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Open MPI is a Message Passing Interface (MPI) library project combining technologies and resources from several other projects (FT-MPI, LA-MPI, LAM/MPI, and PACX-MPI).It is used by many TOP500 supercomputers including Roadrunner, which was the world's fastest supercomputer from June 2008 to November 2009, [3] and K computer, the fastest supercomputer from June 2011 to June 2012.
Anaconda, Inc. compiles and builds the packages available in the Anaconda repository itself, and provides binaries for Windows 32/64 bit, Linux 64 bit and MacOS 64-bit (Intel, Apple Silicon). Anything available on PyPI may be installed into a Conda environment using pip, and Conda will keep track of what it has installed and what pip has installed.
Conda is an open-source, [2] cross-platform, [3] language-agnostic package manager and environment management system. It was originally developed to solve package management challenges faced by Python data scientists , and today is a popular package manager for Python and R .
[10] Version 3.0 was released in May 2008. Included in the new features in 3.0 is the concept of tasks and the task construct, [11] significantly broadening the scope of OpenMP beyond the parallel loop constructs that made up most of OpenMP 2.0. [12] Version 4.0 of the specification was released in July 2013. [13]
WSL (Beta) (Bash on Ubuntu on Windows) Windows 10 build 14316: Windows 10 version 1607 (Anniversary Update) WSL (no longer Beta) Windows 10 build 16251: Windows 10 version 1709 (Fall Creators Update) WSL 2 (lightweight VM) Windows 10 build 18917: Windows 10 version 2004 (also backported to 1903 and 1909) WSL 2 GPU support: Windows 10 build 20150
Mingw-w64 includes a port of the GNU Compiler Collection (GCC), GNU Binutils for Windows (assembler, linker, archive manager), a set of freely distributable Windows specific header files and static import libraries for the Windows API, a Windows-native version of the GNU Project's GNU Debugger, and miscellaneous utilities.
The Message Passing Interface (MPI) is a portable message-passing standard designed to function on parallel computing architectures. [1] The MPI standard defines the syntax and semantics of library routines that are useful to a wide range of users writing portable message-passing programs in C, C++, and Fortran.
Chapel supports a multithreaded parallel programming model at a high level by supporting abstractions for data parallelism, task parallelism, and nested parallelism.It enables optimizations for the locality of data and computation in the program via abstractions for data distribution and data-driven placement of subcomputations.