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.
- 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 provides an overview of the Pacific Research Platform (PRP) and discusses its role in connecting researchers across institutions and enabling new applications. It summarizes the PRP's key components like Science DMZs, Data Transfer Nodes (FIONAs), and use of Kubernetes for container management. Several examples are given of how the PRP facilitates high-performance distributed data analysis, access to remote supercomputers, and sensor networks coupled to real-time computing. Upcoming work on machine learning applications and expanding the PRP internationally is also outlined.
Global Research Platforms: Past, Present, FutureLarry Smarr
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise boosts blood flow, releases endorphins, and promotes changes in the brain which help regulate emotions and stress levels.
The Pacific Research Platform: Building a Distributed Big Data Machine Learni...Larry Smarr
This document summarizes Dr. Larry Smarr's invited talk about the Pacific Research Platform (PRP) given at the San Diego Supercomputer Center in April 2019. The PRP is building a distributed big data machine learning supercomputer by connecting high-performance computing and data resources across multiple universities in California and beyond using high-speed networks. It provides researchers with petascale computing power, distributed storage, and tools like Kubernetes to enable collaborative data-intensive science across institutions.
The document discusses the Pacific Research Platform (PRP), a distributed cyberinfrastructure that connects researchers and data across multiple campuses in California and beyond using optical fiber networking. Key points:
- The PRP uses high-speed networking infrastructure like the CENIC network to connect data generators and consumers across 15+ campuses, creating an integrated "big data freeway system".
- It deploys specialized data transfer nodes called FIONAs to enable high-speed transfer of large datasets between sites at near the full network speed.
- Recent additions include using Kubernetes to orchestrate containers across the PRP infrastructure and integrating machine learning resources through the CHASE-CI grant to support data-intensive AI applications.
Creating a Big Data Machine Learning Platform in CaliforniaLarry Smarr
Big Data Tech Forum: Big Data Enabling Technologies and Applications
San Diego Chinese American Science and Engineering Association (SDCASEA)
Sanford Consortium
La Jolla, CA
December 2, 2017
A California-Wide Cyberinfrastructure for Data-Intensive ResearchLarry Smarr
The document discusses creating a California-wide cyberinfrastructure for data-intensive research. It outlines efforts to connect all UC campuses and other research institutions across California with high-speed optical networks. This would create a "big data plane" to share large datasets. Several campuses have received NSF grants to upgrade their networks and implement Science DMZ architectures with 10-100Gbps connections to CENIC. Connecting these resources would provide researchers access to high-performance computing, large scientific instruments, and datasets. This would support collaborative big data science across disciplines like physics, climate modeling, genomics and microscopy.
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.
Opening Keynote Lecture
15th Annual ON*VECTOR International Photonics Workshop
Calit2’s Qualcomm Institute
University of California, San Diego
February 29, 2016
The Pacific Research Platform:a Science-Driven Big-Data Freeway SystemLarry Smarr
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.
The Rise of Supernetwork Data Intensive ComputingLarry Smarr
Invited Remote Lecture to SC21
The International Conference for High Performance Computing, Networking, Storage, and Analysis
St. Louis, Missouri
November 18, 2021
My Remembrances of Mike Norman Over The Last 45 YearsLarry Smarr
Mike Norman has been a leader in computational astrophysics for over 45 years. Some of his influential work includes:
- Cosmic jet simulations in the early 1980s which helped explain phenomena from galactic centers.
- Pioneering the use of adaptive mesh refinement in the 1990s to achieve dynamic load balancing on supercomputers.
- Massive cosmology simulations in the late 2000s with over 100 trillion particles using thousands of processors across multiple supercomputing sites, producing petabytes of data.
- Developing end-to-end workflows in the 2000s to couple supercomputers, high-speed networks, and large visualization systems to enable real-time analysis of extremely large astrophysics simulations.
