This workshop seeks to explore solutions for supporting efficient execution of irregular applications in the form of new features at the level of the micro- and system-architecture, network, languages and libraries, runtimes, compilers, analysis, algorithms. Topics of interest, of both theoretical and practical significance, include but are not limited to:

- Micro- and System-architectures, including multi- and many-core designs, heterogeneous processors, accelerators (GPUs, vector processors, Automata processor), reconfigurable (coarse grained reconfigurable and FPGA designs) and custom processors 

- Network architectures and interconnect (including high-radix networks, optical interconnects) 

- Novel memory architectures and designs (including processors-in memory) 

- Impact of new computing paradigms on irregular workloads (including neuromorphic processors and quantum computing) 

- Modeling, simulation and evaluation of novel architectures with irregular workloads 

- Innovative algorithmic techniques 

- Combinatorial algorithms (graph algorithms, sparse linear algebra, etc.)

- Impact of irregularity on machine learning approaches

- Parallelization techniques and data structures for irregular workloads

- Data structures combining regular and irregular computations (e.g., attributed graphs)

- Approaches for managing massive unstructured datasets (including streaming data) 

- Languages and programming models for irregular workloads

- Library and runtime support for irregular workloads

- Compiler and analysis techniques for irregular workloads

- High performance data analytics applications, including graph databases