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|Title=IEEE Cluster Conference | |Title=IEEE Cluster Conference | ||
|Ordinal=23 | |Ordinal=23 | ||
− | | | + | |In Event Series=Event Series:IEEE Cluster |
+ | |Single Day Event=no | ||
+ | |Start Date=2021/09/07 | ||
+ | |End Date=2021/09/10 | ||
+ | |Event Status=as scheduled | ||
+ | |Event Mode=online | ||
+ | |Academic Field=Computer Science | ||
|Official Website=https://clustercomp.org/2021/ | |Official Website=https://clustercomp.org/2021/ | ||
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|Submission Link=https://ssl.linklings.net/conferences/ieeecluster/ | |Submission Link=https://ssl.linklings.net/conferences/ieeecluster/ | ||
+ | |Type=Conference | ||
|has general chair=Toni Cortes, Kathryn Mohror | |has general chair=Toni Cortes, Kathryn Mohror | ||
|has program chair=Ewa Deelman, Lin Gan | |has program chair=Ewa Deelman, Lin Gan | ||
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|pageEditor=User:Curator 53 | |pageEditor=User:Curator 53 | ||
|contributionType=1 | |contributionType=1 | ||
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}} | }} | ||
{{Event Deadline | {{Event Deadline | ||
+ | |Notification Deadline=2021/07/05 | ||
|Abstract Deadline=2021/05/10 | |Abstract Deadline=2021/05/10 | ||
|Paper Deadline=2021/05/17 | |Paper Deadline=2021/05/17 | ||
− | |||
|Camera-Ready Deadline=2021/07/30 | |Camera-Ready Deadline=2021/07/30 | ||
|Submission Deadline=2021/05/17 | |Submission Deadline=2021/05/17 | ||
}} | }} | ||
+ | {{Organizer | ||
+ | |Contributor Type=organization | ||
+ | |Organization=IEEE Computer Society, Institute of Electrical and Electronics Engineers | ||
+ | }} | ||
+ | {{Event Metric}} | ||
{{S Event}} | {{S Event}} | ||
− | === Topics === | + | ===Topics=== |
− | ==== Area 1: Application, Algorithms, and Libraries ==== | + | ====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 ==== | + | ====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 ==== | + | ====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 ==== | + | ====Area 4: Data, Storage, and Visualization==== |
− | * Cluster architectures for Big Data storage and processing | + | *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 |
Revision as of 12:20, 8 September 2023
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Venue
Warning: Venue is missing. The map might not show the exact location.
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