13^th Workshop on Scalable Computing
(WSC’23)

Warsaw, Poland, 17–20 September, 2023

The world of large-scale computing continuously evolves. The most recent addition to the mix comes from numerous data streams that materialize from exploding number of cheap sensors installed “everywhere”, on the one hand, and ability to capture and study events with systematically increasing granularity, on the other. To address the needs for scaling computational and storage infrastructures, concepts like: edge, fog and dew computing emerged.

Novel issues in involved in “pushing computing away from the center” did not replace open questions that existed in the context of grid and cloud computing. Rather, they added new dimensions of complexity and resulted in the need of addressing scalability across more and more complex ecosystems consisting of individual sensors and micro-computers (e.g. Raspberry PI based systems) as well as supercomputers available within the Cloud (e.g. Cray computers facilitated within the MS Azure Cloud).

Addressing research questions that arise in individual “parts” as well as across the ecosystem viewed from a holistic perspective, with scalability as the main focus is the goal of the Workshop on Scalable Computing. In this context, the following topics are of special interest (however, this list is not exhaustive).

Topics

Covered topics include (but are not limited to):

Algorithms, programming and data models for large-scale applications, simulations and systems
Architectures for large-scale computations (Accelerators – GPUs, Vector, FPGAs, quantum systems, federated systems, etc.)
HPC in Cloud
Large-scale computing with serverless and microservices
Large-scale symbolic, numeric, data-intensive, graph-oriented, distributed computations
Resilient, fault-tolerant and consensus techniques for large-scale computing
Large-scale distributed databases and repositories
Load-balancing/intelligent resource management in large-scale applications, simulations and systems
Performance analysis, evaluation, and optimisation for large-scale applications and systems
Scientific workflow scheduling
Data visualisation and virtualisation supporting large-scale computations
On-demand computing
Scaling applications from small-scale to exascale (and back) in edge-cloud continuum
Big data real-time computing/analytics and Big Data cloud services
Large-scale batch processing
Economic, business, ROI models, and energy efficient computation for large-scale applications in data centers
Disruptive uses of HPC technologies in AI/ML/DL
Integration of predictive models to improve the performance of scientific applications in terms of execution time and/or simulation accuracy
Workflow of applying AI/ML/DL to scientific applications in HPC infrastructures
HPC with AI/ML/DL and AI/ML/DL for HPC
HPC tools and infrastructure to improve the usability of AI/ML/DL to scientific applications
Optimised HPC systems design and setup for efficient AI/ML/DL

Submission rules

Authors should submit their papers as Postscript, PDF or MSWord files.
The total length of a paper should not exceed 12 pages IEEE style (including tables, figures and references). More pages can be added, for an additional fee (see details). IEEE style templates are available here.
Papers will be refereed and accepted on the basis of their scientific merit and relevance to the workshop.
Preprints containing accepted papers will be published on a USB memory stick provided to the FedCSIS participants.
Only papers presented at the conference will be published in Conference Proceedings and submitted for inclusion in the IEEE Xplore® database.
Conference proceedings will be published in a volume with ISBN, ISSN and DOI numbers and posted at the conference WWW site.
Conference proceedings will be submitted for indexation according to information here.
Organizers reserve right to move accepted papers between FedCSIS technical sessions.