The Pacific Research Platform enables distributed big data machine learning by connecting scientific instruments, sensors, and supercomputers across California and the United States with high-speed optical networks. Key components include FIONA data transfer nodes that allow fast disk-to-disk transfers near the theoretical maximum, Kubernetes to orchestrate distributed computing resources, and the Nautilus hypercluster which aggregates thousands of CPU cores and GPUs into a unified platform. This infrastructure has accelerated many scientific workflows and supported cutting-edge research in fields such as astronomy, oceanography, climate science, and particle physics.
The Pacific Research Platform: Building a Distributed Big-Data Machine-Learni...
The document summarizes the Pacific Research Platform (PRP) which connects researchers across multiple universities with high-speed networks and computing resources for big data and machine learning applications. Key points:
- PRP connects 15 universities with optical networks, distributed storage devices (FIONAs), and over 350 GPUs for data analysis and AI training.
- It allows researchers to rapidly share and analyze large datasets, with one example reducing a workflow from 19 days to 52 minutes.
- Other projects using PRP resources include climate modeling, astrophysics simulations, and machine learning courses involving thousands of students.
Internet & Climate Change: Cyberinfrastructure for a Carbon-Constrained World
- Internet and information technologies (ICT) can play a key role in addressing climate change by enabling efficiency gains across multiple sectors that could reduce greenhouse gas emissions up to 5 times more than ICT's own carbon footprint.
- University campuses can serve as living laboratories for testing green ICT solutions and infrastructure to reduce emissions from buildings, transportation, electricity generation and distribution.
- Advances in machine learning and brain-inspired computing will be necessary to develop low-power exascale supercomputers needed to fully model and simulate climate systems.
National Federated Compute Platforms: The Pacific Research Platform
The Pacific Research Platform (PRP) is a multi-institution hypercluster that connects science DMZs across 25 partner campuses using FIONA data transfer nodes and 10-100Gbps networks. PRP adopted Kubernetes and Rook to orchestrate petabytes of distributed storage and GPUs for data science applications. A CHASE-CI grant added machine learning capabilities. PRP is working to federate with the Open Science Grid and become a prototype for a future National Research Platform connecting regional networks.
The Pacific Research Platform (PRP) is a multi-institutional cyberinfrastructure project that connects researchers across California and beyond to share large datasets. It spans the 10 University of California campuses, major private research universities, supercomputer centers, and some out-of-state universities. Fifteen multi-campus research teams in fields like physics, astronomy, earth sciences, biomedicine, and multimedia will drive the technical needs of the PRP over five years. The goal is to create a "big data freeway" to allow high-speed sharing of data between research labs, supercomputers, and repositories across multiple networks without performance loss over long distances.
High Performance Cyberinfrastructure is Needed to Enable Data-Intensive Scien...
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National Science Board
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Title: High Performance Cyberinfrastructure is Needed to Enable Data-Intensive Science and Engineering
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The Pacific Research Platform:a Science-Driven Big-Data Freeway System
The Pacific Research Platform will create a regional "Big Data Freeway System" along the West Coast to support science. It will connect major research institutions with high-speed optical networks, allowing them to share vast amounts of data and computational resources. This will enable new forms of collaborative, data-intensive research for fields like particle physics, astronomy, biomedicine, and earth sciences. The first phase aims to establish a basic networked infrastructure, with later phases advancing capabilities to 100Gbps and beyond with security and distributed technologies.
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The document summarizes Dr. Larry Smarr's presentation on the Pacific Research Platform (PRP) and its role in working toward a national research platform. It describes how PRP has connected research teams and devices across multiple UC campuses for over 15 years. It also details PRP's innovations like Flash I/O Network Appliances (FIONAs) and use of Kubernetes to manage distributed resources. Finally, it outlines opportunities to further integrate PRP with the Open Science Grid and expand the platform internationally through partnerships.
The document discusses the vision and progress of the Pacific Research Platform (PRP) in creating a "big data freeway" across the West Coast to enable data-intensive science. It outlines how the PRP builds on previous NSF and DOE networking investments to provide dedicated high-performance computing resources, like GPU clusters and Jupyter hubs, connected by high-speed networks at multiple universities. Several science driver teams are highlighted, including particle physics, astronomy, microbiology, earth sciences, and visualization, that will leverage PRP resources for large-scale collaborative data analysis projects.
