Download as PDF, PPTX
Uploaded byGlobus
Recent Upgrades to ARM Data Transfer and Delivery Using Globus
The document discusses upgrades to the Atmospheric Radiation Measurement (ARM) facility's data center for improving data transfer and delivery using Globus and ESnet networks. It details the data growth, disaster recovery processes, and data science facilitation through effective data processing, storage, and retrieval. The ARM initiative aims to enhance climate and earth system models while providing users with tools for data discovery and analytics.
More Related Content
Similar to Recent Upgrades to ARM Data Transfer and Delivery Using Globus
Recent Upgrades to ARM Data Transfer and Delivery Using Globus
- 1. May 6, 20191 Improving Data Transfer and Delivery using Globus Recent Upgrades to The Atmospheric Radiation Measurement (ARM) Facility Data Center Architecture GIRI PRAKASH, ZACH PRICE, JOSEPH OLATT, AND JITU KUMAR ARM Data Center, Oak Ridge National Laboratory Globus World, May 01, 2019 palanisamyg@ornl.gov
- 2. ARM’s Vision 2 To providea detailed & accurate description of the earth atmosphere in diverse climate regimes to resolve the uncertainties in climate and earth system models toward the development of sustainable solutions for the Nation’s energy & environmental challenges.
- 3. ARM Data Flow– The Big Picture Data Growth 1 PB 3
- 4. ARM Data –Disaster Recovery Offsite Data backup ARM Data files that are copied into the ORNL HPSS system at ORNL are also copied over to the HPSS system at ANL. The Globus-URL-copy program and the ESnet network between the two labs are utilized for this purpose. ■ Date copying to ANL started: 03-26-2018 ■ Total size transferred: 188.03 TB ■ Total number of files transferred: 3,938,465 4
- 5. Data Transfer andStaging to Facilitate Data Science 5
- 6. Data Transfer andStaging to Facilitate Data Science 6
- 7. Data Pipeline andSoftware Architecture May 6, 2019 7 Data Processing Storage & Data Model Querying Analytics Scientific Users Data Pipeline Software Architecture Interface Visualization Analytics Output Spark ARM HPC Computing Clusters JupyterLab Relational Database NoSQL Database • Supports fast analysis of voluminous data • Hides architectural complexities • Stage data in HPC • Metadata • Order History • Data from multiple instruments Frontend Analytic Server Backend Dr.Bhargavi Krishna, Yuping Lu, and Dr.Jitu Kumar 7
- 8. Data Retrieval, Packaging,and Delivery § Merging § DQR filtering § Conversion Retrieval Future capability Data- streams HPSS Online copy Link to data access Data quality Access to plots DOI based citation guidance Publication request Discovery UI & Web services NetCDF data extractions Data staging order Live Data WS 8
- 9.
- 10. 10 § Based onbig data analysis platform (NoSQL) § ARM HPC Clusters for data processing § Provides an interactive web interface for users to find simulations of interest through examination of the LES performance relative to select ARM observations § Allows user to visualize LASSO data bundle diagnostics and skill scores on the fly using plots and tables § Globus as a delivery option Cassandra D3 & NodeJS Spark Data Discovery for LASSO
- 11. Questions? 5/6/19 11 ARM DataServices Giri Prakash palanisamyg@ornl.gov