Performance Tuning in the Petascale Era
Felix Wolf, David Böhme, Brian J. N. Wylie, Bernd W. Mohr, Markus Geimer, Marc-André Hermanns, Zoltán Szebenyi · JuSER (Forschungszentrum Jülich) · 2010
Driven by application requirements and accelerated by current trends in microprocessor design, the number of processor cores on modern supercomputers grows from generation to generation. As a consequence, supercomputing applications are required to harness much higher degrees of parallelism in order to satisfy their growing demand for computing power. However, writing code that runs efficiently on large numbers of processors remains a significant challenge. The situation is exacerbated by the fact that the rising number of cores imposes scalability demands not only on applications but also on the software tools needed for their development. To address this challenge, the Helmholtz University Young Investigators Group Performance Analysis of Parallel Programs at Jülich Supercomputing Centre (JSC) in cooperation with the JSC Division Application Support creates software technologies aimed at improving the performance of applications running on leadership-class systems. At the center of our activities lies the development of Scalasca, a performance-analysis tool that has been specifically designed for large-scale systems and that allows the automatic identification of harmful wait states in applications running on tens of thousands of processors. In this article, we highlight the research activities of our group during the past two years and give an outlook on future work. 1