Outline
• Motivation, Context
• Modern Research Data Portal
• Petascale DTN Project
• Long Term Vision
12/20/20182

• Networks are an essential part of data-intensive science
– Connect data sources to data analysis
– Connect collaborators to each other
– Enable machine-consumable interfaces to data and analysis resources
(e.g. portals), automation, scale
• Performance is critical
– Exponential data growth
– Constant human factors
– Data movement and data analysis must keep up
• Effective use of wide area (long-haul) networks by scientists
has historically been difficult
Motivation
3 – ESnet Science Engagement (engage@es.net) - 12/20/2018
© 2016, Energy Sciences Network

Data Placement: A Common Problem
• Scientists often need to move data from where it is to where it needs to be
– Observation to analysis
– Assemble data set from multiple sources
– Transfer data to/from supercomputer center
• Data movement tools run on systems which use networks – lots involved:
– Servers, storage
– Networks, security policy
• Lots of ways to assemble these things  architecture
• Traditional architectures are not performant in today’s context
– Large data objects
– Data sets with tens of thousands (or more) files
12/20/20184

Science Data Portals
• Large repositories of scientific data
– Climate data
– Sky surveys (astronomy, cosmology)
– Many others
– Data search, browsing, access
• Many scientific data portals were designed 15+ years ago
– Single-web-server design
– Data browse/search, data access, user awareness all in a single system
– All the data goes through the portal server
• In many cases by design
• E.g. embargo before publication (enforce access control)
– Better than old command-line FTP, but outdated by today’s standards
12/20/20185

Legacy Portal Design
10GE
Border Router
WAN
Firewall
Enterprise
perfSONAR
perfSONAR
Filesystem
(data store)
10GE
Portal
Server
Browsing path
Query path
Data path
Portal server applications:
web server
search
database
authentication
data service
12/20/20186
• Very difficult to improve performance
without architectural change
– Software components all tangled
together
– Complexity makes security hard
– Many components aren’t scalable
• What does architectural change mean?

Architectural Examination of Data Portals
• Common data portal functions (most portals have these)
– Search/query/discovery
– Data download method for data access
– GUI for browsing by humans
– API for machine access – ideally incorporates search/query + download
• Performance pain is primarily in the data handling piece
– Rapid increase in data scale eclipsed legacy software stack capabilities
– Portal servers often stuck in enterprise network
• Can we “disassemble” the portal and put the pieces back together better?
12/20/20187

Legacy Portal Design
10GE
Border Router
WAN
Firewall
Enterprise
perfSONAR
perfSONAR
Filesystem
(data store)
10GE
Portal
Server
Browsing path
Query path
Data path
web server
search
database
authentication
data service
12/20/20188

Next-Generation Portal Leverages Science DMZ
10GE10GE
10GE
10GE
Border Router
WAN
Science DMZ
Switch/Router
Firewall
Enterprise
perfSONAR
perfSONAR
10GE
10GE
10GE
10GE
DTN
DTN
API DTNs
(data access governed
by portal)
DTN
DTN
perfSONAR
Filesystem
(data store)
10GE
Portal
Server
Browsing path
Query path
web server
search
database
authentication
Data Path
Data Transfer Path
Portal Query/Browse Path
12/20/20189
https://peerj.com/articles/cs-144/

NCAR RDA Data Portal
• Let’s say I have a nice compute allocation at NERSC – a national
supercomputer center
• Let’s say I need some data from NCAR for my project
• https://rda.ucar.edu/
• Data sets (there are many more, but these are two examples):
• https://rda.ucar.edu/datasets/ds199.1/
• https://rda.ucar.edu/datasets/ds313.0/
• Download to NERSC (could also do ALCF or NCSA or OLCF)
12/20/201810

