Scaling science applications on blue gene

Massively parallel supercomputers like IBM's Blue Gene/L offer exciting new opportunities for scientific discovery by enabling numerical simulations on an unprecedented scale. However, achieving highly scalable performance is often not straightforward as the system's extraordinary level of parallelism and its specialized nodes present challenges to applications in many areas, including: communication efficiency, memory usage, and I/O. This mini-symposium aimed to highlight some of the remarkable scaling and performance results achieved, and bring together users and system experts to discuss possible solutions to yet unresolved issues. It featured speakers whose applications have run at large scale on the 8K node system at John von Neumann Institute for Computing at Forschungszentrum Jülich and the 20K node system at IBM's Watson Research Center. The talks provided a sampling of the different applications and algorithms that have successfully run on Blue Gene. The speakers discussed best practices, particularly with respect to scaling to tens of thousands of processes, and challenges faced in using BlueGene/L to massive scale, and they showcased some of the breakthrough science that has already been achieved.