2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS)

Topics of interest include, but are not limited to:

• Parallel and distributed algorithms, focusing on topics such as: numerical and combinatorial parallel algorithms for analysis, machine learning and simulation; parallel algorithms for accelerators, neuromorphic architectures, and other non-traditional systems; algorithms for cloud computing; power-aware parallel algorithms; streaming algorithms; domain-specific parallel and distributed algorithms; performance modeling and analysis of parallel and distributed algorithms; run-time algorithms and protocols for resource management, communication and synchronization on parallel and distributed systems.

• Applications of parallel and distributed computing, including computational and data-enabled science and engineering, big data applications, parallel crowd sourcing, large-scale social network analysis, management of big data, cloud and grid computing, scientific, biological and medical applications, and mobile computing. Papers focusing on applications using novel commercial or research architectures, big data approaches, or discussing scalability toward the exascale level are encouraged.

• Parallel and distributed architectures, including architectures for instruction-level and thread-level parallelism; memory technologies and memory hierarchy architectures; exascale systems designs; data center architectures; novel big data architectures; special purpose architectures, including graphics processors, signal processors, network processors, media accelerators, neuromorphic systems, and other special purpose processors and accelerators; impact of technology on architecture; network and interconnect architectures; parallel I/O and storage systems; power-efficient and green computing systems; resilience and dependable architectures; and performance modeling and evaluation.

• Parallel and distributed software, including parallel and multicore programming languages and compilers, runtime systems, operating systems, resource management including, middleware for supercomputers, grids, clouds, and data centers, libraries, performance modeling and evaluation, parallel programming paradigms, and programming environments and tools. Papers focusing on novel software systems for big data and exascale systems are encouraged.