Interactive Supercomputing has released an updated version of Star-P software, designed for users of Python. The new version offers huge productivity gains for Python users who need to solve computationally intensive problems.
Star-P 2.5 for Python is an interactive parallel computing platform that enables users to code algorithms and models on their desktops using Python, but run them instantly and interactively on parallel high performance computers (HPCs). It eliminates the need to re-program the applications in lower-level language extensions such as MPI (message passing interface) to run on parallel systems – which typically takes months to complete for large, complex problems.
The software benefits Python users in two key ways: it allows them to work with much larger data sets, and it reduces the time to discovery by using faster algorithms
Star-P 2.5 for Python includes a new Python client interface that lets users take advantage of Python-specific numerical libraries and functions. These include NumPy and SciPy, Python programming extensions that add support for large, multi-dimensional arrays and matrices, as well as high-level mathematical functions which operate on these arrays.
Star-P for Python allows users to use any of Python’s hundreds of functions in a task parallel computation, such as Monte Carlo simulations or unrolling serial ‘for’ loops. Additionally, for data parallel computing more than 50 of the most popular blockbuster functions commonly used in technical computing are included, and more are being added rapidly.