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Technical Computing / High Performance ComputingUniversity Perspective
Chris Maher, IBM Vice President HPC [email protected]
Agenda
• Industry Expansion of HPC and Technical Computing
• Universities and HPC
• Taming the Growing Data Explosion
• Why HPC Cloud
• Technical Computing Systems
• University Resources and University Examples
• Putting it all together with Datatrend Technologies
Smarter traffic systems
Smarter water mgmt
Smarter energy grids
Smarter healthcare
Smarter food systems
Intelligent oil field technologies
Smarter regions
Smarter weather
Smarter countries
Smarter supply chains
Smarter cities
Smarter retail
...and this is driving a new economic climate.
The world is getting smarter – more instrumented, interconnected, intelligent
Technical computing is being applied to a broader set of industries enabling more areas for collaborative work at universities
Large Industrial sector applications
HPC
“en
try
cost
s”–
inve
stm
ent
and
skill
nee
ded
Timeline
High
Low
SupercomputersScience, Research &
Government
SupercomputersScience, Research &
Government
Broad adoption across a variety of industries as technology becomes affordable & pervasiveUsage driven by modeling, simulation, predictive analysis workloadsDelivered via Clusters, Grids and Cloud
SupercomputersScience, Research &
Government
Automotive Aerospace Engineering
PetroleumElectronic
Design Automation
Life SciencesFinancial Services Digital Media
ExascaleThe Next Grand
Challenge
1990’s 2010’s
HPC 1.0 HPC 1.5
HPC 2.0
HPC
Pro
blem
Dom
ains
Add
ress
ed
“PhysicsDriven”
“Data Driven”
“Applied”Technical
Computing
“Mainstream”Technical Computing
Research Engineering/Simulations Analysis/Big Data/Cloud deployments
+ +
• Computational analysis• Upstream/downstream processing• Next-generation genomics• Satellite ground stations• Video capture and surveillance• 3-D computer modeling• Social media analysis• Data mining/unstructured
information analysis (Watson-like)• Financial “tick” data analysis• Large-scale real-time CRM
Examples of growth for Technical Computing
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Industry TrendsThe Data Deluge
• Big data, big data management consuming researchers now• Very large projects have data measured in the 100s of petabytes
Expanding the role of HPC and HPC Cloud on Campus• Myriad of campus needs for both high throughput computing and high
performance (capability) computing using a shared environment• Best practices show cost reduction with central condominium facility
where researchers can contribute their grant money and which serves the larger university community
• HPC makes a university more competitive for grantsExascale computing will be a reality in 2018/9
• Petascale has been delivered(2008)• Large scale is being tackled now• In 2018, will large university installations have a multi petaflop computer?
What will house it?What will be the power requirements?The Power Utilization Efficiency (PUE) of your datacenter is as important as the “green solution” you put in it.
Agenda
• Industry Expansion of HPC and Technical Computing
• Universities and HPC
• Taming the Growing Data Explosion
• Why HPC Cloud
• Technical Computing Systems
• University Resources and University Examples
• Putting it all together with Datatrend Technologies
8
What we are seeing as trends at the University Level
• HPC is growing at a robust CAGR (6.9% according to Tabor)
• HPC is required for a research university to attract faculty.
• VP of Research titles changing to VP of Research and Economic Development acknowledging that joint ventures with companies is a MUST for universities
• Greater partnerships with new industries
• Power, cooling and space are making universities think about central vs. decentralized computing (total cost of ownership)
• Next Generation Sequencing and in silico Biology, High Energy Physics, Search and Surveillance, Nanotechnology, Analytics are key workload areas Use of accelerators (for example nVidia)
• HPC in the CLOUD becoming more relevant
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Sample Workload/ISVs• In silico Biology– Amber, NAMD, BLAST, FAST/A, HMMer, NGS.
• Computational Chemistry– Gaussian, Jaguar, VASP, MOE, Open Eye, Accelrys Material Studio.
• Matlab– used in most medical school settings
• Statistics– IBM SPSS or SAS
• High Energy Physics– workload from Cern LHC– Monte Carlo techniques
• Quantum Physics– Quantum Chromodynamics (QCD)
• Analytics– COGNOS, Big Insights, InfoSphere Streams (large data being generated by the Square Kilometer Array), CERN, and Smarter Planet initiatives.
