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IPython

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  Analyzed about 2 hours ago

IPython: Productive Interactive Computing IPython provides a rich toolkit to help you make the most out of using Python interactively. Its main components are: - Powerful interactive Python shells (terminal-, Qt- and web-based). - Support for interactive data visualization and use of GUI ... [More] toolkits. - Flexible, embeddable interpreters to load into your own projects. - Tools for high level and interactive parallel computing. [Less]

58.3K lines of code

68 current contributors

about 13 hours since last commit

472 users on Open Hub

High Activity
4.70103
   
0 Reviews
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Mostly written in Python
Licenses: BSD-3-Clause
Tags interactive library matplotlib notebook numpy parallelcomputing python scipy shell visualization

PETSc

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Claimed by Argonne National Laboratory Analyzed about 17 hours ago

PETSc, pronounced PET-see (the S is silent), is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations. It employs the MPI standard for parallelism.

1M lines of code

67 current contributors

2 days since last commit

24 users on Open Hub

Very High Activity
5.0
 
0 Reviews
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Mostly written in C
Licenses: bsd_2clau...
Tags hpc mathematics mpi odes parallel parallelcomputing pdes scientific_computing simulation solvers

GROMACS

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  Analyzed about 4 hours ago

GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. It is primarily designed for biochemical molecules like proteins, lipids and nucleic acids that have a lot of complicated bonded ... [More] interactions, but but thanks to its speed, many groups also use it for research on non-biological systems, e.g. polymers. Speed is one of the key features that makes GROMACS particularly attractive. Thanks to the strong emphasis on bottom-up performance tuning: hand-tuned CPU SIMD kernels are available for most CPU architectures, CUDA-and OpenCL-based GPU acceleration together with efficient multi-threading and neutral-territory domain-decomposition with MPI SPMD parallelization is supported. [Less]

4.69M lines of code

30 current contributors

3 days since last commit

20 users on Open Hub

High Activity
5.0
 
0 Reviews
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Mostly written in C++
Licenses: lgpl21
Tags avx avx2 bgq C++11 cuda gpu gromacs high_performance_computing hpc molecular_dynamics moleculardynamics molecular_simulation 8 more...

hazelcast

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  Analyzed 1 day ago

Hazelcast is a clustering and highly scalable data distribution platform for Java. Features: Distributed implementations of java.util.{Queue, Set, List, Map} Distributed implementation of java.util.concurrency.locks.Lock Distributed implementation of java.util.concurrent.ExecutorService ... [More] Distributed MultiMap for one-to-many relationships Distributed Topic for publish/subscribe messaging Transaction support and J2EE container integration via JCA Socket level encryption support for secure clusters Synchronous (write-through) and asynchronous (write-behind) persistence Second level cache provider for Hibernate Monitoring and management of the cluster via JMX Dynamic HTTP session clustering Support for cluster info and membership events Dynamic discovery Dynamic scaling Dynamic partitioning with backups Dynamic fail-over Hazelcast is for you if you want to share data/state among many servers (e.g. web session sharing) cache your data (distributed cache) for better performance cluster your application provide secure communication among servers partition your in-memory data send/receive messages among applications distribute workload onto many servers take advantage of parallel processing provide fail-safe data management Hazelcast is pure Java. JVMs that are running Hazelcast will dynamically cluster. Although by default Hazelcast will use multicast for discovery, it can also be configured to only use TCP/IP for enviroments where multicast is not available or preferred. Communication among cluster members is always TCP/IP with Java NIO beauty. Default configuration comes with 1 backup so if one node fails, no data will be lost. It is as simple as using java.util.{Queue, Set, List, Map}. Just add the hazelcast.jar into your classpath and start coding. A test application comes with the Hazelcast distribution that simulates the queue, set, map and lock APIs. You may want to watch the following 12 minute screencast to quickly get started. [Less]

1.6M lines of code

66 current contributors

1 day since last commit

15 users on Open Hub

High Activity
5.0
 
0 Reviews
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Mostly written in Java
Licenses: apache_2
Tags cache cloud cluster datagrid dht distributed distributed_computing distributedsystems ehcache elastic grid gridcomputing 8 more...

