, most of the researchers propose using evolutionary algorithms and artificial intelligence approaches based on heuristics as optimization techniques. In addition to this, parallel programming... -
3
splitjob
Reads from stdin, splits and sends to parallel invocations of commands
Useful to split up jobs over multiple CPU cores or even multiple computers. Examples: tar -cf - /bigdirectory | splitjob -j 4 gzip > big.tar.gz splitjob "ssh h1 bzip2" "ssh h2 bzip2" < f > f.bz2 -
4
A framework to run MATLAB programs as batch jobs. Features a structured input description, integrity constraints and GUI.Independent parts of a job can execute in parallel on a cluster computer. Developed at Freiburg Brain Imaging (FBI) - http://fbi.uniklinik-freiburg.de/
-
Pylon is an All-in-one B2B Support Platform for modern B2B businesses.We bring together everything a post-sales teams team needs including a ticketing system, B2B omnichannel integrations (Slack Connect, Microsoft Teams), modern chat widget, knowledge base, AI support bot, account management, customer marketing, and more.
-
5
Ichnaea
Performance Timing Tools
Ichnaea is a set of tools that aid in collecting and tracking parameters and timings for parallel applications. The Performance Modelling Timing Module, PMTM, is a library that wraps system timing calls to abstract these from code developers and aid portability. It also has functionality to store parameters and print those, along with the timing information to a comma separated variable file. The Performance Modelling Analysis Tool, PMAT, is coming soon. This is able to read in and... -
6
neuranep
Neural Network Engineering Platform
A parallel-programming framework for concurrently running large numbers of small autonomous jobs, or microthreads, across multiple cores in a CPU or CPUs in a cluster. NeuraNEP emulates a distributed processing environment capable of handling millions of microthreads in parallel, for example running neural networks with millions of spiking cells. Microthreads are general processing elements that can also represent non-neural elements, such as cell populations, extracellular space, emulating... -
7
mapgraph
Massively Parallel Graph processing on GPUs -- now part of Blazegraph
Mapgraph is SYSTAP’s disruptive new technology to exploit the main memory bandwidth advantages of GPUs. The early work was co-developed with the University of Utah SCI Institute and has its pedigree in the UINTAH software running on over 750M cores on the TITAN Super Computer. Today, SYSTAP has commercialized this technology into it’s Blazegraph Accelerator and Blazegraph HPC products. Checkout our options for GPU acceleration of graphs or contact us to learn more: ... -
8
PuSSH is Pythonic, Ubiquitous SSH, a Python wrapper/script that runs commands in parallel on clusters/ranges of linux/unix machines via SSH, ideally where SSH is configured to use Kerberos, RSA/DSA keys, or ssh-agent as to avoid password authentication.
-
9
-
Secure Your Website Now | Source Defense PlatformSource Defense Platform provides a simple and effective solution for data security and data privacy compliance – addressing threats and risks originating from the increased use of JavaScript, third-party vendors, and open-source code in your web properties.
-
10
GXP is a parallel/distributed shell, plus a parallel task execution engine that runs your Makefile in parallel on distributed machines. Very easy to install (no need to compile. install it on YOUR machine and use it on ALL machines).
-
11
corunner
A utility to transport files and execute at remote in prarallel
Are you maitaining many machines and bored with the tedious operation of logging to those machines one by one just for checking the machine's status? Or are you losing patient for your simple script that have to run command in those machines in sequence? The corunner is just for those senarios. It's designed to speed up execution in your machines. It can executes command in handreds of or thousands of machines concurrently. Provide it with your files and command and the machines' location,... -
12
FlowVR is an open source middleware tailored for high performance in situ data processing and analytics running on large parallel machines
-
13
-
14
MapPSO is a tool for Ontology Alignment, which uses Discrete Particle Swarm Optimisation. A particle swarm is used to search for the optimal alignment. The algorithm is massively parallel and adapts naturally on parallel architectures.
-
15
PyDSH is a remote administration tool, consisting of pydsh and pydcp. Pydsh allows you to run a command on multiple hosts in parallel over RSH, SSH or Telnet, OR manage your SSH public keys. The pydcp command allows copying files to/from multiple hosts.
-
16
SECTOR: A Distributed Data Storage and Processing Platform
-
17
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
-
18
Platform for parallel computation in the Amazon cloud, including machine learning ensembles written in R for computational biology and other areas of scientific research. Home to MR-Tandem, a hadoop-enabled fork of X!Tandem peptide search engine.
-
19
A scripting language and reference implementation to allow command line tools to be chained into complex parallel workflows.
-
20
Equalizer is the standard middleware to create parallel OpenGL-based applications. Please visit https://github.com/Eyescale for current development information.
-
21
GridSim allows modeling and simulation of entities in parallel and distributed computing systems such as users, applications, resources, and resource brokers/schedulers for design and evaluation of scheduling algorithms. http://www.gridbus.org/gridsim
-
22
HadoopDB is a hybrid of parallel database and MapReduce technologies. It approaches parallel databases in performance and efficiency, yet still yields the scalability, fault tolerance, and flexibility of MapReduce systems.
-
23
Simdist lets you harness the power of cluster computing without any knowledge of parallel libraries such as MPI, and with no restrictions on programming language. Primarily targeted at evolutionary computing and similar master-slave configurations.
-
24
RT-BOINC stands for a Real-Time BOINC. It was designed for managing highly-interactive, short-term, and massively-parallel real-time applications. We implemented RT-BOINC on top of the recent BOINC server source codes.
-
25
Distributed Parallel Programming for Python! This package builds on traditional Python by enabling users to write distributed, parallel programs based on MPI message passing primitives. General python objects can be messaged between processors. Ru
