by Ioan Raicu, Ian Foster and Yong Zhao, published at International Science Grid This Week
“Tightly-coupled applications for which jobs must communicate between each other during execution are typically best served by clustered High Performance Computing (HPC). Applications with many independent job streams, on the other hand, are better suited to distributed High Throughput Computing (HTC). But there are still other kinds of applications.
Over the past half decade we’ve examined many applications from astrophysics, bioinformatics, data mining and other fields, and have found that high-performance computations comprising multiple distinct activities and coupled via file system operations (as opposed to the standard message passing interface commonly found in HPC) don’t fit nicely in either category. To address this, we’ve defined the concept of “Many Task Computing”. We believe that it bridges a gap between these two dominant computing paradigms and opens up opportunities to apply HPC systems in new ways for increasingly complex applications that were simply intractable just a few years ago.”