Metagenics How Do I Quantify My Body and Try to Improve its Health? June 18 2019Larry Smarr
Larry Smarr discusses quantifying his body and health over time through extensive self-tracking. He measures various biomarkers through regular blood tests and analyzes his gut microbiome by sequencing stool samples. This revealed issues like chronic inflammation and an unhealthy microbiome. Smarr then took steps like a restricted eating window and increasing plant diversity in his diet, which reversed metabolic syndrome issues and correlated with shifts in his microbiome ecology. His goal is to continue precisely measuring factors like toxins, hormones, gut permeability and food/supplement impacts to further optimize his health.
Panel: Reaching More Minority Serving InstitutionsLarry Smarr
This document discusses engaging more minority serving institutions (MSIs) in cyberinfrastructure development through regional networks. It provides data showing the importance of MSIs like historically black colleges and universities (HBCUs) in educating underrepresented minority students in STEM fields. Regional networks can help equalize opportunities by assisting MSIs in overcoming barriers to resources through training, networking infrastructure support, and helping institutions obtain necessary staffing and funding. Strategies mentioned include collaborating with MSIs on grants and addressing issues identified in surveys like lack of vision for data use beyond compliance. The goal is to broaden participation in STEAM fields by leveraging the success MSIs have shown in supporting underrepresented students.
Global Network Advancement Group - Next Generation Network-Integrated SystemsLarry Smarr
This document summarizes a presentation on global petascale to exascale workflows for data intensive sciences. It discusses a partnership convened by the GNA-G Data Intensive Sciences Working Group with the mission of meeting challenges faced by data-intensive science programs. Cornerstone concepts that will be demonstrated include integrated network and site resource management, model-driven frameworks for resource orchestration, end-to-end monitoring with machine learning-optimized data transfers, and integrating Qualcomm's GradientGraph with network services to optimize applications and science workflows.
No black holes from light einstein general relativitySérgio Sacani
— One of the consequences of the fact
that energy—and not mass—is the one responsible for
the curvature of spacetime is the a priori possibility
of having massless fields being held together by gravity. These exotic structures (known as geons) were first
considered by Wheeler [1–3] for electromagnetic fields.
The cases of the (almost massless) neutrinos [4] and the
gravitational field itself [5, 6] were subsequently studied.
These objects are found to be unstable under perturbations [7], leading to either a “leakage” of the massless
field [1] or its collapse into a black hole [8]. In this context, the term kugelblitz (German for “ball lightning”)
has become popular as a way to refer to any hypothetical black hole formed by the gravitational collapse of
electromagnetic radiation [9].
Kugelblitze are allowed by general relativity: there are
exact solutions to Einstein-Maxwell equations describing
black holes generated by the collapse of electromagnetic
energy [10, 11]. Kugelblitze have been studied in the
context of the cosmic censorship hypothesis [11–13], the
evaporation of white holes [11], dark matter [14], and
have even been proposed as the engine of a really speculative option for interstellar travel [15–17]. However, none
of these works take into account quantum effects, which
should play an important role in determining whether a
kugelblitz can form or not. This is especially so if we
are interested in black holes of small sizes such as the
artificial ones required in [15–17].
5S and 45S rDNA monomer organization: lengths, variation and interruption in tandem arrays from Musaceae species
Authors
Pat Heslop-Harrison1,2, Qing Liu2 , Ziwei Wang2, Trude Schwarzacher1,2
Affiliations
1 University of Leicester, Leicester, United Kingdom 2 South China Botanical Garden, Guangzhou, China
Abstract
Long, single-molecule DNA sequencing shows the organization and structures of rDNA monomers in tandem repeats. Short reads of both 5S and 45S rDNA collapse the arrays during assembly, while older BAC sequences suffer from chaemerism and assembly artefacts. Far from being a continuous array of monomers, we find short deletions, insertions or interruptions in the arrays. Full-length retroelements are found at variable points within some 45S and 5S monomers in the arrays, and there are occasional insertions of uncharacterized sequences. Within monomers, both deletions and short duplications are found. Similar rearrangements have been found in multiple, non-identical, reads, giving evidence for homogenization through unequal crossing-over (and hence duplication of segments of the arrays). The 'starts' of the arrays have been characterized with flanking sequences. Musaceae provides a good model for the comparative study of the rDNA arrays, with long reads available from multiple species, variable chromosome numbers and evolutionary movement of rDNA between chromosomes, independent of other genes. The rDNA is very variable between species, many with one pair sites of 45S rDNA, representing 1% of all the DNA, to Musa beccarii with 3 sites and 5% of the DNA. Monomer lengths are also variable, with the typical length around 400bp found for most 5S monomers but 1056bp in Ensete. The detailed characterization of the arrays shows evolutionary mechanisms and diversity of the ribosomal DNA arrays. Further information and references are given at www.molcyt.org .