CENIC: Pacific Wave and PRP Update Big News for Big Data
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High Performance Cyberinfrastructure Enabling Data-Driven Science Supporting ...
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Sanford Consortium for Regenerative Medicine
Salk Institute, La Jolla
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Title: High Performance Cyberinfrastructure Enabling Data-Driven Science Supporting Stem Cell Research
The Pacific Research Platform: Building a Distributed Big-Data Machine-Learni...Larry Smarr
The Pacific Research Platform (PRP) is a distributed big data and machine learning cyberinfrastructure connecting researchers across multiple UC campuses. It was established in 2015 with NSF funding and has since expanded to include other California universities and national/international partners. The PRP provides high-speed networks, storage, and computing resources like GPUs. It has enabled new data-intensive collaborations and significantly accelerated research workflows. The PRP also supports educational initiatives, providing computing resources for data science courses impacting thousands of students.
Looking Back, Looking Forward NSF CI Funding 1985-2025Larry Smarr
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The Pacific Research Platform: a Science-Driven Big-Data Freeway SystemLarry Smarr
The Pacific Research Platform (PRP) is a multi-institutional partnership that establishes a high-capacity "big data freeway system" spanning the University of California campuses and other research universities in California to facilitate rapid data access and sharing between researchers and institutions. Fifteen multi-campus application teams in fields like particle physics, astronomy, earth sciences, biomedicine, and visualization drive the technical design of the PRP over five years. The goal of the PRP is to extend campus "Science DMZ" networks to allow high-speed data movement between research labs, supercomputer centers, and data repositories across campus, regional
The Pacific Research Platform: Building a Distributed Big-Data Machine-Learni...Larry Smarr
The document summarizes the Pacific Research Platform (PRP) which connects researchers across multiple universities with high-speed networks and computing resources for big data and machine learning applications. Key points:
- PRP connects 15 universities with optical networks, distributed storage devices (FIONAs), and over 350 GPUs for data analysis and AI training.
- It allows researchers to rapidly share and analyze large datasets, with one example reducing a workflow from 19 days to 52 minutes.
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- University campuses can serve as living laboratories for testing green ICT solutions and infrastructure to reduce emissions from buildings, transportation, electricity generation and distribution.
- Advances in machine learning and brain-inspired computing will be necessary to develop low-power exascale supercomputers needed to fully model and simulate climate systems.
National Federated Compute Platforms: The Pacific Research PlatformLarry Smarr
The Pacific Research Platform (PRP) is a multi-institution hypercluster that connects science DMZs across 25 partner campuses using FIONA data transfer nodes and 10-100Gbps networks. PRP adopted Kubernetes and Rook to orchestrate petabytes of distributed storage and GPUs for data science applications. A CHASE-CI grant added machine learning capabilities. PRP is working to federate with the Open Science Grid and become a prototype for a future National Research Platform connecting regional networks.
The Pacific Research Platform (PRP) is a multi-institutional cyberinfrastructure project that connects researchers across California and beyond to share large datasets. It spans the 10 University of California campuses, major private research universities, supercomputer centers, and some out-of-state universities. Fifteen multi-campus research teams in fields like physics, astronomy, earth sciences, biomedicine, and multimedia will drive the technical needs of the PRP over five years. The goal is to create a "big data freeway" to allow high-speed sharing of data between research labs, supercomputers, and repositories across multiple networks without performance loss over long distances.
High Performance Cyberinfrastructure is Needed to Enable Data-Intensive Scien...Larry Smarr
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The Pacific Research Platform will create a regional "Big Data Freeway System" along the West Coast to support science. It will connect major research institutions with high-speed optical networks, allowing them to share vast amounts of data and computational resources. This will enable new forms of collaborative, data-intensive research for fields like particle physics, astronomy, biomedicine, and earth sciences. The first phase aims to establish a basic networked infrastructure, with later phases advancing capabilities to 100Gbps and beyond with security and distributed technologies.
