Scheduling speculative tasks in a compute farm

Users often behave speculatively, submitting work that initially they do not know is needed. Farm computing often consists of single node speculative tasks issued by, e.g., bioinformaticists comparing dna sequences and computer graphics artists rendering scenes who wish to reduce their time waiting for needed tasks and the amount they will be charged for unneeded speculation. Existing schedulers are not effective for such behavior. Our ‘batchactive’ scheduling exploits speculation: users submit explicitlylabeled batches of speculative tasks, interactively request outputs when ready to process them, and cancel tasks found not to be needed. Users are encouraged to participate by a new pricing mechanism charging for only requested tasks no matter what ran. Over a range of simulated user and task characteristics, we show that: batchactive scheduling improves visible response time - a new metric for speculative domains - by at least 2X for 20% of the simulations; batchactive scheduling supports higher billable load at lower visible response time, encouraging adoption by resource providers; and a batchactive policy favoring users who use more of their speculative tasks provides additional performance and resists a denialof- service.