IBC2024 Madrid International Botanical Congress XX XXIBC
These 40 slides show how Excel is used to examine arithmetic operations with the historic definition of pi=22/7 and the algebraic definition of pi=c/2r.
The outcome is a 'digital pi' of 11/7 and c/r with major implications for 'Digital Integer Mathematics' and 'On-Screen Measuring' as new domains.
The innovative concept is 'Digital Numbers' as the basis for patterns in prime numbers - the most fundamental integers - published as "Prime Numbers in Amazing Colour Patterns" on https://primenumbers.store
This experimentation with Excel as a 'visualisation tool' led to the discovery of the contributors to the 'entanglement' of pi as a letter that generalises numbers and their calculations.
Protein: Structure and Function
Introduction
Proteins are essential macromolecules that play critical roles in nearly all biological processes. They are composed of amino acids linked by peptide bonds, forming complex three-dimensional structures that determine their function.
Structure of Proteins
Primary Structure: The linear sequence of amino acids in a polypeptide chain, determined by the genetic code.
Secondary Structure: Localized folding patterns within a polypeptide chain, such as alpha-helices and beta-sheets, stabilized by hydrogen bonds.
Tertiary Structure: The overall three-dimensional shape of a single polypeptide chain, resulting from interactions between side chains (R groups) of amino acids.
Quaternary Structure: The arrangement of multiple polypeptide chains (subunits) into a single functional protein complex. This structure is stabilized by various interactions, including hydrogen bonds, disulfide bridges, and hydrophobic interactions.
Function of Proteins
Enzymatic Activity: Proteins act as enzymes, catalyzing biochemical reactions with high specificity and efficiency. Example: Amylase catalyzes the breakdown of starch into sugars.
Structural Support: Proteins provide structural integrity and support to cells and tissues. Example: Collagen is a structural protein in connective tissues.
Transport and Storage: Proteins transport and store molecules within cells and throughout the body. Example: Hemoglobin transports oxygen in the blood.
Signaling and Regulation: Proteins are involved in cell signaling and regulation of cellular processes. Example: Insulin regulates blood sugar levels.
Defense Mechanisms: Proteins play a role in the immune response and protection against pathogens. Example: Antibodies recognize and neutralize foreign invaders.
Movement: Proteins are essential for muscle contraction and movement. Example: Actin and myosin are proteins involved in muscle contraction.
Natural polyphenolics are a diverse group of bioactive compounds widely distributed in the plant kingdom. Characterized by the presence of multiple phenolic rings, these compounds are recognized for their significant antioxidant, anti-inflammatory, and anticancer properties. They are primarily found in fruits, vegetables, tea, coffee, and red wine, and play a crucial role in human health by neutralizing free radicals and reducing oxidative stress.
This abstract explores the chemical diversity, biological activities, and potential health benefits of natural polyphenolics. We will review their classification into flavonoids, phenolic acids, and other polyphenol subclasses, highlighting their mechanisms of action at the molecular level. Additionally, we will discuss the impact of natural polyphenolics on chronic diseases such as cardiovascular diseases, diabetes, and cancer, supported by recent clinical and epidemiological studies.
