会议名称(中文)： 2015年IEEE集群计算国际会议
会议名称(英文)： 2015 IEEE International Conference on Cluster Computing (CLUSTER)
所属学科： 计算数学与科学工程计算,计算机科学理论,计算机系统结构与硬件,计算机应用技术
开始日期： 2015-09-08
结束日期： 2015-09-11
所在国家： 美国
所在城市： 美国
具体地点： Chicago, IL, USA
主办单位： IEEE Computer Society
[ 会务组联系方式 ]
联系人： Mary Dzielski
会议背景介绍：
Welcome to IEEE Cluster 2015. The conference takes place in Chicago, Illinois, the third largest city in the United States and a major technological and cultural capital. The conference is held on September 9-11 (Wednesday through Friday) with affiliated workshops and tutorials occurring on September 8 (Tuesday). Cluster 2015 welcomes research papers, workshops, and tutorials on advances in topics related to cluster computing.
征文范围及要求：
The conference’s topics of interest include, but are not limited to:
Area 1: Applications, Algorithms, and Libraries
HPC Applications on Clusters
Performance Modeling and Measurement
Novel Algorithms on Clusters
Hybrid Programming Techniques (MPI+OpenMP, MPI+OpenCL, etc.)
Cluster Benchmarks
Application-level Libraries on Clusters
Effective Use of Clusters in Novel Applications
Performance Evaluation Tools
Area 2: Architecture, Networks/Communication, and Management
Energy-efficient Cluster Architectures
Node and System Architecture
Packaging, Power and Cooling
GPU/ManyCore and Heterogeneous Clusters
Interconnect/memory Architectures
Single System Image Clusters
Administration and Maintenance Tools
Area 3: Programming and System Software
Cluster System Software/Operating Systems
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 Environment on Clusters
Fault Tolerance and High-availability
Area 4: Data, Storage, and Visualization
Cluster Architecture for Big Data Storage and Processing
Middleware for Big Data Management
Cluster-based Cloud Architecture for Big Data
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 |
