Data centers are critical, energy-hungry infrastructures that run large-scale Internet-based
services. Energy consumption models are pivotal in designing and optimizing energy …

Modern graphics processing units (GPUs) have complex architectures that admit
exceptional performance and energy efficiency for high-throughput applications. Although …

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 …

This paper describes PowerBooter, an automated power model construction technique that
uses built-in battery voltage sensors and knowledge of battery discharge behavior to monitor …

Federated learning enables a cluster of decentralized mobile devices at the edge to
collaboratively train a shared machine learning model, while keeping all the raw training …

This paper proposes and evaluates single-ISA heterogeneous multi-core architectures as a
mechanism to reduce processor power dissipation. Our design incorporates heterogeneous …

With power dissipation becoming an increasingly vexing problem across many classes of
computer systems, measuring power dissipation of real, running systems has become …

As the market for mobile architectures continues its rapid growth, it has become increasingly
important to understand and optimize the power consumption of these battery-driven …

Log files are generated in many different formats by a plethora of devices and software. The
proper analysis of these files can lead to useful information about various aspects of each …

The increasing costs of power delivery and cooling, as well as the trend toward higher-
density computer systems, have created a growing demand for better power management in …