Lisa Gerhardt

According to our database1, Lisa Gerhardt authored at least 14 papers between 2013 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2022
The LBNL Superfacility Project Report.
CoRR, 2022

2021
ALS Share, a Lightweight Data Sharing Service for a Synchrotron Radiation Facility.
Proceedings of the 3rd Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing, 2021

2020
Cross-facility science with the Superfacility Project at LBNL.
Proceedings of the 2nd IEEE/ACM Annual Workshop on Extreme-scale Experiment-in-the-Loop Computing, 2020

2019
Alchemist: An Apache Spark ⇔ MPI interface.
Concurr. Comput. Pract. Exp., 2019

A Quantitative Approach to Architecting All-Flash Lustre File Systems.
Proceedings of the High Performance Computing, 2019


2018
Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Graph Neural Networks for IceCube Signal Classification.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

2016
Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies.
CoRR, 2016

Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015
The IceProd framework: Distributed data processing for the IceCube neutrino observatory.
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J. Parallel Distributed Comput., 2015

2014
Adventures in Antarctic Computing, or How I Learned to Stop Worrying and Love the Neutrino.
Computer, 2014

Cori: A Pre-Exascale Supercomputer for Big Data and HPC Applications.
Proceedings of the Big Data and High Performance Computing, 2014

2013
Extreme Data Science at the National Energy Research Scientific Computing (NERSC) Center.
Proceedings of the Parallel Computing: Accelerating Computational Science and Engineering (CSE), 2013


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