Pacific Northwest National Laboratory, United States of America
Due to the heterogeneous data sets they process, data intensive applications employ a diverse set of methods and data structures, exhibiting irregular memory accesses, control flows and communication patterns. Current supercomputing systems are organized around components optimized for data locality and bulk synchronous computations. Managing any form of irregularity on them demands substantial programming effort, and often leads to poor performance. Holistic solutions to these challenges emerge only by considering the problem from multiple perspectives: from micro- to system-architectures, from compilers to languages, from libraries to runtimes and from algorithm design to data characteristics. Only strong collaborative efforts among researchers with different expertise, including domain experts and end users, can lead to significant breakthroughs. This workshop brings together scientists with different backgrounds to discuss methods and technologies for efficiently supporting irregular applications on current and future architectures.