Understanding Emerging Workloadsfor Performance and Energy

The size and capacity of datacenters has grown over time, and today, datacentershave become a significant source for compute capacity. This is because the type, aswell as the number of applications and users that are moving into the cloud have beensteadily increasing. As datacenter use increases, so does the energy consumed bythese large computing facilities. Therefore, by improving datacenter efficiency, one cansignificantly reduce datacenter cost.In order to achieve improved datacenter efficiency, the hardware and softwarebottlenecks that exists in today's software need to be identified and evaluated. In thiswork a number of popular datacenter workloads using the Top-Down methodologywas evaluated with the aim to use it to better understand the bottlenecks andbehavior of these workloads. The goal of this work is to determine if the applicationsshow any time-varying behavior and if there are any potential for improvements ofthe hardware with respect to energy efficiency. The proposed methodology workswell for understanding high level bottlenecks on modern hardware. We identifiedtime-varying behavior as well as areas of improvement common to several studiedapplications