papers

Publications (12)

physics.data-an2017

STAR Data Reconstruction at NERSC/Cori, an adaptable Docker container approach for HPC

Mustafa Mustafa, Jan Balewski, Jérôme Lauret +5

As HPC facilities grow their resources, adaptation of classic HEP/NP workflows becomes a need. Linux containers may very well offer a way to lower the bar to exploiting such resour…

cs.DC2022

The LBNL Superfacility Project Report

Deborah Bard, Cory Snavely, Lisa Gerhardt +24

The Superfacility model is designed to leverage HPC for experimental science. It is more than simply a model of connected experiment, network, and HPC facilities; it encompasses th…

cs.DC2018

Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist

Alex Gittens, Kai Rothauge, Shusen Wang +6

Apache Spark is a popular system aimed at the analysis of large data sets, but recent studies have shown that certain computations---in particular, many linear algebra computations…

cs.DC2016

Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies

Alex Gittens, Aditya Devarakonda, Evan Racah +14

We explore the trade-offs of performing linear algebra using Apache Spark, compared to traditional C and MPI implementations on HPC platforms. Spark is designed for data analytics…

astro-ph.CO2022

Data Preservation for Cosmology

Marcelo Alvarez, Stephen Bailey, Deborah Bard +9

We describe the needs and opportunities for preserving cosmology datasets and simulations, and facilitating their joint analysis beyond the lifetime of individual projects. We reco…

cs.DC2024

Optimizing Checkpoint-Restart Mechanisms for HPC with DMTCP in Containers at NERSC

Madan Timalsina, Lisa Gerhardt, Nicholas Tyler +2

This paper presents an in-depth examination of checkpoint-restart mechanisms in High-Performance Computing (HPC). It focuses on the use of Distributed MultiThreaded CheckPointing (…

hep-ex2020

The use of Convolutional Neural Networks for signal-background classification in Particle Physics experiments

Venkitesh Ayyar, Wahid Bhimji, Lisa Gerhardt +2

The success of Convolutional Neural Networks (CNNs) in image classification has prompted efforts to study their use for classifying image data obtained in Particle Physics experime…

cs.LG2018

Graph Neural Networks for IceCube Signal Classification

Nicholas Choma, Federico Monti, Lisa Gerhardt +7

Tasks involving the analysis of geometric (graph- and manifold-structured) data have recently gained prominence in the machine learning community, giving birth to a rapidly develop…

astro-ph.IM2010

A prototype station for ARIANNA: a detector for cosmic neutrinos

Lisa Gerhardt, Spencer R. Klein, Thorsten Stezelberger +4

The Antarctic Ross Iceshelf Antenna Neutrino Array (ARIANNA) is a proposed detector for ultra-high energy astrophysical neutrinos. It will detect coherent radio Cherenkov emission…

hep-ph2010

Electron and Photon Interactions in the Regime of Strong LPM Suppression

Lisa Gerhardt, Spencer R. Klein

Most searches for ultra-high energy (UHE) astrophysical neutrinos look for radio emission from the electromagnetic and hadronic showers produced in their interactions. The radio fr…

astro-ph.HE2009

Study of High pT Muons in IceCube

Lisa Gerhardt, Spencer Klein

Muons with a high transverse momentum (p_T) are produced in cosmic ray air showers via semileptonic decay of heavy quarks and the decay of high p_T kaons and pions. These high p_T…

cs.DC2018

Alchemist: An Apache Spark <=> MPI Interface

Alex Gittens, Kai Rothauge, Shusen Wang +6

The Apache Spark framework for distributed computation is popular in the data analytics community due to its ease of use, but its MapReduce-style programming model can incur signif…