Agenda
• Industry Expansion of HPC and Technical Computing
• Universities and HPC
• Taming the Growing Data Explosion
• Why HPC Cloud
• Technical Computing Systems
• University Resources and University Examples
• Putting it all together with Datatrend Technologies
All these and more are contributing to the Growing Data Explosion
1980 1990 2000 2010
Megabytes
Gigabytes
Terabytes
Petabytes
Kilobytes
Half a Zettabyte of Annual IP Traffic by 2013 (a trillion gigabytes; 1 followed by 21 zeroes)
MRIs will generate a Petabyteof data in 2010
Text messages generate 400TB of data per day (US)
“IDC’s annual Digital Universe… indicates that over the next 10 years, data generation is expected to increase a staggering 44x” *
“IDC’s annual Digital Universe… indicates that over the next 10 years, data generation is expected to increase a staggering 44x” *
* The Ripple Effect of Seagate's 3TB External HDDJuly 06, 2010 - IDC Link
Data Centric Thinking
inputoutput
Data lives on disk and tapeMove data to CPU as neededDeep Storage Hierarchy
Data becomes Center of AttentionWe are never certain exactly where it is
•Although we can ask Abstraction allows for specializationAbstraction allows for Storage Evolution
DataData
Today’s Compute-Focused Model Future Data-Focused Model
Top Storage/Data Issues
Source: 2010 InfoPro Survey
0% 10% 20% 30% 40% 50% 60% 70%
Storage Provisioning
Archiving / Archive Mgmt
Performance Problems
Managing Complexity
Backup Administration
Managing Costs
Forecasting / Reporting
Managing Storage Growth
At look at Next Generation Sequencing
• Growth is 10x YTY
Sequencers can generate 2TB+ of final data per week/sequencer. Processing the data is compute intensive; the data storage is PBs per medium sized institution. For
example, BGI in China currently has 10 PB.
Managing the data explosion from NGS
Average Storage Cost Trends
Source: Disk - Industry Analysts, Tape - IBM
2003 2004 2005 2006 2007 2008 2009 2010 2011$0.01
$50.00
$1.00
$10.00
$/G
B
Industry Disk HC LC Disk Average Tape
Projected Storage Prices
Use of Tape Technology
• Virtual Tape + deduplication growing technology for secondary data– Key value – time to restore
– Use compute to reduce hardware costs
– Add HA clustering and remote site replication
• Tape used as the “Store” in large HPC configurations– Files required for job staged from tape to disk ‘cache’ by a data mover (HPSS)
– Results written to disk, then destaged back to Tape
• Hybrid disk and tape use for archive applications – large capacity, long term retention– Metadata on Disk, Content on Tape
– Lowest cost storage
– Lowest power consumption
– Most space efficient
– Long life media• Specialty Niche – removable media interchange
Any statements or images regarding IBM's future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.
Agenda
• Industry Expansion of HPC and Technical Computing
• Universities and HPC
• Taming the Growing Data Explosion
• Why HPC Cloud
• Technical Computing Systems
• University Resources and University Examples
• Putting it all together with Datatrend Technologies
High Performance Computing continues to evolve
HPCCluster
HPCGrid
HPCCloud
SingleSystem
Why are Universities exploring Clouds?• Cost Efficiency
– Consolidation and sharing of infrastructure
– Leverage resource pooling for centralized policy administration• System/Configuration Management Policies
• Energy-related Policies
• Security-related Policies
• User-related Policies
• Flexibility– End-user self-service cloud portal enablement
– Exploit advanced automation to free technical resources for higher value work
– Enhanced access to specialized resources (e.g. GPUs)
– Dynamic on demand provisioning and scaling
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IBM’s new HPC Cloud addresses the specific intersection of high performance computing and cloud computing
CloudBurst
ISDM, TPM, TSAM
Virtual Machine Provisioning
Intelligent Cluster
HPC Management Suite
Bare Metal & VM Provisioning
System x, BladeCenter
System p, System z
SAN, NAS
1Gigabit Ethernet
iDataPlex
BlueGene, System p 775
GPFS, SONAS
InfiBand, 10-40 GbE
General PurposeComputing
High PerformanceComputing
CloudComputing
Stand-aloneComputing
IBM’s HPC Cloud is being deployedat clients such as the phase 2 pilot at NTU
Needs include–Batch job scheduling – several unique schedulers and runtime libraries–Parallel application development and debugging, scaling and tuning–Parallel data access–Low latency, high bandwidth interconnects
Environment Characteristics
Full and direct access to system resources (bare metal pooling)
Efficient virtualization, where applicable (KVM and VMWare pooling)
Diverse technologies – Windows & Linux– Diverse cluster
managers
Agenda
• Industry Expansion of HPC and Technical Computing
• Universities and HPC
• Taming the Growing Data Explosion
• Why HPC Cloud
• Technical Computing Systems
• University Resources and University Examples
• Putting it all together with Datatrend Technologies
New Era of Technical Computing SystemsHardware + Software + Services = Systems and Solutions
Purpose built, optimized offerings for Supercomputing- iDataPlex, DCS3700 Storage, TS3500 Tape Library
Full array of standard hardware offerings for Technical Computing- Intel- based IBM blade servers, IBM Rack Servers, x3850X5 SMPs, Integrated Networking Solutions, Storage Products (DCS3700)
Hardware