Portal creates a Globus transfer job for us
12/20/201815

Submit the transfer job, go about our business
12/20/201816

Data Transfer from RDA Portal – Results
12/20/201817

Science DMZ Design Pattern (Abstract)
10GE
10GE
10GE
10GE
10G
BorderRouter
WAN
ScienceDMZ
Switch/Router
EnterpriseBorder
Router/Firewall
Site/Campus
LAN
Highperformance
DataTransferNode
withhigh-speedstorage
Per-service
securitypolicy
controlpoints
Clean,
High-bandwidth
WANpath
Site/Campus
accesstoScience
DMZresources
perfSONAR
perfSONAR
perfSONAR
http://fasterdata.es.net/science-dmz/

Put The Data On Dedicated Infrastructure
• We have separated the data handling from the portal logic
• Portal is still its normal self, but enhanced
– Portal GUI, database, search, etc. all function as they did before
– Query returns pointers to data objects in the Science DMZ
– Portal is now freed from the data servers (run it in the Cloud if you want!)
• Data handling is separate, and scalable
– High-performance data cluster in the Science DMZ
– Scale as much as you need to without modifying the portal software
• Shift data management to computing centers
– Computing centers are set up for large-scale data
– Let them handle the large-scale data, and let the portal do the orchestration
of data placement
• https://peerj.com/articles/cs-144/ - Modern Research Data Portal paper
12/20/201819

Data And HPC: The Petascale DTN Project
• Built on top of the Science DMZ
• Effort to improve data transfer performance between the DOE ASCR HPC
facilities at ANL, LBNL, and ORNL, and also NCSA.
– Multiple current and future science projects need to transfer data between HPC
facilities
– Performance was slow, configurations inconsistent
– Performance goal of 15 gigabits per second (equivalent to 1PB/week)
– Realize performance goal for routine Globus transfers without special tuning
• Reference data set is 4.4TB of cosmology simulation data
• Use performant, easy-to-use tools with production options on
– Globus Transfer service (previously Globus Online)
– Use GUI just like a user would, with default options
• E.g. integrity checksums enabled, as they should be
• No arcane magic!
12/20/201820

DTN Cluster Performance – HPC Facilities (2017)
21.2/22.6/24.5
Gbps
23.1/33.7/39.7
Gbps
26.7/34.7/39.9
Gbps
33.2/43.4/50.3
Gbps
35.9/39.0/40.7
Gbps
29.9/33.1/35.5
Gbps
34.6/47.5/56.8
Gbps
44.1/46.8/48.4
Gbps
41.0/42.2/43.9
Gbps
33.0/35.0/37.8
Gbps
43.0/50.0/56.3
Gbps
55.4/56.7/57.4
Gbps
DTN
DTN
DTN
DTN
NERSC DTN cluster
Globus endpoint: nersc#dtn
Filesystem: /project
Data set: L380
Files: 19260
Directories: 211
Other files: 0
Total bytes: 4442781786482 (4.4T bytes)
Smallest file: 0 bytes (0 bytes)
Largest file: 11313896248 bytes (11G bytes)
Size distribution:
1 - 10 bytes: 7 files
10 - 100 bytes: 1 files
100 - 1K bytes: 59 files
1K - 10K bytes: 3170 files
10K - 100K bytes: 1560 files
100K - 1M bytes: 2817 files
1M - 10M bytes: 3901 files
10M - 100M bytes: 3800 files
100M - 1G bytes: 2295 files
1G - 10G bytes: 1647 files
10G - 100G bytes: 3 files
Petascale DTN Project
November 2017
L380 Data Set
Gigabits per second
(min/avg/max), three
transfers
ALCF DTN cluster
Globus endpoint: alcf#dtn_mira
Filesystem: /projects
OLCF DTN cluster
Globus endpoint: olcf#dtn_atlas
Filesystem: atlas2
NCSA DTN cluster
Globus endpoint: ncsa#BlueWaters
Filesystem: /scratch
12/20/201821

