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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.
Anaconda distribution comes with over 300 packages automatically installed, and over 7,500 additional open-source packages can be installed from the Anaconda repository [36] as well as the Conda package and virtual environment manager. It also includes a GUI, Anaconda Navigator, [37] as a graphical alternative to the command-line interface (CLI).
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.
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.
1. Go to www.java.com. 2. Click Free Java Download. 3. Click Agree and Start Free Download. 4. Click Run. Notes: If prompted by the User Account Control window, click Yes. If prompted by the Security Warning window, click Run. 5. Click Install, and then follow the on-screen instructions to complete the installation. You're done!
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.
Cluster versions of LAPACK and FFTs are also available as part of MKL to take advantage of MPI parallelism in addition to single node parallelism from multithreading. Vector math functions include computationally intensive core mathematical operations for single and double precision real and complex data types. These are similar to libm ...
ScaLAPACK is designed for heterogeneous computing and is portable on any computer that supports MPI or PVM. ScaLAPACK depends on PBLAS operations in the same way LAPACK depends on BLAS . As of version 2.0, the code base directly includes PBLAS and BLACS and has dropped support for PVM.