Información de la conferencia
SC 2024: International Conference for High Performance Computing, Networking, Storage, and Analysis
https://sc24.supercomputing.org/
Día de Entrega:
2024-03-26
Fecha de Notificación:
2024-06-14
Fecha de Conferencia:
2024-11-17
Ubicación:
Atlanta, Georgia, USA
Años:
36
CCF: a   CORE: a   QUALIS: a1   Vistas: 53688   Seguidores: 160   Asistentes: 16

Solicitud de Artículos
Overview

The SC Papers program is the leading venue for presenting high-quality original research, groundbreaking ideas, and compelling insights on future trends in high performance computing, networking, storage, and analysis. Technical papers are peer-reviewed and an Artifact Description is mandatory for all papers submitted to SC.

Areas/Tracks

Submissions will be considered on any topic related to high performance computing within the areas below. Authors must indicate a primary area from the choices on the submissions form and are strongly encouraged to indicate a secondary area.

Small-scale studies – including single-node studies – are welcome as long as the paper clearly conveys the work’s contribution to high performance computing.

Algorithms

The development, evaluation, and optimization of scalable, general-purpose, high performance algorithms.

Applications

The development and enhancement of algorithms, parallel implementations, models, software and problem solving environments for specific applications that require high performance resources.

Architecture and Networks

All aspects of high performance hardware including the optimization and evaluation of processors and networks.

Clouds and Distributed Computing

Cloud and system software architecture, configuration, optimization and evaluation, support for parallel programming on large-scale systems or building blocks for next-generation HPC architectures.

Data Analytics, Visualization, and Storage

All aspects of data analytics, visualization, storage, and storage I/O related to HPC systems. Submissions on work done at scale are highly favored.

Machine Learning (ML) with HPC

The development and enhancement of algorithms, systems, and software for scalable machine learning utilizing high-performance computing technology.

Performance Measurement, Modeling, and Tools

Novel methods and tools for measuring, evaluating, and/or analyzing performance for large scale systems.

Post-Moore Computing

Technologies that continue the scaling of supercomputing performance beyond the limits of Moore's law, including system architectures, programming frameworks, system software, and applications.

Programming Frameworks and System Software

Operating system, runtime system, technologies, and software building blocks that enable management of hardware resources and support parallel programming for large-scale systems.

State of the Practice

All aspects of the pragmatic practices of HPC, including operational IT infrastructure, services, facilities, large-scale application executions and benchmarks.
Última Actualización Por Dou Sun en 2024-01-01
Coeficiente de Aceptación
AñoEnviadosAceptadosAceptados(%)
20143948220.8%
20134579621%
201247210021.2%
20113527421%
2009341029.4%
2008702028.6%
2007692130.4%
20062395422.6%
20052606324.2%
20041925930.7%
20032076029%
20022306729.1%
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