NCAR RDA Performance to DOE HPC Facilities
13.9 Gbps 16.6 Gbps 11.9 Gbps
DTN
nersc#dtn
NERSC
DTN
olcf#dtn_atlas
OLCF
DTN
alcf#dtn_mira
ALCF
DTN
NCAR RDA
rda#datashare
12/20/201822
• 1.5TB data set
• 1121 files

MRDP Partially Integrated Into ESGF
12/20/201823

Modernized Cyberinfrastructure
• This is an example of the capabilities of modern cyberinfrastructure
– High speed networks
– Science DMZ design pattern
– Modern Research Data Portal design pattern
– HPC facilities
– High performance data platforms
• Together these enable dramatically-improved data placement performance
• Large-scale data analysis is now possible
– Data from portals analyzed at supercomputer centers
– Data shared between supercomputer centers
12/20/201824

Larger Strategic Picture
• Across the scientific community, larger structures are being built
– HPC facilities combined with experiments
– DTNs between campuses
– These create the platform for future scientific discoveries.
• Building DMZs, DTNs, and similar things for scientists puts the power of
modern cyberinfrastructure in the hands of the people who will make the
discoveries that change our world for the better.
• By doing this work, we help bring about the future that we all want - better
medicine, better technology, more energy, a cleaner environment, etc.
12/20/201825

Long-Term Vision
ESnet
(Big Science facilities,
DOE labs)
Internet2 + Regionals
(US Universities and
affiliated institutions)
International Networks
(Universities and labs in Europe,
Asia, Americas, Australia, etc.)
High-performance feature-rich
science network ecosystem
Commercial Clouds
(Amazon, Google,
Microsoft, etc.)
Agency Networks
(NASA, NOAA, etc.)
Campus HPC
+
Data
12/20/201826

It’s All A Bunch Of Science DMZs
DTN
DTN
DTN
DTN
DMZDMZ
DMZDMZ
DTN
DATA
DTN
DMZDMZ
DTN
DTN
DMZDMZ
DATA
DTN DTN
DMZDMZ
Parallel
Filesystem
DTN DTN
DTN
DTNDMZDMZ
DATA
DTN
DTN
DMZDMZ
Experiment
Data Archive
DTN
DTN
DTN
DTN
DTN DMZDMZ
DTN DTN
DMZDMZ
DATA
12/20/201827

It’s All A Bunch Of Science DMZs
DTN
DTN
DTN
DTN
DMZDMZ
DMZDMZ
DTN
DATA
DTN
DMZDMZ
DTN
DTN
DMZDMZ
DATA
DTN DTN
DMZDMZ
Parallel
Filesystem
DTN DTN
DTN
DTNDMZDMZ
DATA
DTN
DTN
DMZDMZ
Experiment
Data Archive
DTN
DTN
DTN
DTN
DTN DMZDMZ
DTN DTN
DMZDMZ
DATA
HPC Facilities
Single Lab
Experiments
Data
Portal
LHC
Experiments
University
Computing
12/20/201828

Thanks!
Eli Dart - dart@es.net
Energy Sciences Network (ESnet)
Lawrence Berkeley National Laboratory
engage@es.net
http://my.es.net/
http://www.es.net/
http://fasterdata.es.net/

Extra slides – data download from portal
12/20/201830

ESnet - the basic facts:
High-speed international networking facility,
optimized for data-intensive science:
• connecting 50 labs, plants and facilities with >150 networks,
universities, research partners globally
• supporting every science office, and serving as an integral
extension of many instruments
• 400Gbps transatlantic extension in production since Dec 2014
• >1.3 Tbps of external connectivity, including high speed access
to commercial partners such as Amazon
• growing number university connections to better serve LHC
science (and eventually: Belle II)
• older than commercial Internet, growing ~twice as fast
Areas of strategic focus: software, science engagement.
• Engagement effort now 12% of staff
• Software capability critical to next-generation network
31