The metabolism and bioavailability of polyphenolics are complex and vary among individuals, affecting their efficacy. Advances in research are focusing on optimizing their delivery and enhancing their bioavailability to maximize their therapeutic potential. Emerging evidence suggests that dietary polyphenolic intake can be an integral part of a preventive and therapeutic strategy for improving health outcomes.
In conclusion, natural polyphenolics offer promising avenues for the development of novel nutraceuticals and functional foods, emphasizing the need for continued research to fully harness their health benefits and therapeutic potential.
The National Research Platform Enables a Growing Diversity of Users and Applications
1. “The National Research Platform
Enables a Growing Diversity of Users and Applications”
Remote Presentation
Emerging Centers Track
Campus Research Computing Consortium (CaRCC)
June 21, 2023
1
Dr. Larry Smarr
Founding Director Emeritus, California Institute for Telecommunications and Information Technology;
Distinguished Professor Emeritus, Dept. of Computer Science and Engineering
Jacobs School of Engineering, UCSD
http://lsmarr.calit2.net
2. Abstract
The demand from academic institutions of all scales for equitable and inclusive access to affordable
computing (CPUs, GPUs, FPGAs) and data storage to enable machine learning (ML) and artificial intelligence
(AI) applications has grown rapidly in recent years. I will discuss how NSF funding of a number of
cyberinfrastructure grants has led to the emergence of the National Research Platform (NRP), which is
increasingly providing this access. The NRP, led by UCSD’s Professor Frank Wuerthwein (SDSC Director)
enables faculty and students to launch their containerized software applications from their home campus
onto the widely distributed NRP cyberinfrastructure, where Google’s Kubernetes automatically executes the
software. I will review the broad spectrum of both data-intensive disciplinary and emerging AI/ML NRP
applications. The NRP has rapidly grown as more and more campus host NRP nodes, all unified into a shared
CI Commons. NRP currently enables user access to over 1,250 GPUs, nearly 20,000 CPU cores, and 32 FPGAs
plus >10 PB of 40-100Gbps-connected high-speed storage. The campuses having NRP users has grown over
the last ten years from 19 campuses in 6 states to 135 campuses in 45 states. Diversity has increased as well:
from the original 9 Minority Serving Institutions with NRP users to now over 25 and from 2 NSF EPSCoR
states to 20, plus two territories and the District of Columbia. The NRP’s goal is to continue this inclusive
growth by training and engaging an even broader set of researchers.
3. 2010-2022:
NSF Adopted a DOE High-Performance Networking Model
DOE
NSF
NSF Campus Cyberinfrastructure Program
2012-2022
Has Made Over 340 Awards:
Across 50 States and Territories
Slide Adapted From Kevin Thompson, NSF
Science
DMZ
Data Transfer
Nodes
(DTN/FIONA)
Network
Architecture
(zero friction)
Performance
Monitoring
(perfSONAR)
ScienceDMZ Coined in 2010 by ESnet
http://fasterdata.es.net/science-dmz/
Slide Adapted From Inder Monga, ESnet
4. 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
Extended – Ended Year 7 in Oct 2022
(GDC)
Source: John Hess, CENIC
5. 2015-2022: UCSD Designs PRP Data Transfer Nodes (DTNs) --
Flash I/O Network Appliances (FIONAs)
FIONAs Solved the Disk-to-Disk Data Transfer Problem
at Near Full Speed on Best-Effort 10G, 40G and 100G
FIONAs Designed by UCSD’s Phil Papadopoulos, John Graham,
Joe Keefe, and Tom DeFanti
https://nationalresearchplatform.org/fiona/
Add Up to 8 Nvidia GPUs Per 2U FIONA
To Add Machine Learning Capability
Up to 240TB Storage
6. 2018/2019: Installing Community Shared FIONA CPU/GPU/Storage Systems
on Campuses and Working With Campus CIOs on DMZs
UC Merced
Stanford
UC Santa Barbara
UC Riverside
UC Santa Cruz UC Irvine
7. 2018/2019: PRP Game Changer!
