Mark Sandstrom

Improving application program performance will require parallelizing the program execution at ever finer granularity now that the processor clock rates are no longer increasing. However, even in a per-application dedicated computing environment, the parallelization overhead is known to place a limit on how much application on-time throughput performance increase can be achieved via higher levels of parallel processing. The throughput-limiting impact of parallelization overhead will be significantly amplified when executing multiple internally parallelized applications on dynamically shared cloud computing environment, since the allocation of processing resources to instances and tasks of any given application cannot be done in isolation, but instead it needs to be done collectively across all the applications dynamically sharing the given pool of computing resources... (more)