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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.
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 .
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.
OpenMP is an application programming interface (API) that supports multi-platform shared-memory multiprocessing programming in C, C++, and Fortran, [3] on many platforms, instruction-set architectures and operating systems, including Solaris, AIX, FreeBSD, HP-UX, Linux, macOS, and Windows.
Information flow of Reduce operation performed on three nodes. f is the associative operator and α is the result of the reduction. The reduce pattern [4] is used to collect data or partial results from different processing units and to combine them into a global result by a chosen operator.
pip (also known by Python 3's alias pip3) is a package-management system written in Python and is used to install and manage software packages. [4] The Python Software Foundation recommends using pip for installing Python applications and its dependencies during deployment. [5]
LAM/MPI is one of the predecessors of the Open MPI project. Open MPI represents a community-driven, next generation implementation of a Message Passing Interface (MPI) fundamentally designed upon a component architecture to make an extremely powerful platform for high-performance computing. LAM/MPI was officially retired in March 2015. [1]
Intel launched the oneAPI Math Kernel Library in November 1994, and called it Intel BLAS Library. [9] In 1996, the library was renamed to Intel Math Kernel Library until April 2020, when intel oneMKL has become part of oneAPI initiative to support multiple hardware architectures, holding the current name Intel oneAPI Math Kernel Library.