ScUtil

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  Analyzed 1 day ago

Hundreds of functions of a variety of topics, from statistics to string parsing, module utilities to network tools. Everyone's pet library accumulates features over time. My erlang library got big, fast. I often find myself giving functions from it out to other people, and a lot of my other ... [More] libraries are dependant on ScUtil in various ways, so I figured what the hell, let's give it away. This library is believed to be efficiently implemented at all points. Efficiency tips are, however, both appreciated and taken seriously. ScUtil uses the TestErl library for unit, regression and stochastic testing. ScUtil is free and MIT licensed, because the GPL is evil. ScUtil is written by John Haugeland, from http://fullof.bs/ . [Less]

9.39K lines of code

0 current contributors

over 10 years since last commit

11 users on Open Hub

Inactive
4.8
   
0 Reviews
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Mostly written in Erlang
Licenses: mit
Tags algorithms bayesian bayesianinference bayesianmodelling concurrency conversion correlation development dispatch distributed distributed_computing distributedcomputing 40 more...

MPICH

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Claimed by Argonne National Laboratory Analyzed 1 day ago

MPICH is a high-performance and widely portable implementation of the Message Passing Interface (MPI) standard. The goals of MPICH are: (1) to provide an MPI implementation that efficiently supports different computation and communication platforms including commodity clusters (desktop systems ... [More] , shared-memory systems, multicore architectures), high-speed networks and proprietary high-end computing systems and (2) to enable cutting-edge research in MPI through an easy-to-extend modular framework for other derived implementations. [Less]

514K lines of code

36 current contributors

2 days since last commit

11 users on Open Hub

High Activity
5.0
 
0 Reviews
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Mostly written in C
Licenses: BSD-3-Clause
Tags high_performance_computing hpc message_passing mpi mpi_2 mpi_3 mpich mpich2 mpich3 mpi_io parallel parallelcomputing 2 more...

HPX

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  Analyzed about 3 hours ago

HPX is a general purpose parallel C++ runtime system for parallel and distributed applications of any scale. It is a very modular and well designed runtime system architecture. Real world applications are used to drive the development of HPX, coining out required functionalities and converging onto ... [More] an stable API which provides a smooth migration path for developers. The API exposed by HPX is modelled after the interfaces defined by the C++11/14 ISO standard and adheres to the programming guidelines used by the Boost collection of C++ libraries. [Less]

631K lines of code

37 current contributors

about 11 hours since last commit

8 users on Open Hub

Very High Activity
5.0
 
0 Reviews
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Mostly written in C++
Licenses: boost
Tags c++ cplusplus cross-platform distributed distributed_computing distributedcomputing library parallel parallelalgorithm parallelcalculaion parallelcomputing paralleldistributedprocessing 9 more...

LAMMPS

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  Analyzed over 2 years ago

LAMMPS is a classical molecular dynamics simulator designed for parallel machines. It can model atomic, polymeric, biological, metallic, or granular systems using a variety of force fields and boundary conditions and can be easily modified and extend

2.38M lines of code

62 current contributors

over 2 years since last commit

6 users on Open Hub

Activity Not Available
0.0
 
0 Reviews
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Mostly written in C++
Licenses: No declared licenses
Tags c++ molecular_dynamics molecularsimulation mpi parallelcomputing scientific_computing

Portable Computing Language

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  Analyzed 2 days ago

Portable OpenCL is an open source implementation of the OpenCL standard which can be easily adapted for new targets. One of the goals of the project is improving performance portability of OpenCL programs, avoiding the need for target-dependent manual optimizations. A "native" target is included ... [More] , which allows running OpenCL kernels on the host (CPU). [Less]

392K lines of code

15 current contributors

8 days since last commit

5 users on Open Hub

High Activity
4.0
   
0 Reviews
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Mostly written in C
Licenses: mit
Tags compiler library llvm opencl parallelcomputing parallelprogramming performance portable

deeplearning4j

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  Analyzed about 22 hours ago

Deeplearning4j is the first commercial-grade, open-source, distributed deep-learning library; designed to be used in business environments. Deeplearning4j aims to be cutting-edge plug and play, more convention than configuration, which allows for fast prototyping for non-researchers. Vast ... [More] support of scale out: Hadoop, Spark and Akka + AWS et al It includes both a distributed, multi-threaded deep-learning framework and a normal single-threaded deep-learning framework. Iterative reduce net training. First framework adapted for a micro-service architecture. A versatile n-dimensional array class. GPU integration [Less]

1.16M lines of code

17 current contributors

5 months since last commit

5 users on Open Hub

Low Activity
4.0
   
0 Reviews
I Use This
Mostly written in Java
Licenses: apache_2
Tags akka aws bigdata cloud_computing cluster cpu deeplearning distributed gpu gpu_computing gpucomputing hadoop 8 more...