Using Google’s Kubernetes to Orchestrate Containers Across the PRP
User
Applications
Clouds
Containers
8. 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.
9. Nautilus Has Established a Distributed
Set of Ceph Storage Pools
Allows users to select the placement for
compute jobs relative to the storage pools.
PRP forms optimal-scale Ceph pools with
best performance and lowest latency
10. 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
PI: Larry Smarr
Co-PIs:
• Tajana Rosing
• Ken Kreutz-Delgado
• Ilkay Altintas
• Tom DeFanti
11. Original PRP
CENIC/PW Link
2018-2021: Toward the National Research Platform (TNRP) -
Using CENIC & Internet2 to Connect Quilt Regional R&E Networks
“Towards
The NRP”
3-Year Grant
Funded
by NSF
$2.5M
October 2018
Award #1826967
PI Smarr
Co-PIs Altintas
Papadopoulos
Wuerthwein
Rosing
DeFanti
12. 2021-2026: PRP Federates with
NSF-Funded Prototype National Research Platform
NSF Award OAC #2112167 (June 2021) [$5M Over 5 Years]
PI Frank Wuerthwein (UCSD, SDSC)
Co-PIs Tajana Rosing (UCSD), Thomas DeFanti (UCSD), Mahidhar Tatineni (SDSC), Derek Weitzel (UNL)
13. The Open Science Grid (OSG)
Has Been Integrated With the PRP
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
All OSG User
Communities
Use HTCondor for
Resource Orchestration
SDSC
U.Chicago
FNAL
Caltech
Distributed
OSG Petabyte
Storage Caches
15. 2023: NRP’s Nautilus is a Multi-Institution National to Global Scale Hypercluster
Connected by Optical Networks
~200 FIONAs on 30 Partner Campuses
Networked Together at 10-100Gbps
December 14, 2023
16. Nautilus’ >21,000 CPU Cores and ~1,200 GPUs Distributed over US Networks
Are Hosted on 30 Campuses, Connected by Regional Optical Networks & Internet2
Slide Courtesy of Tom DeFanti, UCSD; PRP co-PI
17. Nautilus 10 PB Ceph Storage
Connected Over Regional Optical Networks & Internet2
Slide Courtesy of Tom DeFanti, UCSD; PRP co-PI
18. The NRP Web Site Provides Widely-Used Open-Source Services
For How to Join, Application Research, Development, and Collaboration
https://nationalresearchplatform.org/nautilus/
19. The December 2022 Pacific Research Platform Video
Highlights 3 Different Applications Out of 1000 Nautilus Namespace Projects
Pacific Research Platform Video:
https://pacificresearchplatform.org/media/pacific-research-platform-video/
20. 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 Using NRP and OSG
as a Cohesive, Federated, National-Scale Research Data Infrastructure
NSF’s IceCube & LIGO Both See Nautilus
as Just Another OSG Resource
IceCube Used
Up to 600 of RP’s 1200
GPUs in 2022/3!
21. 2017: PRP 20Gbps Connection of UCSD SunCAVE and UCM WAVE Over CENIC
2018-2019: Added Their 90 GPUs to PRP for Machine Learning Computations
Leveraging UCM Campus Funds and NSF CNS-1456638 & CNS-1730158 at UCSD
UC Merced WAVE (20 Screens, 20 GPUs) UCSD SunCAVE (70 Screens, 70 GPUs)
See These VR Facilities in Action in the PRP Video
22. NSF-Funded WIFIRE Uses NRP/CENIC to Couple Wireless Edge Sensors
With Supercomputers, Enabling Fire Modeling Workflows
Landscape data
WIFIRE Firemap
Fire Perimeter
Source: Ilkay Altintas, SDSC
Real-Time
Meteorological Sensors
Weather Forecasts
Work Flow
NRP
23. The Rise of Machine Learning ML Applications
on the NRP
24. A Major Project in UCSD’s Hao Su Lab
is Large-Scale Robot Learning
• We Build A Digital Twin of The Real World in Virtual Reality (VR)
For Object Manipulation
• Agents Evolve In VR
o Specialists (Neural Nets) Learn Specific Skills
by Trial and Error
o Generalists (Neural Nets) Distill Knowledge
to Solve Arbitrary Tasks
• On Nautilus:
o Hundreds of specialists
have been trained
o Each specialist is trained
in millions of environment
variants
o ~10,000 GPU hours per
run
25. UCSD’s Ravi Group: How to Create Visually Realistic
3D Objects or Dynamic Scenes in VR or the Metaverse
Source: Prof. Ravi Ramamoorthi, UCSD
ML Computing Transforms a Series of 2D Images
Into a 3D View Synthesis
26. Machine Learning-Based
Neural Radiance Fields for View Synthesis (NeRFs) Are Transformational!
