20 projects tagged "Distributed Computing"
Updated 26 Apr 2013
JPPF
| Pop | 873.85 |
|---|---|
| Vit | 88.98 |
JPPF makes it easy to parallelize computationally intensive tasks and execute them on a Grid.
Updated 23 Apr 2013
Makeflow
| Pop | 338.32 |
|---|---|
| Vit | 14.09 |
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 19 Feb 2013
Parrot and Chirp
| Pop | 248.50 |
|---|---|
| Vit | 10.63 |
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 06 Nov 2012
Shared Scientific Toolbox in Java
| Pop | 203.07 |
|---|---|
| Vit | 5.55 |
The Shared Scientific Toolbox is a library that facilitates development of efficient, modular, and robust scientific/distributed computing applications in Java. It features multidimensional arrays with extensive linear algebra and FFT support, an asynchronous, scalable networking layer, and advanced class loading, message passing, and statistics packages.
Updated 03 Nov 2012
Wisecracker
| Pop | 51.19 |
|---|---|
| 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.
Updated 25 Oct 2012
dispy
| Pop | 77.50 |
|---|---|
| Vit | 2.48 |
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 10 Oct 2012
POP-C++
| Pop | 56.78 |
|---|---|
| Vit | 2.03 |
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 22 Mar 2011
Dapper Dataflow Engine
| Pop | 171.89 |
|---|---|
| Vit | 4.03 |
Dapper, or "Distributed and Parallel Program Execution Runtime", is a tool for taming the complexities of developing for large-scale cloud and grid computing, enabling the user to create distributed computations from the essentials: the code that will execute, along with a dataflow graph description. It supports rich execution semantics, carefree deployment, a robust control protocol, modification of the dataflow graph at runtime, and an intuitive user interface.
Updated 26 Feb 2011
WOSH Framework
| Pop | 147.58 |
|---|---|
| Vit | 5.37 |
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 14 Dec 2010
StarCluster
| Pop | 78.69 |
|---|---|
| Vit | 2.14 |
StarCluster is a utility for creating traditional computing clusters used in research labs or for general distributed computing applications on Amazon's Elastic Compute Cloud (EC2). It uses a simple configuration file provided by the user to request cloud resources from Amazon and to automatically configure them with a queuing system, an NFS shared /home directory, passwordless SSH, OpenMPI, and ~140GB scratch disk space. It consists of a Python library and a simple command line interface to the library. For end-users, the command line interface provides simple intuitive options for getting started with distributed computing on EC2 (i.e. starting/stopping clusters, managing AMIs, etc). For developers, the library wraps the EC2 API to provide a simplified interface for launching/terminating nodes, executing commands on the nodes, copying files to/from the nodes, etc.
