Power and energy efficiency are now critical concerns in extreme-scale high-performance
scientific computing. Many extreme-scale computing systems today (for example: Top500) …

We describe an energy-based analogue of the time-based roofline model. We create this
model from the perspective of algorithm designers and performance tuners, with the intent …

We propose an image classification framework by leveraging the non-negative sparse
coding, low-rank and sparse matrix decomposition techniques (LR-Sc+ SPM). First, we …

Power dissipation is becoming the most challenging design constraint in nanometer
technologies. Among various design implementation schemes, standard cell ASICs offer the …

There is growing interest to replace traditional servers with low-power multicore systems
such as ARM Cortex-A9. However, such systems are typically provisioned for mobile …

Compute intensive kernels make up the majority of execution time in HPC applications.
Therefore, many of the power draw and energy consumption traits of HPC applications can …

Understanding on-node application power and performance characteristics is critical to the
push toward exascale computing. In this paper, we present an analysis of factors that impact …

Energy efficiency in high performance computing (HPC) will be critical to limit operating
costs and carbon footprints in future supercomputing centers. Energy efficiency of a …

We examine the scalability of a set of techniques related to Dynamic Voltage-Frequency
Scaling (DVFS) on HPC systems to reduce the energy consumption of scientific applications …

Energy predictive modeling is the leading method for determining the energy consumption
of an application. Performance monitoring counters (PMCs) and resource utilizations have …