An Integrated Science Cyberinfrastructure for Data-Intensive ResearchLarry Smarr
This document summarizes Dr. Larry Smarr's vision for an integrated science cyberinfrastructure to support data-intensive research. It discusses the exponential growth of digital data and need for dedicated high-bandwidth networks and data repositories. Specific examples are provided of initiatives at UCSD, regional optical networks connecting research institutions, and national projects like the Open Science Grid and Cancer Genomics Hub that are creating cyberinfrastructure to enable data-intensive scientific discovery.
Towards a High-Performance National Research Platform Enabling Digital ResearchLarry Smarr
The document summarizes Dr. Larry Smarr's keynote presentation on enabling a high-performance national research platform. It describes how multi-institutional research increasingly relies on access to large datasets, requiring new cyberinfrastructure. The Pacific Research Platform provides high-bandwidth networking between universities to support research collaborations across disciplines. The next steps involve scaling this model into a national and global platform. The presentation highlights how the PRP enables various scientific applications and drives innovation through improved data transfer capabilities and distributed computing resources.
The document summarizes Dr. Larry Smarr's presentation on the Pacific Research Platform (PRP) and its role in working toward a national research platform. It describes how PRP has connected research teams and devices across multiple UC campuses for over 15 years. It also details PRP's innovations like Flash I/O Network Appliances (FIONAs) and use of Kubernetes to manage distributed resources. Finally, it outlines opportunities to further integrate PRP with the Open Science Grid and expand the platform internationally through partnerships.
Pacific Research Platform Science DriversLarry Smarr
The document discusses the vision and progress of the Pacific Research Platform (PRP) in creating a "big data freeway" across the West Coast to enable data-intensive science. It outlines how the PRP builds on previous NSF and DOE networking investments to provide dedicated high-performance computing resources, like GPU clusters and Jupyter hubs, connected by high-speed networks at multiple universities. Several science driver teams are highlighted, including particle physics, astronomy, microbiology, earth sciences, and visualization, that will leverage PRP resources for large-scale collaborative data analysis projects.
CENIC: Pacific Wave and PRP Update Big News for Big DataLarry Smarr
The document discusses the Pacific Wave exchange and Pacific Research Platform (PRP). It provides an overview of Pacific Wave, including its history and connectivity across the Pacific and western US. It then discusses how the PRP will build on infrastructure projects to create a high-speed "big data freeway" for science across California universities. This will allow researchers to more easily share and analyze large datasets for projects in areas like climate modeling, cancer genomics, astronomy and particle physics. Details are provided on specific science applications and datasets that will benefit from the enhanced connectivity of the PRP.
Toward a Global Interactive Earth Observing CyberinfrastructureLarry Smarr
The document discusses the need for a new generation of cyberinfrastructure to support interactive global earth observation. It outlines several prototyping projects that are building examples of systems enabling real-time control of remote instruments, remote data access and analysis. These projects are driving the development of an emerging cyber-architecture using web and grid services to link distributed data repositories and simulations.
High Performance Cyberinfrastructure Enabling Data-Driven Science Supporting ...Larry Smarr
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Larry Smarr, Calit2 & Phil Papadopoulos, SDSC/Calit2
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15th Annual ON*VECTOR International Photonics Workshop
Calit2’s Qualcomm Institute
University of California, San Diego
February 29, 2016
- The Pacific Research Platform (PRP) interconnects campus DMZs across multiple institutions to provide high-speed connectivity for data-intensive research.
- The PRP utilizes specialized data transfer nodes called FIONAs that provide disk-to-disk transfer speeds of 10-100Gbps.
- Early applications of the PRP include distributing telescope data between UC campuses, connecting particle physics experiments to computing resources, and enabling real-time wildfire sensor data analysis.
The document discusses the National Research Platform (NRP), specifically the 4th NRP workshop. It provides an overview of NRP's Nautilus, a multi-institution hypercluster connected by optical networks across 25 partner campuses. In 2022, Nautilus comprised ~200 computing nodes and 4000TB of rotating storage. The document highlights several large research projects from different domains that utilize Nautilus, including particle physics, telescopes, biomedical applications, earth sciences, and visualization. These applications demonstrate how Nautilus enables data-intensive and collaborative multi-campus research at national scale.
