Come see Didrik Pinte from #Enthought
speak on "Harnessing the Power of #HPC
with the #Python
Ecosystem" at the Advances in #Numerical
Algorithms and #High
Performance Computing event on Tues 4/15 at the #University
of Manchester http://ow.ly/vImut
Abstract: Numerical analysis is at a crossroads where hardware advances are outpacing the capability of software to harness its full potential, leaving data scientists constrained by the limitations of standard algorithms and generic software. To date, the lagging development of more sophisticated mathematical software has been in part due to the need for a programming language that can be learned quickly by a broad audience, yet still be powerful and flexible enough to handle the information throughput of HPC applications.
While Python has historically been overlooked in the high-performance computing world, today, with Python libraries such as NumPy, the language has transformed from a generalist programming language into a highly capable platform for developing next generation algorithms and HPC frameworks. Because Python is easy to learn but also easy to extend, professionals and researchers can build scalable, fast and robust software in a fraction of the time required by other coding languages.
In this presentation, we will illustrate how Python provides the tools and flexibility to develop software that paces the advances in HPC and how Python’s high-level programming stack is enriched by its broad ecosystem of libraries tailored to mathematical and scientific computing. We’ll provide examples of Python’s applicability for HPC ranging from how libraries such as NumPy allow for rapid manipulation and processing of large datasets to creating distributed arrays and interfacing with GPU's. With Python, data scientists now have the building blocks to create comprehensive HPC solutions to fully leverage the power of today’s hardware.