Many-Task Computing: Bridging the Gap between High Throughput Computing and High Performance Computing
Ioan Raicu · 2009
Many-task computing aims to bridge the gap between two computing paradigms, high-throughput computing and high-performance computing. Many-task computing is reminiscent to high-throughput computing, but it differs in the emphasis of using many computing resources over short periods of time to accomplish many computational tasks, where the primary metrics are measured in seconds (e.g. tasks per second, I/O per second), as opposed to operations per month (e.g. jobs per month). Many-task computing denotes high-performance computations comprising of multiple distinct activities, coupled via file system operations. Tasks may be small or large, uniprocessor or multiprocessor, compute-intensive 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