Extra Slides – Science DMZ
12/20/201832

Overview
• Science DMZ Motivation and Introduction
• Science DMZ Architecture
• Network Monitoring For Performance
• Data Transfer Nodes & Applications
• Science Engagement

• Networks are an essential part of data-intensive science
– Connect data sources to data analysis
– Connect collaborators to each other
– Enable machine-consumable interfaces to data and analysis resources
(e.g. portals), automation, scale
• Performance is critical
– Exponential data growth
– Constant human factors
– Data movement and data analysis must keep up
• Effective use of wide area (long-haul) networks by scientists
has historically been difficult
Motivation

The Central Role of the Network
• The very structure of modern science assumes science networks exist: high
performance, feature rich, global scope
• What is “The Network” anyway?
– “The Network” is the set of devices and applications involved in the use of a
remote resource
• This is not about supercomputer interconnects
• This is about data flow from experiment to analysis, between facilities, etc.
– User interfaces for “The Network” – portal, data transfer tool, workflow engine
– Therefore, servers and applications must also be considered
• What is important? Ordered list:
1. Correctness
2. Consistency
3. Performance

TCP – Ubiquitous and Fragile
• Networks provide connectivity between hosts – how do hosts see the
network?
– From an application’s perspective, the interface to “the other end” is a
socket
– Communication is between applications – mostly over TCP
• TCP – the fragile workhorse
– TCP is (for very good reasons) timid – packet loss is interpreted as
congestion
– Packet loss in conjunction with latency is a performance killer
– Like it or not, TCP is used for the vast majority of data transfer
applications (more than 95% of ESnet traffic is TCP)

A small amount of packet loss makes a huge
difference in TCP performance
Metro Area
Local
(LAN)
Regional
Continental
International
Measured (TCP Reno) Measured (HTCP) Theoretical (TCP Reno) Measured (no loss)
With loss, high performance
beyond metro distances is
essentially impossible

Working With TCP In Practice
• Far easier to support TCP than to fix TCP
– People have been trying to fix TCP for years – limited success
– Like it or not we’re stuck with TCP in the general case
• Pragmatically speaking, we must accommodate TCP
– Sufficient bandwidth to avoid congestion
– Zero packet loss
– Verifiable infrastructure
• Networks are complex
• Must be able to locate problems quickly
• Small footprint is a huge win – small number of devices so that problem
isolation is tractable

Putting A Solution Together
• Effective support for TCP-based data transfer
– Design for correct, consistent, high-performance operation
– Design for ease of troubleshooting
• Easy adoption is critical
– Large laboratories and universities have extensive IT deployments
– Drastic change is prohibitively difficult
• Cybersecurity – defensible without compromising performance
• Borrow ideas from traditional network security
– Traditional DMZ
• Separate enclave at network perimeter (“Demilitarized Zone”)
• Specific location for external-facing services
• Clean separation from internal network
– Do the same thing for science – Science DMZ

Dedicated
Systems for Data
Transfer
Network
Architecture
Performance
Testing &
Measurement
Data Transfer Node
• High performance
• Configured specifically
for data transfer
• Proper tools
Science DMZ
• Dedicated network
location for high-speed
data resources
• Appropriate security
• Easy to deploy - no need
to redesign the whole
network
perfSONAR
• Enables fault isolation
• Verify correct operation
• Widely deployed in ESnet
and other networks, as
well as sites and facilities
The Science DMZ Design Pattern

Abstract or Prototype Deployment
• Add-on to existing network infrastructure
– All that is required is a port on the border router
– Small footprint, pre-production commitment
• Easy to experiment with components and technologies
– DTN prototyping
– perfSONAR testing
• Limited scope makes security policy exceptions easy
– Only allow traffic from partners
– Add-on to production infrastructure – lower risk