BY JARED LINDZON
NOVEMBER 10, 2022
A neural radiance field (NeRF) is
a fully-connected neural network
that can generate
novel views of complex 3D scenes,
based on a partial set of 2D images.
https://datagen.tech/guides/synthetic-data/neural-radiance-field-nerf/ Source: Prof. Ravi Ramamoorthi, UCSD
https://youtu.be/hvfV-iGwYX8
27. Namespace ucsd-ravigroup
Consumed the 3nd Most Nautilus GPU-Hours in 2022
200,000 GPU-Hours
Peaking at 122 GPUs
• Much of the compute involves training computationally expensive NeRFs.
• Training time to learn a representation of a single scene on a GPU can vary from seconds to a day.
• NeRFs that can see behind occlusions may require a week of training on 8 GPUs simultaneously.
Source: Alexander Trevithick, UCSD Ravi Group
https://grafana.nrp-nautilus.io/d/fHSeM5Lmk/k8s-compute-resources-cluster-gpus
28. California State University San Bernardino is an Excellent Example
Of How to Help Your Faculty and Students Use NRP
www.csusb.edu/academic-technologies-innovation/xreal-lab-and-high-performance-computing/high-performance-computing
Their Campus HPC Program
Enabled CSUSB Faculty & Students
to Use More NRP GPU-Hours
In the Last 12 Months
Than 7 of the 10 UC Campuses!
29. The Key Role of Regional Optical Network Meetings
to Engage More Campuses in Using NRP
www.thequilt.net/quilt-circle/snapshot-scaling-a-national-research-platform/
See https://nationalresearchplatform.org/events/fourth-national-research-platform-4nrp/
for slides and videos of all 4NRP presentations
Jen Leasure
President & CEO,
The Quilt
30. University of Missouri’s Grant Scott
Has Built a Model Program for Data Intensive Computing and ML/AI Using NRP
https://engineering.missouri.edu/2023/engineers-share-expertise-around-nautilus-with-great-plains-network/
31. UCSD’s Information Technology Services Has Adapted PRP FIONA8s
To Support Data Science Courses
• Student-Focused GPU/CPU Cluster For:
– Undergraduate & Graduate Coursework
– For-Credit Independent Study
– Thesis/Dissertation Research
– Capstones & Projects
• Research-Driven Architecture
• Managed by Central IT Services
• Racked FIONA Clusters
– 124 32-bit GPUs
– 660 CPU-cores
32. The UCSD Data Science and Machine Learning Platform
Supports 2-3 Dozen Courses with 2500-4000 Students Per Quarter
Source: Adam Tilghman, ITS
https://datahub.ucsd.edu/hub
www.hpcwire.com/off-the-wire/uc-san-diegos-jupyterhub-platform-aids-students-with-data-intensive-computing-needs/
33. ● Dell PowerEdge Cluster for Instructional Use, with 15 Nodes
Containing 32 GPUs, 768 CPU cores, and 960 TB Storage.
