Autotasked Performance in the NAS Workload: A Statistical Analysis

A statistical analysis of the workload performance of a production quality FORTRAN code for five different Cray Y-MP hardware and system software configurations is performed. The analysis was based on an experimental procedure that was designed to minimize correlations between the number of requested CPUs and the time of day the runs were initiated. Observed autotasking over heads were significantly larger for the set of jobs that requested the maximum number of CPUs. Speedups for UNICOS 6 releases show consistent wall clock speedups in the workload of around 2. which is quite good. The observed speed ups were very similar for the set of jobs that requested 8 CPUs and the set that requested 4 CPUs. The original NAS algorithm for determining charges to the user discourages autotasking in the workload. A new charging algorithm to be applied to jobs run in the NQS multitasking queues also discourages NAS users from using auto tasking. The new algorithm favors jobs requesting 8 CPUs over those that request less, although the jobs requesting 8 CPUs experienced significantly higher over head and presumably degraded system throughput. A charging algorithm is presented that has the following desirable characteristics when applied to the data: higher overhead jobs requesting 8 CPUs are penalized when compared to moderate overhead jobs requesting 4 CPUs, thereby providing a charging incentive to NAS users to use autotasking in a manner that provides them with significantly improved turnaround while also maintaining system throughput.