Science DMZ Design Pattern (Abstract)
10GE
10GE
10GE
10GE
10G
BorderRouter
WAN
ScienceDMZ
Switch/Router
EnterpriseBorder
Router/Firewall
Site/Campus
LAN
Highperformance
DataTransferNode
withhigh-speedstorage
Per-service
securitypolicy
controlpoints
Clean,
High-bandwidth
WANpath
Site/Campus
accesstoScience
DMZresources
perfSONAR
perfSONAR
perfSONAR

Local And Wide Area Data Flows
10GE
10GE
10GE
10GE
10G
Border Router
WAN
Science DMZ
Switch/Router
Enterprise Border
Router/Firewall
Site / Campus
LAN
High performance
Data Transfer Node
with high-speed storage
Per-service
security policy
control points
Clean,
High-bandwidth
WAN path
Site / Campus
access to Science
DMZ resources
perfSONAR
perfSONAR
High Latency WAN Path
Low Latency LAN Path
perfSONAR

Support For Multiple Projects
• Science DMZ architecture allows multiple projects to put DTNs in place
– Modular architecture
– Centralized location for data servers
• This may or may not work well depending on institutional politics
– Issues such as physical security can make this a non-starter
– On the other hand, some shops already have service models in place
• On balance, this can provide a cost savings – it depends
– Central support for data servers vs. carrying data flows
– How far do the data flows have to go?

Multiple Projects
10GE
10GE
10GE
10G
Border Router
WAN
Science DMZ
Switch/Router
Enterprise Border
Router/Firewall
Site / Campus
LAN
Project A DTN
Per-project
security policy
control points
Clean,
High-bandwidth
WAN path
Site / Campus
access to Science
DMZ resources
perfSONAR
perfSONAR
Project B DTN
Project C DTN

Multiple Science DMZs – Dark Fiber
Dark
Fiber
Dark
Fiber
10GE
Dark
Fiber
10GE
10G
Border Router
WAN
Science DMZ
Switch/Routers
Enterprise Border
Router/Firewall
Site / Campus
LAN
Project A DTN
(building A)
Per-project
security
policy
perfSONAR
perfSONAR
Facility B DTN
(building B)
Cluster DTN
(building C)
perfSONARperfSONAR
Cluster
(building C)

Supercomputer Center Deployment
• High-performance networking is assumed in this environment
– Data flows between systems, between systems and storage, wide area, etc.
– Global filesystem often ties resources together
• Portions of this may not run over Ethernet (e.g. IB)
• Implications for Data Transfer Nodes
• “Science DMZ” may not look like a discrete entity here
– By the time you get through interconnecting all the resources, you end up
with most of the network in the Science DMZ
– This is as it should be – the point is appropriate deployment of tools,
configuration, policy control, etc.
• Office networks can look like an afterthought, but they aren’t
– Deployed with appropriate security controls
– Office infrastructure need not be sized for science traffic

Supercomputer Center
Virtual
Circuit
Routed
Border Router
WAN
Core
Switch/Router
Firewall
Offices
perfSONAR
perfSONAR
perfSONAR
Supercomputer
Parallel Filesystem
Front end
switch
Data Transfer
Nodes
Front end
switch

Supercomputer Center Data Path
Virtual
Circuit
Routed
Border Router
WAN
Core
Switch/Router
Firewall
Offices
perfSONAR
perfSONAR
perfSONAR
Supercomputer
Parallel Filesystem
Front end
switch
Data Transfer
Nodes
Front end
switch
High Latency WAN Path
Low Latency LAN Path
High Latency VC Path

Common Threads
• Two common threads exist in all these examples
• Accommodation of TCP
– Wide area portion of data transfers traverses purpose-built path
– High performance devices that don’t drop packets
• Ability to test and verify
– When problems arise (and they always will), they can be solved if the
infrastructure is built correctly
– Small device count makes it easier to find issues
– Multiple test and measurement hosts provide multiple views of the data
path
• perfSONAR nodes at the site and in the WAN
• perfSONAR nodes at the remote site

