The high performance computing industry has tended to emphasise the raw hardware performance of supercomputing, heralding ever-faster processors and parallel architectures. But a new initiative at Arizona State University (ASU) seeks to turn the focus to the human side of supercomputing, studying new tools and techniques that make researchers work faster, easier and more productively.
The High Performance Computing Initiative (HPCI) at ASU’s Ira A. Fulton School of Engineering is exploring a range of future programming paradigms for HPC systems, comparing them against traditional parallel programming methods.
The HPCI is investigating how parameters such as user interface, ease-of-use, interactive discovery and time-to-solution factor into an optimal computing paradigm. To provide the necessary infrastructure for the applications currently being tested by 100 students and faculty members, the university is running Star-P, from Interactive Supercomputing, on a 2,000 multicore processor parallel system.
The Star-P software allows the users to build algorithms and models on their desktops using familiar mathematical tools – such as Matlab, Python and R – and then run them instantly and interactively on the parallel system with little to no modification.