English
Related papers

Related papers: Performance of an Operating High Energy Physics Da…

200 papers

High Performance Computing is an internet based computing which makes computer infrastructure and services available to the user for research purpose. However, an important issue which needs to be resolved before High Performance Computing…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-13 Vivek Chalotra , Anju Bhasin , Anik Gupta , Sanjeev Singh Sambyal , Sanjay Mahajan

The CDF and D0 collaborations at Fermilab's Tevatron p-pbar collider have in place an extensive program to measure fundamental properties of the top quark. Recent results from Run I (sqrt-s = 1.8 TeV) and Run II (sqrt-s = 1.96 TeV) on the…

High Energy Physics - Experiment · Physics 2010-04-22 Andy Hocker

FASER, the ForwArd Search ExpeRiment, is a proposed experiment dedicated to searching for light, extremely weakly-interacting particles at the LHC. Such particles may be produced in the LHC's high-energy collisions in large numbers in the…

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth makes it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-05-28 Jieyang Chen , Lipeng Wan , Xin Liang , Ben Whitney , Qing Liu , Qian Gong , David Pugmire , Nicholas Thompson , Jong Youl Choi , Matthew Wolf , Todd Munson , Ian Foster , Scott Klasky

Deep learning techniques have evolved rapidly in recent years, significantly impacting various scientific fields, including experimental particle physics. To effectively leverage the latest developments in computer science for particle…

Machine Learning · Computer Science 2025-01-14 Timo Saala , Matthias Schott

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-02 Jieyang Chen , Lipeng Wan , Xin Liang , Ben Whitney , Qing Liu , David Pugmire , Nicholas Thompson , Matthew Wolf , Todd Munson , Ian Foster , Scott Klasky

Energy costs are quickly rising in large-scale data centers and are soon projected to overtake the cost of hardware. As a result, data center operators have recently started turning into using more energy-friendly hardware. Despite the…

Databases · Computer Science 2009-09-15 Stavros Harizopoulos , Mehul Shah , Justin Meza , Parthasarathy Ranganathan

Earth observation (EO) data volumes are rapidly increasing. While cloud computing are now used for processing large EO datasets, the energy efficiency aspects of such a processing have received much less attention. This issue is notable…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-06 Adhitya Bhawiyuga , Serkan Girgin , Rolf A. de By , Raul Zurita-Milla

We summarize the status of Deep Underground Neutrino Experiment (DUNE) Offline Software and Computing program. We describe plans for the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from…

Accelerator Physics · Physics 2023-12-19 Michael Kirby

This paper describes the design, fabrication, installation and performance of the new inner layer called Layer 0 (L0) that was inserted in the existing Run IIa Silicon Micro-Strip Tracker (SMT) of the D0 experiment at the Fermilab Tevatron…

Despite constant improvements in efficiency, today's data centers and networks consume enormous amounts of energy and this demand is expected to rise even further. An important research question is whether and how fog computing can curb…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-02 Philipp Wiesner , Lauritz Thamsen

Composed of a large variety of technologies and applications with unprecedented complexity, the smart grid, as a cyber-physical energy system, needs careful investigation of the interactions between the various domains involved, especially…

Systems and Control · Computer Science 2018-12-27 Van Hoa Nguyen , Yvon Besanger , Quoc Tuan Tran , Cédric Boudinnet , Tung Lam Nguyen , Ron Brandl , Thomas I. Strasser

Accurate and fast simulation of particle physics processes is crucial for the high-energy physics community. Simulating particle interactions with detectors is both time consuming and computationally expensive. With the proton-proton…

High Energy Physics - Experiment · Physics 2021-08-26 Ali Hariri , Darya Dyachkova , Sergei Gleyzer

HEPCloud is rapidly becoming the primary system for provisioning compute resources for all Fermilab-affiliated experiments. In order to reliably meet the peak demands of the next generation of High Energy Physics experiments, Fermilab must…

The Grist project (http://grist.caltech.edu/) is developing a grid-technology based system as a research environment for astronomy with massive and complex datasets. This knowledge extraction system will consist of a library of distributed…

These lectures contain an introduction to the search for supersymmetry at hadron colliders. The Tevatron is one of high-energy physics most sophisticated tools. The high center-of-mass energy of its proton-antiproton collisions makes it an…

High Energy Physics - Experiment · Physics 2007-05-23 Stephan Lammel

The Tevatron Run-II started data-taking in spring 2001 and several searches for new particles have been performed. The preliminary 2005 results are concisely reviewed for the experiments CDF and D0. Model-independent and model-dependent…

High Energy Physics - Phenomenology · Physics 2007-05-23 Andre Sopczak

Run 2 of the Tevatron collider at Fermilab has begun in the spring of 2001. During its first year of operation the Tevatron has delivered a luminosity of approximately 30/pb to the Dzero experiment. These data have been used to commission…

High Energy Physics - Experiment · Physics 2007-05-23 M. Verzocchi

Data-intensive science is increasingly reliant on real-time processing capabilities and machine learning workflows, in order to filter and analyze the extreme volumes of data being collected. This is especially true at the energy and…

Artificial Intelligence · Computer Science 2021-04-21 Chinmaya Mahesh , Kristin Dona , David W. Miller , Yuxin Chen

The Durham High Energy Physics Database (HEPData) has been built up over the past four decades as a unique open-access repository for scattering data from experimental particle physics papers. It comprises data points underlying several…

High Energy Physics - Experiment · Physics 2017-11-23 Eamonn Maguire , Lukas Heinrich , Graeme Watt