Overview

Performance Monitoring
• Everything may function perfectly when it is deployed
• Eventually something is going to break
– Networks and systems are complex
– Bugs, mistakes, …
– Sometimes things just break – this is why we buy support contracts
• Must be able to find and fix problems when they occur
• Must be able to find problems in other networks (your network may
be fine, but someone else’s problem can impact your users)
• TCP was intentionally designed to hide all transmission errors from
the user:
– “As long as the TCPs continue to function properly and the internet
system does not become completely partitioned, no transmission errors
will affect the users.” (From RFC793, 1981)

Soft Network Failures – Hidden Problems
• Hard failures are well-understood
– Link down, system crash, software crash
– Routing protocols are designed to cope with hard failures (route around
damage)
– Traditional network/system monitoring tools designed to quickly find hard
failures
• Soft failures result in degraded capability
– Connectivity exists
– Performance impacted
– Typically something in the path is functioning, but not well
• Soft failures are hard to detect with traditional methods
– No obvious single event
– Sometimes no indication at all of any errors
• Independent testing is the only way to reliably find soft failures

Rebooted router to
fix forwarding table
Gradual failure
of optical line
card
Sample Soft Failures
Gb/s
normal
performance
degrading
performance
repair
one month

Testing Infrastructure – perfSONAR
• perfSONAR is:
– A widely-deployed test and measurement infrastructure
• ESnet, Internet2, US regional networks, international networks
• Laboratories, supercomputer centers, universities
• Individual Linux hosts at key network locations (POPs, Science DMZs, etc.)
– A suite of test and measurement tools
– A collaboration that builds and maintains the toolkit
• By installing perfSONAR, a site can leverage over 1400 test servers
deployed around the world
• perfSONAR is ideal for finding soft failures
– Alert to existence of problems
– Fault isolation
– Verification of correct operation

Lookup Service Directory Search:
http://stats.es.net/ServicesDirectory/
© 2016, Energy Sciences Network56 – ESnet Science Engagement (engage@es.net) - 12/20/2018

perfSONAR Dashboard: http://ps-
dashboard.es.net
© 2016, Energy Sciences Network57 – ESnet Science Engagement (engage@es.net) - 12/20/2018

Overview

Dedicated Systems – The Data Transfer Node
• The DTN is dedicated to data transfer
• Set up specifically for high-performance data movement
– System internals (BIOS, firmware, interrupts, etc.)
– Network stack
– Storage (global filesystem, Fibrechannel, local RAID, etc.)
– High performance tools
– No extraneous software
• Limitation of scope and function is powerful
– No conflicts with configuration for other tasks
– Small application set makes cybersecurity easier
• Limitation of application set is often a core security policy component

Data Transfer Tools For DTNs
• Parallelism is important
– It is often easier to achieve a given performance level with four parallel
connections than one connection
– Several tools offer parallel transfers, including Globus/GridFTP
• Latency interaction is critical
– Wide area data transfers have much higher latency than LAN transfers
– Many tools and protocols assume a LAN
• Workflow integration is important
• Key tools: Globus Online, HPN-SSH

Say NO to SCP (2016)
• Using the right data transfer tool is very important
• Sample Results: Berkeley, CA to Argonne, IL (near Chicago ) RTT = 53 ms,
network capacity = 10Gbps.
• Notes
– scp is 24x slower than GridFTP on this path!!
– to get more than 1 Gbps (125 MB/s) disk to disk requires RAID array.
– (Assumes host TCP buffers are set correctly for the RTT)
Tool Throughput
scp 330 Mbps
wget, GridFTP, FDT, 1 stream 6 Gbps
GridFTP and FDT, 4 streams 8 Gbps (disk limited)
61 – ESnet Science Engagement (engage@es.net) -
12/20/2018