● A Learning Resource that Surges for Research and Instruction
● System Administration as a Service from the NRP
● Friendly User mode this Spring with
● ~90 Users in Computational Engineering 361 &
Astronomical Techniques ASTR 350
● Research in Developing Synthetic Medical Data
for Machine Learning Training
SDSU’s VERNE Expands the UCSD Instructional Model by Federating with NRP:
Visionary, Education, Research, Network, Ecosystem
Slide courtesy of Jerry Sheehan, SDSC CIO
34. The PRP Has Emphasized
Expanding Diversity and Inclusion
• When the PRP Grant Was Funded in 2015, It Started With:
– 6 States Now 45 States
– 19 Campuses Now 135 Campuses
– 9 Minority Serving Institutions Now 24 MSIs
– 2 NSF EPCoR States Now 20 EPSCoR States, 2 Territories, and Wash DC
35. 2015 - United States PRP Campus Users In the Beginning
California
• California Institute of Technology
• San Diego State U. (MSI)
• Stanford U.
• U. of California, Berkeley
• U. of California, Merced (MSI)
• U. of California, Davis (MSI)
• U. of California, Riverside (MSI)
• U. of California, San Francisco
• U. of California, Santa Cruz (MSI)
• U. of California-Irvine (MSI)
• U. of California-Los Angeles
• U. of California-San Diego
• U. of California-Santa Barbara (MSI)
• U. of Southern California
Hawaii (EPSCoR)
• U. of Hawaii (MSI)
Washington
• U. of Washington
Montana (EPSCoR)
• Montana State U- Bozeman
Colorado
• NCAR
Illinois
Northwestern University
U. of Illinois at Chicago (MSI)
Minority Serving Institutions
NSF EPSCoR States
Oct 2015
36. 2023 -Expanded Diversity & Inclusion - Nautilus Campus Users Nationwide:
West
California
• California Institute of Technology
• California State Fullerton (MSI)
• California State Polytechnic U., Humboldt (MSI)
• California State Monterey Bay (MSI)
• California State Polytechnic U., Pomona (MSI)
• California State U. San Bernardino (MSI)
• California State U., Northridge (MSI)
• Harvey Mudd College
• Naval Postgraduate School
• San Diego State U. (MSI)
• San Jose State U. (MSI)
• Stanford U.
• U. of California, Berkeley
• U. of California, Davis (MSI)
• U. of California-Irvine (MSI)
• U. of California-Los Angeles
• U. of California, Merced (MSI)
• U. of California, Riverside (MSI)
• U. of California-San Diego
• U. of California, San Francisco
• U. of California-Santa Barbara (MSI)
• U. of California, Santa Cruz (MSI)
• U. of Southern California
Hawaii (EPSCoR)
• U. of Hawaii (MSI)
Guam (EPSCoR)
• U. of Guam (MSI)
Oregon
• Oregon State U.
• Willamette U.
Washington
• U. of Washington
• Washington State U.
Nevada (EPSCoR)
• U. of Nevada, Reno
Minority Serving Institutions
NSF EPSCoR States
Montana (EPSCoR)
• Montana State U- Bozeman
• Salish Kootenai Tribal College (MSI)
Wyoming (EPSCoR)
• U. of Wyoming
Colorado
• Colorado School of Mines
• NCAR
• U. of Colorado at Boulder
Utah
• Brigham Young U.
• U of Utah
New Mexico (EPSCoR)
• U. of New Mexico
Arizona
• Arizona State U
• U. of Arizona
June 2023
37. Expanded Diversity & Inclusion - Nautilus Campus Users Across the Country:
Midwest
North Dakota (EPSCoR)
• North Dakota State U.
South Dakota (EPSCoR)
Black Hills State U.
South Dakota School of Mines & Tech.
South Dakota State U.
U. of South Dakota
Nebraska (EPSCoR)
U. of Nebraska at Kearney
U. of Nebraska-Lincoln
Kansas (EPSCoR)
Kansas State U.
U. of Kansas
Wichita State U
Oklahoma (EPSCoR)
Oklahoma State U. System
Southwestern Oklahoma State U.
U. of Central Oklahoma
U. of Oklahoma
Texas
Baylor U.
