Related papers: Computing for the Energy Frontier: Snowmass Study …

We summarize the community-based consensus for improvements concerning education, public outreach, and inclusion in Accelerator Science and Engineering that will enhance the workforce in the USA. The improvements identified reflect the…

The rapid growth in demand for HPC systems has led to a rise in carbon footprint, which requires urgent intervention. In this work, we present a comprehensive analysis of the carbon footprint of high-performance computing (HPC) systems,…

An essential companion to the development and advancement of the field of Particle Physics is a strong program in physics education at all levels, that can attract entry level students across the full demographic spectrum and provide them…

Workload characterization is an integral part of performance analysis of high performance computing (HPC) systems. An understanding of workload properties sheds light on resource utilization and can be used to inform performance…

With the increasing interplay between experimental and computational approaches at multiple length scales, new research directions are emerging in materials science and computational mechanics. Such cooperative interactions find many…

Driven by the visions of Internet of Things and 5G communications, the edge computing systems integrate computing, storage and network resources at the edge of the network to provide computing infrastructure, enabling developers to quickly…

This thesis presents a novel framework for analysing the societal impacts of armed conflict by applying principles from engineering and material science. Building on the idea of a "social fabric", it recasts communities as plates with…

In 2022, the National Science Foundation (NSF) funded the Computing Research Association (CRA) to conduct a workshop to frame and scope a potential Convergence Accelerator research track on the topic of "Building Resilience to…

This letter is my comment about the opinion paper: Transdisciplinary electric power grid science (PNAS, 2013 - http://www.pnas.org/content/110/30/12159.full). [arXiv:1307.7305].

This writeup summarizes the work of the Topical Working Group 7 of the Instrumentation Frontier group of the Snowmass 2021 process. Group 'IF07' dealt with issues pertaining to ASICs and Readout Electronics. The community efforts as part of…

Energy cost is increasingly crucial in the modern computing industry with the wide deployment of large-scale machine learning models and language models. For the firms that provide computing services, low energy consumption is important…

Functions as a Service has emerged as a popular abstraction for a wide range of cloud applications and an important cloud workload. We present the design and implementation of FaasMeter, a FaaS control plane which provides energy…

Cosmological observations in the new millennium have dramatically increased our understanding of the Universe, but several fundamental questions remain unanswered. This topical group report describes the best opportunities to address these…

The pursuit of energy transition necessitates the coordination of several technologies, including more efficient and cost-effective distributed energy resources (DERs), smart grids, carbon capture, utilization, and storage (CCUS),…

Much work has been dedicated to estimating and optimizing workloads in high-performance computing (HPC) and deep learning. However, researchers have typically relied on few metrics to assess the efficiency of those techniques. Most notably,…

We present a new method for estimating the frontier of a multidimensional sample. The estimator is based on a kernel regression on the power-transformed data. We assume that the exponent of the transformation goes to infinity while the…

While extensive research over the past decades has been dedicated to developing scalable quantum computers, the question of their energetic performance has only gained attention more recently, but its importance is now recognized. In fact,…

Machine learning (ML) has seen tremendous advancements, but its environmental footprint remains a concern. Acknowledging the growing environmental impact of ML this paper investigates Green ML, examining various model architectures and…

We review the problem of dark energy, including a survey of theoretical models and some aspects of numerical studies.

The Snowmass 2021 Accelerator Frontier topical group \# 6 on Advanced Accelerator Concepts, covers new R\&D concepts for particle acceleration, generation, and focusing. Based on community input, this report describes how leveraging these…