A Campus-Scale High Performance Cyberinfrastructure is Required for Data-Int...Larry Smarr
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Princeton University
Title: A Campus-Scale High Performance Cyberinfrastructure is Required for Data-Intensive Research
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Analyzing Large Earth Data Sets: New Tools from the OptiPuter and LOOKING Pro...Larry Smarr
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Big Data Tech Forum: Big Data Enabling Technologies and Applications
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The Pacific Research Platform: A Regional-Scale Big Data Analytics Cyberinfra...Larry Smarr
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The Vice Chancellor of Research and Chief Information Officer Summit
“Information Technology Enabling Research at the University of California”
Title: Positioning University of California Information Technology for the Future: State, National, and International IT Infrastructure Trends and Directions
Oakland, CA
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4. **Science**: Researchers use FDM to prototype equipment for scientific experiments, build custom laboratory tools, and create models for visualization and testing purposes. It facilitates rapid iteration and customization in scientific endeavors.
5. **Automotive**: Automotive manufacturers employ FDM for prototyping vehicle components, tooling for assembly lines, and customized parts. It speeds up the design validation process and enhances efficiency in automotive engineering.
6. **Consumer Electronics**: FDM is utilized in consumer electronics for designing and prototyping product enclosures, casings, and internal components. It enables rapid iteration and customization to meet evolving consumer demands.
7. **Robotics**: Robotics engineers leverage FDM to prototype robot parts, create lightweight and durable components, and customize robot designs for specific applications. It supports innovation and optimization in robotic systems.
8. **Aerospace**: In aerospace, FDM is used to manufacture lightweight parts, complex geometries, and prototypes of aircraft components. It contributes to cost reduction, faster production cycles, and weight savings in aerospace engineering.
9. **Architecture**: Architects utilize FDM for creating detailed architectural models, prototypes of building components, and intricate designs. It aids in visualizing concepts, testing structural integrity, and communicating design ideas effectively.
Each industry example demonstrates how FDM enhances innovation, accelerates product development, and addresses specific challenges through advanced manufacturing capabilities.
The Pacific Research Platform Enables Distributed Big-Data Machine-Learning
1. “The Pacific Research Platform Enables
Distributed Big-Data Machine-Learning”
Keynote:
Big Data & Extreme-Scale Computing2 (BDEC2)
San Diego, CA
October 15, 2019
Dr. Larry Smarr
Director, California Institute for Telecommunications and Information Technology
Harry E. Gruber Professor,
Dept. of Computer Science and Engineering
Jacobs School of Engineering, UCSD
http://lsmarr.calit2.net
1
2. Source: Maxine Brown, OptIPuter Project Manager
The OptIPuter
Exploits a New World
in Which
the Central Architectural Element
is Optical Networking,
Not Computers.
Distributed Cyberinfrastructure
to Support
Data-Intensive Scientific Research
and Collaboration
PI Smarr,
2002-2009
3. Integrated “OptIPlatform” Cyberinfrastructure System:
A 10Gbps Prototype of an NRP
National LambdaRail
Campus
Optical
Switch
Data Repositories & Clusters
HPC
HD/4k Video Images
HD/4k Video Cams
End User
OptIPortal
10G
Lightpath
HD/4k Telepresence
Instruments
LS 2009
Slide
4. 2000-2015 Using UCSD Campus as Development Prototype:
NSF OptIPuter, Quartzite, Prism Awards
PI Papadopoulos
2013-2015
PI Smarr
2002-2009
PI Papadopoulos
2004-2007
5. 2010-2018: DOE & NSF Partnering
on Science Engagement and ScienceDMZ Technology Adoption
Science
DMZ
Data Transfer
Nodes
(DTN/FIONA)
Network
Architecture
(zero friction)
Performance
Monitoring
(perfSONAR)
ScienceDMZ Coined in 2010 by ESnet
Basis of PRP Architecture and Design
http://fasterdata.es.net/science-dmz/
Slide Adapted From Inder Monga, ESnet
DOE
NSF
NSF Campus Cyberinfrastructure Program
Has Made Over 250 Awards
2012 2013 2014 2015 2016 2017 2018
Quartzite
Prism
6. (GDC)
2015 Vision: The Pacific Research Platform Will Connect Science DMZs
Creating a Regional End-to-End Science-Driven Community Cyberinfrastructure
NSF CC*DNI Grant
$6.3M 10/2015-10/2020
Year 5 Starts in 1 Week!
