[HTML][HTML] Estimation of energy consumption in machine learning
Energy consumption has been widely studied in the computer architecture field for decades.
While the adoption of energy as a metric in machine learning is emerging, the majority of …
While the adoption of energy as a metric in machine learning is emerging, the majority of …
Benchmarking 6dof outdoor visual localization in changing conditions
Visual localization enables autonomous vehicles to navigate in their surroundings and
augmented reality applications to link virtual to real worlds. Practical visual localization …
augmented reality applications to link virtual to real worlds. Practical visual localization …
A survey on run-time power monitors at the edge
Effectively managing energy and power consumption is crucial to the success of the design
of any computing system, helping mitigate the efficiency obstacles given by the downsizing …
of any computing system, helping mitigate the efficiency obstacles given by the downsizing …
Predictive reliability and fault management in exascale systems: State of the art and perspectives
Performance and power constraints come together with Complementary Metal Oxide
Semiconductor technology scaling in future Exascale systems. Technology scaling makes …
Semiconductor technology scaling in future Exascale systems. Technology scaling makes …
Deep learning for EEG-based Motor Imagery classification: Accuracy-cost trade-off
Electroencephalography (EEG) datasets are often small and high dimensional, owing to
cumbersome recording processes. In these conditions, powerful machine learning …
cumbersome recording processes. In these conditions, powerful machine learning …
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 …
Energy‐aware high‐performance computing: survey of state‐of‐the‐art tools, techniques, and environments
The paper presents state of the art of energy‐aware high‐performance computing (HPC), in
particular identification and classification of approaches by system and device types …
particular identification and classification of approaches by system and device types …
New model-based methods and algorithms for performance and energy optimization of data parallel applications on homogeneous multicore clusters
A Lastovetsky, RR Manumachu - IEEE Transactions on Parallel …, 2016 - ieeexplore.ieee.org
Modern homogeneous parallel platforms are composed of tightly integrated multicore CPUs.
This tight integration has resulted in the cores contending for various shared on-chip …
This tight integration has resulted in the cores contending for various shared on-chip …
A comprehensive exploration of languages for parallel computing
Software-intensive systems in most domains, from autonomous vehicles to health, are
becoming predominantly parallel to efficiently manage large amount of data in short (even …
becoming predominantly parallel to efficiently manage large amount of data in short (even …