Southern Methodist U.
U. of Texas at Austin
U. of Texas at Dallas
Minnesota
• U of Minnesota
Iowa (EPSCoR)
Iowa State U.
Missouri
Culver-Stockton College
Missouri Western State U
Truman State U
U of Central Missouri
U. of Missouri - Columbia
Washington U. in St. Louis
Illinois
Illinois Institute of Technology
Northwestern University
U. of Chicago
U. of Illinois at Chicago (MSI)
U of Illinois, Urbana-Champaign
Arkansas (EPSCoR)
U. of Arkansas
U. of Arkansas for Medical Sciences
U. of Arkansas, Little Rock
Louisiana (EPSCoR)
Louisiana Tech U.
Southeastern Louisiana U.
Wisconsin
U. of Wisconsin-Madison
U. of Wisconsin-Milwaukee
Michigan
Michigan State U.
U. of Michigan
Ohio
Case Western Reserve U.
Kent State University
Ohio State U.
U. of Akron
U. of Cincinnati
Indiana
Indiana U.
Purdue U.
U. of Notre Dame
Kentucky (EPSCoR)
• U. of Kentucky
Tennessee
Tennessee Tech. U.
Vanderbilt U.
Minority Serving Institutions
NSF EPSCoR States June 2023
38. Expanded Diversity & Inclusion - Nautilus Campus Users Across the Country:
East
Maine (EPSCoR)
Colby College
Massachusetts
• Boston U.
• MIT
Northeastern U.
Connecticut
U. of Connecticut
Yale U.
Rhode Island (EPSCoR)
Brown U.
U. of Rhode Island
New York
American Museum of Natural History
Columbia U.
Manhattan College
New York U.
Rensselaer Polytechnic Institute
Rochester Institute of Technology
Syracuse U.
The State U. of New York at Buffalo
North Carolina
Duke U.
N. Carolina Agricultural & Tech. State U. (MSI)
N. Carolina State U
U. of North Carolina at Chapel Hill
South Carolina (EPSCoR)
Clemson U.
Georgia
Georgia Institute of Technology
Georgia State U. (MSI)
U. of Georgia
Alabama(EPSCoR)
Auburn U.
U of Alabama in Huntsville
Florida
Florida A&M U. (MSI)
Florida International U. (MSI)
Florida State U.
U. of Central Florida (MSI)
U. of Miami
Puerto Rico (EPSCoR)
U. Puerto Rico (MSI)
Pennsylvania
Carnegie Mellon U.
Pennsylvania State U.
U of Pennsylvania
New Jersey
Princeton U.
Rutgers U.
Delaware (EPSCoR)
U. of Delaware
Maryland
Bowie State U. (MSI)
Johns Hopkins U.
Morgan State U. (MSI)
District of Columbia
• American U.
West Virginia (EPSCoR)
West Virginia U.
Virginia
George Mason U.
Virginia Commonwealth U.
Minority Serving Institutions
NSF EPSCoR States June 2023
40. PRP/TNRP/CHASE-CI/PNRP/NRP
Support and Community
• US National Science Foundation (NSF) awards and subawards to UCSD
--CNS-1456638, CNS-1730158, CNS-2100237, CNS-2120019
--ACI-1540112, ACI-1541349, OAC-1826967, OAC-2029306, OAC-2112167
• DOD DURIP awards to UCSD
• 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, UMo, FAMU, MSU, NYU, UNeb, UNM, UNC, FIU, UDel, UDak, SDakSU,
Stanford, UArk, UOk, UoGuam, UKansas, CWRU, Clemson, MGHPCC, KISTI, UVA, AIST
• CENIC, Pacific Wave/PNWGP, StarLight/MREN, The Quilt, Great Plains Network, NYSERNet, Open
Science Grid, Internet2, DOE ESnet, NCAR/UCAR & Wyoming Supercomputing Center,
• AWS, Google, Microsoft, Cisco, Juniper, Arista
Source: Tom DeFanti, UCSD