PI: Larry Smarr, UC San Diego Calit2
Co-PIs:
• Camille Crittenden, UC Berkeley CITRIS,
• Tom DeFanti, UC San Diego Calit2/QI,
• Philip Papadopoulos, UCI
• Frank Wuerthwein, UCSD Physics and SDSC
Source: John Hess, CENIC
ESnet: Given Fast Networks, Need
DMZs and Fast/Tuned DTNs
Letters of Commitment from:
• 50 Researchers from 15 Campuses
• 32 IT/Network Organization Leaders
7. PRP Engineers Designed and Built Several Generations
of Optical-Fiber Big-Data Flash I/O Network Appliances (FIONAs)
UCSD-Designed FIONAs Solved the Disk-to-Disk Data Transfer Problem
at Near Full Speed on Best-Effort 10G, 40G and 100G Networks
FIONAs Designed by UCSD’s Phil Papadopoulos, John Graham,
Joe Keefe, and Tom DeFanti
Two FIONA DTNs at UC Santa Cruz: 40G & 100G
Up to 192 TB Rotating Storage
Add Up to 8 Nvidia GPUs Per 2U FIONA
To Add Machine Learning Capability
8. Installing FIONAs Across California in Late 2018 and Early 2019
To Enhance User’s CPU and GPU Computing, Data Posting, and Data Transfers
UC Merced
Stanford UC Santa Barbara
UC Riverside
UC Santa Cruz
UC Irvine
9. We Measure Disk-to-Disk Throughput with 10GB File Transfer
4 Times Per Day in Both Directions for All PRP Sites
January 29, 2016
From Start of Monitoring 12 DTNs
to 24 DTNs Connected at 10-40G
in 1 ½ Years
July 21, 2017
Source: John Graham, Calit2
10. OSG (an NRP Providing High Throughput Compute & Data Resources)
Has Been Integrated With the PRP
SDSC
U.ChicagoFNAL
Caltech
In aggregate ~ 200,000 Intel x86 cores
used by ~400 projects
Source: Frank
Würthwein,
OSG Exec Director;
PRP co-PI
UCSD/SDSC
OSG Federates
~100 Clusters
Worldwide
11. The Open Science Grid Delivers
1.8 Billion Core-Hours Per Year to Over 50 Fields of Science
NCSA Delivered
~35,000 Core-Hours
Per Year in 1990
https://gracc.opensciencegrid.org/dashboard/db/gracc-home
12. 2017-2020: NSF CHASE-CI Grant Adds a Machine Learning Layer
Built on Top of the Pacific Research Platform
Caltech
UCB
UCI UCR
UCSD
UCSC
Stanford
MSU
UCM
SDSU
NSF Grant for High Speed “Cloud” of 256 GPUs
For 30 ML Faculty & Their Students at 10 Campuses
for Training AI Algorithms on Big Data
13. Original PRP
CENIC/PW Link
2018-2021: Toward the NRP -
Using CENIC & Internet2 to Connect Quilt Regional R&E Networks
“Towards
The NRP”
3-Year Grant
Funded
by NSF
$2.5M
October 2018
PI Smarr
Co-PIs Altintas
Papadopoulos
Wuerthwein
Rosing
DeFanti
NSF CENIC Link
14. 2018/2019: PRP Game Changer!
Using Kubernetes to Orchestrate Containers Across the PRP
“Kubernetes is a way of stitching together
a collection of machines into,
basically, a big computer,”
--Craig Mcluckie, Google
and now CEO and Founder of Heptio
"Everything at Google runs in a container."
--Joe Beda,Google
15. PRP Uses Cloud-Native Rook as a Storage Orchestrator,
Running ‘Inside’ Kubernetes
https://rook.io/
Source: John Graham, Calit2/QI
16. PRP’s Nautilus Hypercluster Adopted Kubernetes
to Orchestrate Software Containers and Manage Distributed Storage
“Kubernetes with Rook/Ceph Allows Us to Manage Petabytes of
Distributed Storage and GPUs for Data Science,
While We Measure and Monitor Network Use.”
--John Graham, Calit2/QI UC San Diego
Kubernetes (K8s) is an open-source system for
automating deployment, scaling, and
management of containerized applications.
