Irregular applications span a broad range of applications with unpredictable memory access patterns and/or network transfers, and divergent control structures. They typically use pointer-based data structures such as graphs and trees, often present fine-grained synchronization and communication, and generally operate on very large data sets. They have a significant degree of latent parallelism, which however is difficult to exploit due to their complex behavior. Current high performance architectures rely on data locality and regular computation to reduce access latencies, and often do not cope well with the requirements of these applications. Furthermore, irregular applications are difficult to scale on current supercomputing machines, due to their limits in fine-grained synchronization and small data transfers. Irregular applications pertain both to well established and emerging fields, such as social network analysis, bioinformatics, semantic graph databases, Computer Aided Design (CAD) and computer security. Many of these application areas also process massive sets of unstructured data, which keep growing exponentially. Addressing the issues of irregular applications on current and future architectures will become critical to solve the challenges in science and data analysis of the next few years.