Difference between revisions of "IEEE Cluster 2021"

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(modified through wikirestore by orapi)
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|has program chair=Ewa Deelman, Lin Gan
 
|has program chair=Ewa Deelman, Lin Gan
 
|Acronym          =IEEE Cluster 2021
 
|Acronym          =IEEE Cluster 2021
|End date        =2021/09/07
+
|End date        =2021-09-07
 
|Series          =IEEE Cluster
 
|Series          =IEEE Cluster
 
|Type            =Conference
 
|Type            =Conference
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|State            =US/OR
 
|State            =US/OR
 
|City            =US/OR/Portland
 
|City            =US/OR/Portland
 +
|Year            =2021
 
|Homepage        =https://clustercomp.org/2021/
 
|Homepage        =https://clustercomp.org/2021/
 
|Ordinal          =23
 
|Ordinal          =23
|Start date      =2021/09/10
+
|Start date      =2021-09-10
|Title            =IEEE Cluster Conference
+
|Title            =IEEE Cluster Conference}}
}}
 
 
=== Topics ===
 
=== Topics ===
 
==== Area 1: Application, Algorithms, and Libraries ====
 
==== Area 1: Application, Algorithms, and Libraries ====

Revision as of 03:39, 19 November 2021


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List of all ratings can be found at IEEE Cluster 2021/rating

IEEE Cluster 2021
IEEE Cluster Conference
Ordinal 23
Event in series IEEE Cluster
Dates 2021-09-10 (iCal) - 2021-09-07
Homepage: https://clustercomp.org/2021/
Submitting link: https://ssl.linklings.net/conferences/ieeecluster/
Location
Location: US/OR/Portland, US/OR, US
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Important dates
Abstracts: 2021/05/10
Papers: 2021/05/17
Submissions: 2021/05/17
Notification: 2021/07/05
Camera ready due: 2021/07/30
Committees
General chairs: Toni Cortes, Kathryn Mohror
PC chairs: Ewa Deelman, Lin Gan
Table of Contents

Topics

Area 1: Application, Algorithms, and Libraries

  • HPC and Big Data application studies on large-scale clusters
  • Applications at the boundary of HPC and Big Data
  • New applications for converged HPC/Big Data clusters
  • Application-level performance and energy modeling and measurement
  • Novel algorithms on clusters
  • Hybrid programming techniques in applications and libraries (e.g., MPI+X)
  • Cluster benchmarks
  • Application-level libraries on clusters
  • Effective use of clusters in novel applications
  • Performance evaluation tools

Area 2: Architecture, Network/Communications, and Management

  • Node and system architecture for HPC and Big Data clusters
  • Architecture for converged HPC/Big Data clusters
  • Energy-efficient cluster architectures
  • Packaging, power and cooling
  • Accelerators, reconfigurable and domain-specific hardware
  • Heterogeneous clusters
  • Interconnect/memory architectures
  • Single system/distributed image clusters
  • Administration, monitoring and maintenance tools

Area 3: Programming and System Software

  • Cluster system software/operating systems
  • Programming models for converged HPC/Big Data/Machine Learning systems
  • System software supporting the convergence of HPC, Big Data, and Machine Learning processing
  • Cloud-enabling cluster technologies and virtualization
  • Energy-efficient middleware
  • Cluster system-level protocols and APIs
  • Cluster security
  • Resource and job management
  • Programming and software development environments on clusters
  • Fault tolerance and high-availability

Area 4: Data, Storage, and Visualization

  • Cluster architectures for Big Data storage and processing
  • Middleware for Big Data management
  • Cluster-based cloud architectures for Big Data
  • Storage systems supporting the convergence of HPC and Big Data processing
  • File systems and I/O libraries
  • Support and integration of non-volatile memory
  • Visualization clusters and tiled displays
  • Big data visualization tools
  • Programming models for Big Data processing
  • Big Data application studies on cluster architectures