+ Software- Parallel File Systems - Resource Management
= Systems & SolutionsHPC Cloud Offerings from IBM- IBM HPC Management Suite for Cloud- IBM Engineering Solutions for Cloud: HPC cloud offerings optimized for Electronics, Automotive & Aerospace clients
Intelligent Cluster- IBM Intelligent Cluster solutions: Integrated, optimized w/servers, storage and switches
+ Services
- HPC Cloud Quick Start Implementation Services - Technical Computing Services Offering Portfolio:Full range of customizable services to help clients design, develop, integrate, optimize, validate and deploy comprehensive solutions to address their Technical Computing challenges
- Parallel Application Development Tools- Systems Management
ISV Solutions - Partnering with leading ISVs to maximize the value of our joint solutions
IBMResearchInnovation
Agenda
• Industry Expansion of HPC and Technical Computing
• Universities and HPC
• Taming the Growing Data Explosion
• Why HPC Cloud
• Technical Computing Systems
• University Resources and University Examples
• Putting it all together with Datatrend Technologies
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University Relations (UR) and STG University Alliances
• IBM University Relations: Resources for educators, researchers, staff and students
–https://www.ibm.com/developerworks/university/
• IBM Systems and Technolgy Group University Alliances
–Responsible for guiding STG research and collaboration with universities
–Enables new opportunities for deploying IBM systems and solutions at universities
–RTP Center for Advanced Studies headed by Dr. Andrew Rindos, [email protected]
University Relations Teaming Examples
IBM, Imperial College, government & industry partners to invest ~ $81M for Digital City Research project to develop & implement the next generation infrastructure, systems & services to modernize cities (i.e. make cities smarter) Goals include connecting citizens to real time intelligence,
bring value through smart decision making, generating commercial, creative and social opportunities to enhance quality of life
In addition catalyse the next generation of digital services inhealthcare, energy, transportation and creative industries.
Proposed Collaboration w/ Imperial College London : Digital City Lab (DCL)
SUR Project : Smarter Infrastructure Lab for Smarter Cities
MOU signed creating SI Lab collaboration taking a system of systems view of a university managed like a smart city using sensors, data, and analyticsGoals include development of fixed & mobile infrastructure
analytics technologies & solutions for a smarter city (e.g. smart water, waste, buildings, energy, transportation, healthcare, environment, etc.). Also to provide a showcase for client visits & demonstrations of IBM Smarter Cities technologies
Future proposal to have lab become part of larger Pennsylvania Smarter Infrastructure Incubator Initiative
SUR Project : Smarter City Solutions For China
Tongji University signed a Smarter City Initiative collaboration agreement aimed at building and providing integrated IBM Smarter City solutions for ChinaGoal of collaboration is to overcome the current silo decision
making by different government ministries and to provide a city mayor and other decision makers an integrated Smarter City framework, solution package, and a real life city modelToJU will partner with IBM on Smart City projects based on
ToJU's urban planning work in several cities (Shanghai Pudong, Hangzhou & Yiwu )
IBM & Swansea University (Wales UK)Partner for Economic Dev’t
The vision for the collaboration is economic dev’t & job creation ; build state of the art HPC capability across the universities in Wales to provide enabling technology that delivers research innovation, high level skills dev’t and transformational ICT for economic benefit. Wales infrastructure is linked to the larger UKQCD consortium (19 UK Particle Physicists and Computing Scientists from 19 UK universities) that share computing resourcesSeeded w/ SUR award which drove revenue of $2.4M in 2010
University of Victoria
Industries: Higher EducationURL: http://www.uvic.ca/
Upgrading old hardware while significantly boosting performance and research capabilities
The need:Requirement to replace original circa 1999 UNIX machines
Principal Investigator’s key requirement was research collaboration
Physics Department main requirement was only for FLOPs / $$ for performance was key
Solution:A research capability computing facility of 380 iDataplex Nodes (2x Intel x5650’s 1:1 InfiniBand)
A performance/capacity cluster of iDataplex nodes (2x Intel x5650’s 2x 1Gig)
High Performance Focused on Benchmark results (disk I/O and Jitter performance)
The benefits:Research time cut by 50%
Power and cooling was 40% less while gaining 30% throughput benefits
St. Jude’s Children’s Research HospitalSimplifies storage management to meet researchers needs
Business challenge:St. Jude’s Children’s Research Hospital , based in Memphis, TN, is a leading pediatric treatment and research facility focused on children's catastrophic diseases. The mission of St. Jude Children’s Research Hospital is to advance cures, and means of prevention, for pediatric catastrophic diseases through research and treatment. Their current NAS solution was not scalable to meet researchers needs and tiering of data was becoming an arduous process.
