A survey of power and energy predictive models in HPC systems and applications
Power and energy efficiency are now critical concerns in extreme-scale high-performance
scientific computing. Many extreme-scale computing systems today (for example: Top500) …
scientific computing. Many extreme-scale computing systems today (for example: Top500) …
A survey of communication performance models for high-performance computing
This survey aims to present the state of the art in analytic communication performance
models, providing sufficiently detailed descriptions of particularly noteworthy efforts …
models, providing sufficiently detailed descriptions of particularly noteworthy efforts …
A comparative study of methods for measurement of energy of computing
Energy of computing is a serious environmental concern and mitigating it is an important
technological challenge. Accurate measurement of energy consumption during an …
technological challenge. Accurate measurement of energy consumption during an …
Bi-objective optimization of data-parallel applications on heterogeneous HPC platforms for performance and energy through workload distribution
Performance and energy are the two most important objectives for optimization on modern
parallel platforms. In this article, we show that moving from single-objective optimization for …
parallel platforms. In this article, we show that moving from single-objective optimization for …
Bi-objective optimization of data-parallel applications on homogeneous multicore clusters for performance and energy
Performance and energy are now the most dominant objectives for optimization on modern
parallel platforms composed of multicore CPU nodes. The existing intra-node and inter-node …
parallel platforms composed of multicore CPU nodes. The existing intra-node and inter-node …
SYnergy: Fine-grained Energy-Efficient Heterogeneous Computing for Scalable Energy Saving
Energy-efficient computing uses power management techniques such as frequency scaling
to save energy. Implementing energy-efficient techniques on large-scale computing systems …
to save energy. Implementing energy-efficient techniques on large-scale computing systems …
A novel data-partitioning algorithm for performance optimization of data-parallel applications on heterogeneous HPC platforms
Modern HPC platforms have become highly heterogeneous owing to tight integration of
multicore CPUs and accelerators (such as Graphics Processing Units, Intel Xeon Phis, or …
multicore CPUs and accelerators (such as Graphics Processing Units, Intel Xeon Phis, or …
Scission: Performance-driven and context-aware cloud-edge distribution of deep neural networks
L Lockhart, P Harvey, P Imai, P Willis… - 2020 IEEE/ACM 13th …, 2020 - ieeexplore.ieee.org
Partitioning and distributing deep neural networks (DNNs) across end-devices, edge
resources and the cloud has a potential twofold advantage: preserving privacy of the input …
resources and the cloud has a potential twofold advantage: preserving privacy of the input …
Energy-efficient parallel computing: Challenges to scaling
The energy consumption of Information and Communications Technology (ICT) presents a
new grand technological challenge. The two main approaches to tackle the challenge …
new grand technological challenge. The two main approaches to tackle the challenge …
Energy predictive models of computing: theory, practical implications and experimental analysis on multicore processors
The energy efficiency in ICT is becoming a grand technological challenge and is now a first-
class design constraint in all computing settings. Energy predictive modelling based on …
class design constraint in all computing settings. Energy predictive modelling based on …