Abstract
Tigres provides a programming library to compose and execute large-scale data-intensive scientific workflows from desktops to supercomputers. DOE User Facilities and large science collaborations are increasingly generating large enough data sets that it is no longer practical to download them to a desktop to operate on them. They are instead stored at centralized compute and storage resources such as high performance computing (HPC) centers. Analysis of this data requires an ability to run on these facilities, but with current technologies, scaling an analysis to an HPC center and to a large data set is difficult even for experts. Tigres is addressing the challenge of enabling collaborative analysis of DOE Science data through a new concept of reusable "templates" that enable scientists to easily compose, run and manage collaborative computational tasks. These templates define common computation patterns used in analyzing a data set.
- Release Date:
- 2017-04-28
- Project Type:
- Open Source, No Publicly Available Repository
- Software Type:
- Scientific
- Licenses:
-
Other (Commercial or Open-Source): https://dst.lbl.gov/ACSSoftware/tigres/docs/tigres-0.2.0/license_agreement.html
- Sponsoring Org.:
-
USDOEPrimary Award/Contract Number:AC02-05CH11231
- Code ID:
- 55037
- Site Accession Number:
- 7478; 2016-147
- Research Org.:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
- Country of Origin:
- United States
Citation Formats
Ramakrishnan, Lavanya, Gunter, Daniel, Pastorello, Gilerto Z., Hendrix, Valerie, Fox, James, Rodrigo Alvarez, Gonzalo P., Kushner, Gary, Rodriguez, Ryan, and Agarwal, Deborah A.
Template Interfaces for Agile Parallel Data-Intensive Science.
Computer Software.
USDOE.
28 Apr. 2017.
Web.
doi:10.11578/dc.20210416.85.
Ramakrishnan, Lavanya, Gunter, Daniel, Pastorello, Gilerto Z., Hendrix, Valerie, Fox, James, Rodrigo Alvarez, Gonzalo P., Kushner, Gary, Rodriguez, Ryan, & Agarwal, Deborah A.
(2017, April 28).
Template Interfaces for Agile Parallel Data-Intensive Science.
[Computer software].
https://doi.org/10.11578/dc.20210416.85.
Ramakrishnan, Lavanya, Gunter, Daniel, Pastorello, Gilerto Z., Hendrix, Valerie, Fox, James, Rodrigo Alvarez, Gonzalo P., Kushner, Gary, Rodriguez, Ryan, and Agarwal, Deborah A.
"Template Interfaces for Agile Parallel Data-Intensive Science." Computer software.
April 28, 2017.
https://doi.org/10.11578/dc.20210416.85.
@misc{
doecode_55037,
title = {Template Interfaces for Agile Parallel Data-Intensive Science},
author = {Ramakrishnan, Lavanya and Gunter, Daniel and Pastorello, Gilerto Z. and Hendrix, Valerie and Fox, James and Rodrigo Alvarez, Gonzalo P. and Kushner, Gary and Rodriguez, Ryan and Agarwal, Deborah A.},
abstractNote = {Tigres provides a programming library to compose and execute large-scale data-intensive scientific workflows from desktops to supercomputers. DOE User Facilities and large science collaborations are increasingly generating large enough data sets that it is no longer practical to download them to a desktop to operate on them. They are instead stored at centralized compute and storage resources such as high performance computing (HPC) centers. Analysis of this data requires an ability to run on these facilities, but with current technologies, scaling an analysis to an HPC center and to a large data set is difficult even for experts. Tigres is addressing the challenge of enabling collaborative analysis of DOE Science data through a new concept of reusable "templates" that enable scientists to easily compose, run and manage collaborative computational tasks. These templates define common computation patterns used in analyzing a data set.},
doi = {10.11578/dc.20210416.85},
url = {https://doi.org/10.11578/dc.20210416.85},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20210416.85}},
year = {2017},
month = {apr}
}