ThunderX2 Performance and Energy-Efficiency for HPC Workloads

Energy-Efficiency Evaluation of Intel KNL for HPC Workloads

Energy consumption is increasingly becoming a limiting factor to the design of faster large-scale parallel systems, and development of energy-efficient and energy-aware applications is today a relevant issue for HPC code-developer communities. In this work we focus on energy performance of the Knights Landing (KNL) Xeon Phi, the latest many-core architecture processor introduced by Intel for th...

Energy Efficiency in Hpc Systems

1.1 INTRODUCTION Power consumption of High Performance Computing (HPC) platforms is becoming a major concern for a number of reasons including cost, reliability, energy conservation, and environmental impact. High-end HPC systems today consume several megawatts of power, enough to power small towns, and are in fact, soon approaching the limits of the power available to them. For example, the Cr...

Understanding Emerging Workloads for Performance and Energy

The Case For Colocation of HPC Workloads

The current state of practice in supercomputer resource allocation places jobs from different users on disjoint nodes both in terms of time and space. While this approach largely guarantees that jobs from different users do not degrade one another’s performance, it does so at high cost to system throughput and energy efficiency. This focused study presents job striping, a technique that signifi...

Hadoop Workloads Characterization for Performance and Energy Efficiency Optimizations on Microservers

The traditional low-power embedded processors such as Atom and ARM are entering into the high-performance server market. At the same time, big data analytics applications are emerging and dramatically changing the landscape of data center workloads. Emerging big data applications require a significant amount of server computational power. However, the rapid growth in the data yields challenges ...