17. Using Kubernetes to Surround the PRP/CHASE-CI Machine Learning Platform
With Clouds of CPUs, GPUs and Non-Von Neumann Processors
CHASE-CI
288
64-bit GPUs
Field-Programmable Gate Arrays (FPGA)
18. PRP’s Nautilus Forms a Multi-Application
Powerful Distributed “Big Data” Storage and Machine-Learning Computer
Source: grafana.nautilus.optiputer.net on 9/22/2019
20. CENIC/PW Link
40G 3TB
U Hawaii
40G 160TB
NCAR-WY
40G 192TB
UWashington
100G FIONA
I2 Chicago
100G FIONA
I2 Kansas City
10G FIONA1
40G FIONA
UIC
100G FIONA
I2 NYC
40G 3TB
StarLight
PRP/TNRP’s United States Nautilus Hypercluster FIONAs
Now Connects 4 More Regionals and 3 Internet2 sites
21. Global PRP Nautilus Hypercluster Is Rapidly Adding International Partners
Beyond Our Original Partner in Amsterdam
PRP
Guam
Australia
Korea
Singapore
Netherlands
10G 35TB
UvA40G FIONA6
40G 28TB
KISTI
10G 96TB
U of Guam
100G 35TB
U of Queensland
Transoceanic Nodes Show Distance is Not the Barrier
to Above 5Gb/s Disk-to-Disk Performance
PRP’s Current
International
PartnersGRP Workshop 9/17-18 at UCSD
22. Operational Metrics: Containerized Trace Route Tool Allows Realtime Visualization
of Status of PRP Network Links on a National and Global Scale
Source: Dima Mishin, SDSC9/16/2019
Guam
Univ. Queensland
Australia
LIGO
UK
Netherlands
Korea
25. PRP Enables Speed-Ups of Complex Distributed Workflows:
Scott Sellars’ Rapid 4D Object Segmentation of NASA Water Vapor Data
NASA *MERRA v2 –
Water Vapor Data
Across the Globe
4D Object Constructed
(Lat, Lon, Value, Time)
Object Detection,
Segmentation and Tracking
Scott L. Sellars1, John Graham1, Dima Mishin1, Kyle Marcus2 , Ilkay Altintas2, Tom DeFanti1, Larry Smarr1,
Joulien Tatar3, Phu Nguyen4, Eric Shearer4, and Soroosh Sorooshian4
1Calit2@UCSD; 2SDSC; 3Office of Information Technology, UCI; 4Center for Hydrometeorology and Remote Sensing, UCI
26. Calit2’s FIONA
SDSC’s COMET
Calit2’s FIONA
Pacific Research Platform (10-100 Gb/s)
GPUsGPUs
Complete workflow time: 19.2 days52 Minutes!
UC, Irvine UC, San Diego
PRP Enabled Scott’s Workflow
to Run 532 Times Faster!
Source: Scott Sellers, CW3E
27. Co-Existence of Interactive and
Non-Interactive Computing on PRP
GPU Simulations Needed to Improve Ice Model.
=> Results in Significant Improvement in Pointing Resolution
for Multi-Messenger Astrophysics
NSF Large-Scale Observatories
Are Beginning to Utilize PRP Compute Resources
IceCube & LIGO Both See Nautilus
as Just Another OSG Resource
28. In 2019 a Growing Number of Applications and Campuses
Have Driven a 4-Fold Increase in Requested Nautilus GPUs
IceCube
Ravi Ramamoorthi, UCSD
Computer Graphics ML
Jeff Krichmar, UCI
Reinforcement Learning
Gary Cottrell, UCSD
Deep Learning
Dinesh Bharadia, UCSD
Autonomous Driving
Mark Alber Group, UCR
Quantitative Modeling in Biology
Anshul Kundaje, Stanford
Genomics Deep Learning
Hao Su, UCSD
AI in Robotics
https://grafana.nautilus.optiputer.net
29. Over the Last 3 Months, PRP Nautilus Has Grown to
Providing the Great Majority of LIGO GPU Compute Time
Source: GRP Talk by Igor Sfiligoi, UCSD/SDSC/OSG
30. 100 Gbps FIONA at UCSC Allows for Downloads to the UCSC Hyades Cluster
from the LBNL NERSC Supercomputer for DESI Science Analysis
300 images per night.
