DescriptionDue to the heterogeneous data sets they process, data intensive applications employ a diverse set of methods and data structures. Consequently, they abound with 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 effort, and often leads to poor performance. Holistic solutions to address these challenges can emerge only by considering the problem from all perspectives: from micro- to system-architectures, from compilers to languages, from libraries to runtimes, from algorithm design to data characteristics. Strong collaborative efforts among researchers with different expertise, including domain experts and end users, could lead to significant breakthroughs. This workshop brings together scientists with these different backgrounds to discuss methods and technologies for efficiently supporting irregular applications on current and future architectures.