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									       IEEE Transactions on
 Parallel and Distributed Systems
         Special Issue on Many-Task Computing
                       The Special Issue on Many-Task Computing (MTC) will provide the scientific
                       community a dedicated forum, within the prestigious IEEE Transactions on
                       Parallel and Distributed Systems Journal, for presenting new research,
                       development, and deployment efforts of loosely coupled large scale
                       applications on large scale clusters, Grids, Supercomputers, and Cloud
                       Computing infrastructure. MTC, the focus of the special issue, encompasses
                       loosely coupled applications, which are generally composed of many tasks
                       (both independent and dependent tasks) to achieve some larger application
                       goal. This special issue will cover challenges that can hamper efficiency and
                       utilization in running applications on large-scale systems, such as local
                       resource manager scalability and granularity, efficient utilization of the raw
                       hardware, parallel file system contention and scalability, data management, I/
                       O management, reliability at scale, and application scalability. We welcome
                       paper submissions on all topics related to MTC on large scale systems.
                                                      • Compute Resource Management in large scale clusters,
                                                        large Grids, Supercomputers, and Cloud Computing
                                                            ◊ Scheduling
                                                            ◊ Job execution frameworks
Special Issue Guest Editors                                 ◊ Local resource manager extensions
                                                            ◊ Performance evaluation of resource managers in use
Ian Foster                                                     on large scale systems
                                                            ◊ Challenges in running many-task workloads on HPC
         University of Chicago                                 systems
                                                            ◊ Challenges in running many-task workloads on
         Argonne National Laboratory                           Cloud Computing Infrastructure
                                                      • Data Management in large scale Grid and Supercomputer
Ioan Raicu                                              environments:
         Northwestern University                            ◊ Data-Aware Scheduling
                                                            ◊ Shared File System performance and scalability in
Yong Zhao                                                      large deployments
                                                            ◊ Distributed file systems
         Microsoft                                          ◊ Data caching frameworks and techniques
                                                      • Large-Scale Workflow Systems
Web Site:              ◊ Workflow system performance and scalability
Contact: Ioan Raicu at            analysis
          Yong Zhao at                  ◊ Scalability of workflow systems
                                                            ◊ Workflow infrastructure and e-Science middleware
                                                            ◊ Programming Paradigms and Models
   Important Dates                                    • Large-Scale Many-Task Applications
                                                            ◊ Large-scale many-task applications
   Abstracts: December 14th, 2009                           ◊ Large-scale many-task data-intensive applications
   Papers: December 21st, 2009                              ◊ Large-scale high throughput computing (HTC)
   Notifications: February 22nd, 2010                          applications
                                                            ◊ Quasi-supercomputing applications, deployments,
   Publication Date: November, 2010                            and                          experiences

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