20 projects tagged "Distributed Computing"
Updated 26 Feb 2011
WOSH Framework
| Pop | 149.53 |
|---|---|
| Vit | 5.34 |
WOSH (Wide Open Smart Home) is a message-oriented middleware for controlling and automating a smart home. It comes with working services and devices. WOSH is an open multi-platform C++ framework. Its architecture is service (bundles) oriented and designed for distributed (cloud) computing. WOSH ships with library source, many services, and some applications (a server, a trayicon remote controller, and a GUI full-controller). Some features provided by its micro-kernel are a multi-user system with access policies, a centralized database manager and system monitor, and automatic network management and masquerading (on TCP). Some of the implemented services are: multimedia audio playback, monitor and control of X10 devices, remote control using instant messaging, and a remote control using SMS and call notification.
Updated 11 Jun 2010
Ex-Crawler
| Pop | 23.47 |
|---|---|
| Vit | 1.04 |
The Ex-Crawler Project is divided into three subprojects. The main part is the Ex-Crawler daemon server, a highly configurable and flexible Web crawler written in Java. It comes with its own socket server, with which you can manage the server, users, distributed grid/volunteer computing, and much more. Crawled information is stored in a database (Currently MySQL, PostgreSQL, and MSSQL are supported). The second part is a graphical (Java Swing) distributed grid/volunteer computing client, including user computer state detection, based on JADIF Project. The Web search engine is written in PHP. It comes with a Content Management System, user language detection and multi-language support, and templates using Smarty, including an application framework that is partly forked from Joomla 1.5, so that Joomla components can be adapted quickly.
Updated 05 Jun 2010
JADIF
| Pop | 21.59 |
|---|---|
| Vit | 33.52 |
Java distributed framework is a framework for distributed grid and / or volunteer computing. It's divided into a server and client library. You can create new or implement it into existing applications in no time; you don't need knowledge about network connections, sockets, etc. The Framework does almost everything automatically. It provides secure automatic client <-> server communications, unique IDs, automatic resending of jobs to new clients if needed, user stats, and much more. The client framework supports the detection of the computer's user state (idling, away, online, etc.). It also offers many other useful features and helpers for developing a distributed client application.
Updated 30 Jun 2010
PyMW
| Pop | 48.37 |
|---|---|
| Vit | 1.00 |
PyMW is a Python module for parallel master-worker computing in a variety of environments. With the PyMW module, users can write a single program that scales from multicore machines to global computing platforms.
Updated 23 Apr 2013
Makeflow
| Pop | 233.62 |
|---|---|
| Vit | 12.30 |
Makeflow is a workflow engine for executing large complex applications on clusters, clouds, and grids. It can be used to drive several different distributed computing systems, including Condor, SGE, and the included Work Queue system. It does not require a distributed filesystem, so you can use it to harness whatever collection of machines you have available. It is typically used for scaling up data-intensive scientific applications to hundreds or thousands of cores.
Updated 30 Oct 2010
dtools
| Pop | 16.03 |
|---|---|
| Vit | 31.01 |
dtools (Distributed tools) is a suite of programs that allows Unix commands to be run in parallel on a list of tagged hosts. It is based on Capistrano and Fabric, has a modular architecture and is easy to extend, and has full integration with SSH.
Updated 10 Oct 2012
POP-C++
| Pop | 55.24 |
|---|---|
| Vit | 1.93 |
POP-C++ is a comprehensive object-oriented system for developing applications in large distributed computing infrastructures such as Grid, P2P or Clouds. It consists of a programming suite (language, compiler) and a run-time system for running POP-C++ applications. The POP-C++ language is a minimal extension of C++ that implements the parallel object model with the integration of resource requirements into distributed objects. This extension is as close as possible to standard C++ so that programmers can easily learn POP-C++ and so that existing C++ libraries can be parallelized using POP-C++ without too much effort. The POP-C++ run-time is an object-oriented open design that aims at integrating different distributed computing tool kits into an infrastructure for executing requirement-driven object-oriented applications. It uses objects to serve objects: the system provides services for executing remote objects.
Updated 19 Feb 2013
Parrot and Chirp
| Pop | 160.30 |
|---|---|
| Vit | 9.33 |
Parrot and Chirp are user-level tools that make it easy to rapidly deploy wide area filesystems. Parrot is the client component: it transparently attaches to unmodified applications, and redirects their system calls to various remote servers. A variety of controls can be applied to modify the namespace and resources available to the application. Chirp is the server component: it allows an ordinary user to easily export and share storage across the wide area with a single command. A rich access control system allows users to mix and match multiple authentication types. Parrot and Chirp are most useful in the context of large scale distributed systems such as clusters, clouds, and grids where one may have limited permissions to install software.
Updated 25 Oct 2012
dispy
| Pop | 75.95 |
|---|---|
| Vit | 2.42 |
dispy is a Python framework for parallel execution of computations by distributing them across multiple processors in a single machine (SMP), or among many machines in a cluster or grid. The computations can be standalone programs or Python functions. dispy is well suited for the data parallel (SIMD) paradigm where a computation is evaluated with different (large) datasets independently (similar to Hadoop, MapReduce, Parallel Python). dispy features include automatic distribution of dependencies (files, Python functions, classes, modules), client-side and server-side fault recovery, scheduling of computations to specific nodes, encryption for security, sharing of computation resources if desired, and more.
Updated 03 Nov 2012
Wisecracker
| Pop | 50.24 |
|---|---|
| Vit | 1.00 |
Wisecracker is a high performance distributed cryptanalysis framework that leverages GPUs and multiple CPUs. It allows security researchers to write their own cryptanalysis tools that can distribute brute-force cryptanalysis work across multiple systems with multiple multi-core processors and GPUs. Security researchers can also use the sample tools provided out-of-the-box. The differentiating aspect of Wisecracker is that it uses OpenCL and MPI together to distribute the work across multiple systems, each having multiple CPUs and/or GPUs.
