Journal Information
IEEE Transactions on Parallel and Distributed Systems (TPDS)
https://www.computer.org/csdl/journal/td
Impact Factor:
3.402
Publisher:
IEEE
ISSN:
1045-9219
Viewed:
21793
Tracked:
93

Call For Papers
IEEE Transactions on Parallel and Distributed Systems (TPDS) is published monthly. It publishes a range of papers, comments on previously published papers, and survey articles that deal with the parallel and distributed systems research areas of current importance to our readers. Particular areas of interest include, but are not limited to:

    Parallel and distributed algorithms, focusing on topics such as: models of computation; numerical, combinatorial, and data-intensive parallel algorithms, scalability of algorithms and data structures for parallel and distributed systems, communication and synchronization protocols, network algorithms, scheduling, and load balancing.

    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 and biomedical applications, mobile computing, and cyber-physical systems.

    Parallel and distributed architectures, including architectures for instruction-level and thread-level parallelism; design, analysis, implementation, fault resilience and performance measurements of multiple-processor systems; multicore processors, heterogeneous many-core systems; petascale and exascale systems designs; novel big data architectures; special purpose architectures, including graphics processors, signal processors, network processors, media accelerators, and other special purpose processors and accelerators; impact of technology on architecture; network and interconnect architectures; parallel I/O and storage systems; architecture of the memory hierarchy; power-efficient and green computing architectures; dependable architectures; and performance modeling and evaluation.

    Parallel and distributed software, including parallel and multicore programming languages and compilers, runtime systems, operating systems, Internet computing and web services, resource management including green computing, middleware for grids, clouds, and data centers, libraries, performance modeling and evaluation, parallel programming paradigms, and programming environments and tools.
Last updated by Dou Sun in 2020-05-07
Special Issues
Special Issue on Innovative R&D toward the Exascale Era
Submission Date: 2021-02-17

This special section explores new foundational and translational research toward enabling exascale computing for emerging scientific and societal challenges. Exascale computing (1,000 times more powerful than petascale) is defined as the capability to perform 1018 operations per second. Productively harnessing such a scale of processing, storage, and networking capabilities for diverse domains—including high-performance computing (HPC) simulations, artificial intelligence (AI), and extreme data-driven computing—relies on not only revitalizing existing parallel and distributed computing technologies but also innovating new solutions. Hence, topics related to applications, programming environments, runtimes, libraries, innovative algorithms, domain-specific frameworks, systems architecture, performance analysis, data processing, and networking technologies, among others, are within the scope of research encompassing parallel, distributed, and heterogeneous systems for exascale. Paths to exascale have been laid out across various national and international funding programs that are largely characterized by multidisciplinary research spanning from exascale centers of excellence for domain sciences to the development of operational IT infrastructure at scale. Characteristic features of the IT infrastructure technologies include accelerated processors, memory and storage hierarchies, smart networks for workflows, and storage for HPC and AI, among others. Software technologies and applications focus on developing next-generation scalable algorithms and frameworks, enabling performance portability, and enhancing productivity of complex parallel and distributed workflows. Contributions highlighting fundamental advances in software technologies, hardware, and applications over the current state-of-the art will be considered. Submissions addressing challenges that are unique to exascale computing, from application and algorithm development to reliability and availability of operational IT infrastructure, are within the scope of the special section. Topics of interest include, but are not limited to: - Efficient hardware for exascale science - Sustainable software technologies for exascale computing, with emphasis on integration, interoperability, and hardware-software co-design - Scalable applications (computational science/engineering, data analytics, AI) and algorithms - Performance measurement, modeling, and tools for exascale - AI for HPC / HPC for AI - Scalable IO for HPC and AI workloads - Libraries and runtimes for exascale - Systems, compilers, programming models, and languages at scale - Testing, tuning, debugging, and profiling applications at scale - Visualization at scale - Domain-specific libraries and frameworks - Parallel and distributed workflows - Availability, reliability, resilience, and fault-tolerance - Resource management and scheduling
Last updated by Shuo Ouyang in 2021-01-02
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