By Tommy Minyard and Dan Stanzione, Texas Advanced Computing Center
Intel has continued to increase core count with the introduction of the Westmere processor, and upcoming processors will feature both more bandwidth and more cores (as will processors in competing lines). These changes will mean an overall improvement, of course, but also will require some deeper thinking about performance to figure out how to configure your applications to get maximum performance per socket.

“Conventional Wisdom” has always held that as you get more cores, you run more tasks. In fact, you run exactly as many tasks (or threads) as you have cores. Leaving a core idle is considered “wasteful”. This is not surprising, but upon careful reflection doesn’t make that much sense… No one considers it a “waste” if while running a job on every core of your machine, half your memory is empty, or half your network is unused, or you are only using half the available IOPS or bandwidth to your disk drive.

No one considers these resources “underutilized” in most situations partially because they aren’t as visible, but mostly simply because they aren’t what you think of as your measure of productivity. In fact, you should measure how productive your cluster (or even workstation) is by, well, how much work you produce. Productivity, like performance, is seldom as straightforward as a single benchmark, so there are several measures you can use to think about productivity. It might be how many jobs your cluster does in a given time (hour, day, year). It might be how fast *your* job runs on your cluster. For the sake of argument on this post, let’s assume you use a cluster because you want to run big jobs that require a cluster… jobs that use multiple cores on a node, and may use multiple cores on multiple nodes. So, let’s further assume that the metric we want to maximize for productivity is making these multi-core jobs run as fast and efficiently as they can on your hardware.

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