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Many-Task Computing for Grids and Supercomputers
| Content Provider | CiteSeerX |
|---|---|
| Author | Raicu, Ioan Foster, Ian T. Zhao, Yong |
| Description | Many-task computing aims to bridge the gap between two computing paradigms, high throughput computing and high performance computing. Many task computing differs from high throughput computing in the emphasis of using large number of computing resources over short periods of time to accomplish many computational tasks (i.e. including both dependent and independent tasks), where primary metrics are measured in seconds (e.g. FLOPS, tasks/sec, MB/s I/O rates), as opposed to operations (e.g. jobs) per month. Many task computing denotes high-performance computations comprising multiple distinct activities, coupled via file system operations. Tasks may be small or large, uniprocessor or multiprocessor, computeintensive or data-intensive. The set of tasks may be static or dynamic, homogeneous or heterogeneous, loosely coupled or tightly coupled. The aggregate number of tasks, quantity of computing, and volumes of data may be extremely large. Many task computing includes loosely coupled applications that are generally communication-intensive but not naturally expressed using standard message passing interface commonly found in high performance computing, drawing attention to the many computations that are heterogeneous but not “happily ” parallel. IEEE Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS08) 2008 |
| File Format | |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | High Throughput Many Computation Many Computational Task High Performance Computing File System Operation High Performance Short Period Denotes High-performance Computation Many-task Computing Large Number Multiple Distinct Activity Standard Message Aggregate Number Independent Task Primary Metric Many Task |
| Content Type | Text |
| Resource Type | Article |
