Difference between revisions of "IEEE Cluster 2021"
Jump to navigation
Jump to search
| Line 11: | Line 11: | ||
|State=Oregon | |State=Oregon | ||
|Country=USA | |Country=USA | ||
| + | |Abstract deadline=2021/05/10 | ||
| + | |Paper deadline=2021/05/17 | ||
| + | |Notification=2021/07/05 | ||
| + | |Camera ready=2021/07/30 | ||
|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 | ||
}} | }} | ||
| + | === 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 | ||
Revision as of 13:51, 8 April 2021
| IEEE Cluster 2021 | |
|---|---|
IEEE Cluster Computing
| |
| Ordinal | 23 |
| Event in series | IEEE Cluster |
| Dates | 2021/09/10 (iCal) - 2021/09/07 |
| Homepage: | https://clustercomp.org/2021/ |
| Location | |
| Location: | Portland, Oregon, USA |
| Important dates | |
| Abstracts: | 2021/05/10 |
| Papers: | 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