100MB per raw image
120GB per night
250 images per night.
530MB per raw image
800GB per night
Source: Peter Nugent, LBNL
Professor of Astronomy, UC Berkeley
Precursors to
LSST and NCSA
NSF-Funded Cyberengineer
Shaw Dong @UCSC
Receiving FIONA
Feb 7, 2017
31. Global Scientific Instruments Will Produce Ultralarge Datasets Continuously
Requiring Dedicated Optic Fiber, Supercomputers, and Machine Learning
NCSA will be
the global central hub
for the LSST processing,
archiving, and serving
the terabytes of data
that will be collected
every night of
the decade-long survey
FIU
Use PRP-Like CI to Connect NCSA Repository
To Remote Astronomy Big Data Analysis Users?
32. UC San Diego Jaffe Lab (SIO) Scripps Plankton Camera
Off the SIO Pier with Fiber Optic Network
33. Over 300 Million Images So Far!
Requires Machine Learning for Automated Image Analysis and Classification
Phytoplankton: Diatoms
Zooplankton: Copepods
Zooplankton: Larvaceans
Source: Jules Jaffe, SIO
”We are using the FIONAs for image processing...
this includes doing Particle Tracking Velocimetry
that is very computationally intense.”-Jules Jaffe
34. Moving a Supercomputer Application
to a Distributed Computation on PRP:
25 years
[CO2,aq] 100 Year Simulation
4 days
75 years
100 years
• 0.5 km x 0.5 km x 17.5 m
• Three sandstone layers
separated by two shale
layers
Simulating the Injection of CO2
in Brine-Saturated Reservoirs:
Poroelastic and Pressure-Velocity Fields
Solved In Parallel Over the PRP,
Using MPI for Domain Decomposition,
Orchestrated by Kubernetes Containers
on FIONA Nodes
Computational Domain
Evolution of Formation Water Carbonic Acid
Concentration in Time, After 4 Days of Injection
Numerical methods:
Finite Elements for Solid Phase,
Finite Volume for Aqueous Phase
35. PRP Distributed-Parallel Computation:
Using OpenMPI on Kubernetes to Create Distributed Pods
[paolini@fiona k8s]$ kubectl get pod -n sdsu -o=custom-columns=NODE:.spec.nodeName
NODE [Creating Kubernetes Distributed Pods]
k8s-nvme-01.sdsc.optiputer.net
fiona.cac.washington.edu
dtn-main.ucr.edu
siderea.ucsc.edu
dtn2-daejeon.kreonet.net
fiona-dtn-1.ucsc.edu
fiona.nwsc.ucar.edu
k8s-epyc-01.sdsc.optiputer.net
(GDC)
Comet: SDSC XSEDE cluster
FIONA
FIONA
FIONA
FIONA
FIONA
FIONA
FIONA
MPI
Beehive:
Petascale
Parallel
Storage
Source: Chris Paolini, SDSU
36. 2020-2025 NRP Future:
SDSC’s EXPANSE Will Use CHASE-CI Developed Composable Systems
~$20M over 5 Years
PI Mike Norman, SDSC
37. PRP/TNRP/CHASE-CI Support and Community:
• US National Science Foundation (NSF) awards to UCSD, NU, and SDSC
CNS-1456638, CNS-1730158, ACI-1540112, ACI-1541349, & OAC-1826967
OAC 1450871 (NU) and OAC-1659169 (SDSU)
• UC Office of the President, Calit2 and Calit2’s UCSD Qualcomm Institute
• San Diego Supercomputer Center and UCSD’s Research IT and Instructional IT
• Partner Campuses: UCB, UCSC, UCI, UCR, UCLA, USC, UCD, UCSB, SDSU, Caltech, NU,
UWash UChicago, UIC, UHM, CSUSB, HPWREN, UMo, MSU, NYU, UNeb, UNC,UIUC,
UTA/Texas Advanced Computing Center, FIU, KISTI, UVA, AIST
• CENIC, Pacific Wave/PNWGP, StarLight/MREN, The Quilt, Kinber, Great Plains Network,
NYSERNet, LEARN, Open Science Grid, Internet2, DOE ESnet, NCAR/UCAR & Wyoming
Supercomputing Center, AWS, Google, Microsoft, Cisco