Scheduling and planning job execution of loosely coupled applications

作者：Afgan Enis^*; Bangalore Purushotham; Skala Tibor

来源：Journal of Supercomputing, 2012, 59(3): 1431-1454.

DOI：10.1007/s11227-011-0555-y

• Distributed architectures
• Load balancing and task assignment
• Scheduling and task partitioning
• User interfaces

Growth in availability of data collection devices has allowed individual researchers to gain access to large quantities of data that needs to be analyzed. As a result, many labs and departments have acquired considerable compute resources. However, effective and efficient utilization of those resources remains a barrier for the individual researchers because the distributed computing environments are difficult to understand and control. We introduce a methodology and a tool that automatically manipulates and understands job submission parameters to realize a range of job execution alternatives across a distributed compute infrastructure. Generated alternatives are presented to a user at the time of job submission in the form of tradeoffs mapped onto two conflicting objectives, namely job cost and runtime. Such presentation of job execution alternatives allows a user to immediately and quantitatively observe viable options regarding their job execution, and thus allows the user to interact with the environment at a true service level. Generated job execution alternatives have been tested through simulation and on real-world resources and, in both cases, the average accuracy of the runtime of the generated and perceived job alternatives is within 5%.

• 出版日期2012-3