Solution:St. Jude’s viewed IBM as a thought leader is storage virtualization. IBM SONAS was deployed to provide a single, scalable namespace for all researchers. IBM Tivoli Storage Management and Hierarchical Storage Management automated tiering and backup of all data allow IT to focus on the needs of research. St Jude’s was able to simplify their storage management while providing the ability to meet researchers needs. Benefits:
A single, scalable, name space for all users that can be enhanced and upgraded with no down time
Avoided the expense, time and risk of manually moving data to improve reliability and access to the information
Able to adjust to dynamic business requirements, reduce maintenance, lower integration costs, and seamlessly bridge to new technologies
Solution components:IBM SONASTivoli TSM & HSMIBM ProtecTIERDS50003 years hardware & software maintenanceIBM Global Technology Services
East Carolina UniversityAdvancing Life Sciences Research with an IBM Intelligent Clustersolution based on IBM BladeCenter technologies
The need:Without a dedicated supercomputer capable of running massively parallel computational tasks, the Biology department at ECU could not run models as quickly as it needed. Researchers were frustrated by slow performance, and scientists were forced to spend time resolving IT issues.
The solution:ECU selected an IBM® Intelligent Cluster™ solution based on IBM BladeCenter® servers powered by Intel® Xeon® 5650 processors, working with Datatrend Technologies Inc. to deploy it. The solution was delivered as a preintegrated, pretested platform for high-performance computing, and includes remote management from Gridcore.
The benefit:ECU can now run up to ten typical computational tasks in parallelUsing all 100 Intel processor cores, models that might previously have taken a day are completed in a matter of minutesEfficient, easy-to-scale solution opens up new research possibilities for the future.
“There are some analyses that make use of all 96 cores… Previously, a task of this magnitude might have taken a full day of computation to complete. With the IBM Intelligent Cluster, it takes just minutes.”
—Professor Jason Bond, East Carolina University
Solution components:IBM® Intelligent Cluster™IBM BladeCenter® HS22
XSP03265-USEN-00
Agenda
• Industry Expansion of HPC and Technical Computing
• Universities and HPC
• Taming the Growing Data Explosion
• Why HPC Cloud
• Technical Computing Systems and University Resources
• University Examples
• Putting it all together with Datatrend Technologies
Putting it All Together… Literally with Datatrend Technolgies
Doug Beary, Technical Account ExecutiveDatatrend Technologies919-961-4777, [email protected]
High Performance Computing PlatformsDatatrend Technologies can help put it All Together –
Providing a Solution
• HPC Clusters– Compute, Interconnect & Storage
• Workload Fit– Distributed Memory (MPI)
• Scale Out: iDataplex, Blades, Rack
– Shared Memory (SMP)• Large Scale SMP: ScaleMP, NumaScale
– Hybrid Systems
• Management System– xCAT, MOAB, eGompute
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HPC Clusters
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Platform Optimization– Optimize Processor Selection
• Performance/$• Performance/W
– Optimize Form Factor– Optimize Delivery & Installation
Typical 84 Node Cluster• 100 to 1000 boxes• Optimize Form Factor• Optimize Delivery &
Installation
Datatrend Solution• One Item
Top Components• Fastest CPUs• Flexible Interconnect Choices
Fabric, Card, Switch, Cabling• Unmatched Storage to Meet
Any CapacityAny Performance
Workload Fit• Distributed Memory
– Most Common Cluster– Under Desk to PetaFlops– 100s to 100,000+ Cores– Many OS Images
• Shared Memory– Growing Demand– Dozens to 1000’s of Cores– 64+TB Memory– One OS
• Hybrid– Do Both on One platform!!
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Hyper-Scale ClusterUp to: 126 Nodes, 1512 cores, 23.6TB • Simple Scaling
• 126 Nodes in 2 Racks• Full Blade Chassis: 9
• Bandwidth:• *Bi-sectional bandwidth:
64%• Largest non-blocking
Island: 14 nodes
• Low Latency• Max. 200ns
Distributed Memory, Shared Memory or BOTH!!
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