Overview

The Data Transfer Superfecta: Science DMZ Model
Data Transfer Node
• Configured for data
transfer
• High performance
• Proper tools
perfSONAR
• Enables fault isolation
• Verify correct operation
• Widely deployed in ESnet
and other networks, as
well as sites and facilities
Science DMZ
• Dedicated location for DTN
• Proper security
• Easy to deploy - no need to redesign the
whole network
Engagement
• Resources & Knowledgebase
• Partnerships
• Education & Consulting

Context Setting
• DOE, NSF, and other agencies are
investing billions of dollars in state-of-
the-art cyberinfrastructure to support
data-intensive science.
• Many researchers do not understand
the value of these services and have
difficulty using them.
• A proactive effort is needed to drive
adoption of advanced services and
accelerate science output: Science
Engagement
12/20/2018 © 2016, Energy Sciences Network

Science Engagement
• The ESnet Science Engagement team's mission is to ensure that science
collaborations at every scale, in every domain, have the information and
tools they need to achieve maximum benefit from global networks through
the creation of scalable, community-driven strategies and approaches.
• Science Engagement team works in several areas at once
– Understand key elements which contribute to desired outcomes
• Requirements analysis – what is needed
• Also identify choke points, road blocks, missing components
– Network architecture, performance, best practice
– Systems engineering, consulting, troubleshooting
– Collaboration with others
– Workshops and webinars
12/20/2018 © 2016, Energy Sciences Network

• The Science DMZ design pattern provides a flexible model for supporting
high-performance data transfers and workflows
• Key elements:
– Accommodation of TCP
• Sufficient bandwidth to avoid congestion
• Loss-free IP service
– Location – near the site perimeter if possible
– Test and measurement
– Dedicated systems
– Appropriate security
– Science Engagement to foster adoption
Science DMZ Wrapup

Links and Lists
– ESnet fasterdata knowledge base
• http://fasterdata.es.net/
– Science DMZ paper
• http://www.es.net/assets/pubs_presos/sc13sciDMZ-final.pdf
– Science DMZ email list
• Send mail to sympa@lists.lbl.gov with subject "subscribe esnet-sciencedmz”
– perfSONAR
• http://fasterdata.es.net/performance-testing/perfsonar/
• http://www.perfsonar.net
– Globus
• https://www.globus.org/

Context: Science DMZ Adoption
• DOE National Laboratories
– Supercomputer centers, LHC sites, experimental facilities
– Both large and small sites
• NSF CC* programs have funded many Science DMZs
– Large investments across the US university complex: over $100M
– Significant strategic importance
• Outside the USA
– Australia
– Brazil
– UK
– More…
12/20/201868

Strategic Impacts
• What does this mean?
– We are in the midst of a significant cyberinfrastructure upgrade
– Enterprise networks need not be unduly perturbed 
• Significantly enhanced capabilities compared to 5 years ago
– Terabyte-scale data movement is much easier
– Petabyte-scale data movement possible outside the LHC experiments
• ~3.1Gbps = 1PB/month
• ~14Gbps = 1PB/week
– Widely-deployed tools are much better (e.g. Globus)
• Metcalfe’s Law of Network Utility
– Value of Science DMZ proportional to the number of DMZs
• n2 or n(logn) doesn’t matter – the effect is real
– Cyberinfrastructure value increases as we all upgrade
12/20/201869

Next Steps – Building On The Science DMZ
• Enhanced cyberinfrastructure substrate now exists
– Wide area networks (ESnet, GEANT, NRENs, Internet2, Regionals)
– Science DMZs connected to those networks
– DTNs in the Science DMZs
• What does the scientist see?
– Scientist sees a science application
• Data transfer
• Data portal
• Data analysis
– Science applications are the user interface to networks and DMZs
• Large-scale data-intensive science requires that we build science
applications on top of the substrate components
12/20/201870

Network Engineering for High Speed Data Sharing

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Network Engineering for High Speed Data Sharing