Improving Processor Allocation through Run-Time Measured Efficiency

In a multiprocessor architecture it is very important to allocate processors to applications in a proportional way to the performance that applications are achieving. Not considering this performance can result in an under-utilization of the multiprocessor, and also it can slowdown the execution time of parallel applications. However, the performance of parallel applications is not known before their execution. In this work, we propose to use dynamically measured application efficiency of OpenMP applications to improve the performance of two scheduling policies proposed so far, the equipartition and the equal_efficiency. The modified scheduling policies will request parallel applications to achieve a target_efficiency to receive more processors. We refer to the modified equipartition and equal_efficiency as equip++ and equal_eff++. We also propose to use a dynamic multiprogramming level to avoid the under-utilization of the machine introduced by these new scheduling policies when using a static multiprogramming level. We have evaluated this work by executing several workloads in a SGI Origin2000 with 64 processors. Results show that the combination of (target_efficiency+dynamic multiprogramming level) achieves, in the worst case, the same performance as the equipartition and the equal_efficiency, and in the best case it achieves a speedup of up to 1.3 in individual applications, and in specific workloads a speedup of up to 2.5, respect to the original algorithms