Inovação e tendências em Computação de Alto Desempenho: a … · 2014-11-24 · HP 17,4% SGI...
Transcript of Inovação e tendências em Computação de Alto Desempenho: a … · 2014-11-24 · HP 17,4% SGI...
© 2014 IBM Corporation
IBM Platform Computing
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Inovação e tendências em "Computação de Alto Desempenho": a visão da IBM
WORKSHOP EM COMPUTAÇÃO CIENTÍFICACENAPAD-SP – 20 ANOS
Marcelo L. BraunsteinLA Platform Computing Sales Exec
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IBM Platform Computing
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Anniversary Wall
Special thanks to Alan Brenner and Ed Seminaro!
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IBM CENAPAD/FAPESP 2010
• 40 nodes SMP IBM Power 7 (750) with 1280 Processingcores
• 32 cores Power 7(3,55 GHz), 128 GB RAM
• 6 nós GPU Nvidia Tesla• Storage 224 TB
• Performance: 42 TFlops• CPU 36 TFlops• GPU 6 Tflops
Second best in Brasil in 2010 !
Operational sinceDecember 2010
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IBM supercomputing leadership
Source: www.top500.org
Semiannual independent ranking of the top 500
supercomputers in the world
June 2014 TOP500 Aggregate Performance
Dawning0,5%
NUDT13,7%
Cray18,2%
Oracle0,3%
Dell2,5%
Bull2,6%
HP17,4%
SGI4,0%
IBM32,0%
Other8,9%
June 2014 TOP500 EntriesHP leads, followed by IBM
Other; 44Bull ; 16
Cray; 51
Oracle; 2
Dell; 8
HP; 184
SGI; 19
IBM; 176
IBM supercomputing leadership ...�Most installed aggregate throughput with over 88 Petaflops out of 274 Petaflops (32%) (Cray: 50/18%,
HP 46/17%, NUDT 37/14%)
Lead for 30 Lists in a row
�Most in TOP 10 with 4 (#3 LLNL-Sequoia BG/Q, #5 ANL-Mira BG/Q, #8 Juelich–JUQUEEN BG/Q, #9 LLNL-Vulcan BG/Q)
�Most in TOP 20 with 7, most in TOP 100 with 32
�Most 1 Petaflop or greater systems with 12 out of 37
�13 of 20 most energy-efficient systems
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IBM TOP100 Club – June 2014
Source: www.top500.org
Indicates new or improved entries
TOP500 Installation Processor Rmax TF/s3 DOE/NNSA/LLNL – Sequoia Blue Gene/Q, 1.6 GHz BQC, 96 racks 17173
5 DOE/SC/Argonne National Lab – Mira Blue Gene/Q, 1.6 GHz BQC, 48 racks 8587
8 Forschungszentrum Juelich (FZJ) - JUQUEEN Blue Gene/Q, 1.6 GHz BQC, 28 racks 5009
9 DOE/NNSA/LLNL – Vulcan Blue Gene/Q, 1.6 GHz BQC, 24 racks 4293
11 Exploration & Production –ENI HPC2 iDataPlex IvyBridge and Nvidia K20x 3003
12 LRZ-SuperMUC iDataPlex 18 islands of 512 nodes Sandy Bridge 2897
17 CINECA-Fermi Blue Gene/Q, 1.6 GHz BQC, 10 racks 1789
22 Power 775 IBM Development Engineering Power 775, 248 drawers 1515
23 Daresbury Laboratory BlueGene/Q, (8 racks) 1431
27 Max-Planck-Gesellschaft MPI/IPP iDataPlex DX360M4, Xeon E5-2680v2 10C 2.8GHz, FDR 1283
29 NCAR (National Center for Atmospheric Research) iDataPlex DX360M4, Xeon E5-2670 8C 2.600GHz, FDR 1258
33 University of Edinburgh BlueGene/Q, Power BQC 16C 1.60GHz, Custom 1073
41 Barcelona Supercomputing Center iDataPlex DX360M4, Xeon E5-2670 8C 2.600GHz, FDR 925
43 Rensselaer Polytechnic Institute BlueGene/Q, Power BQC 16C 1.60GHz, Custom 894
52 Indian Institute of Tropical Meteorology iDataPlex DX360M4, Xeon E5-2670 8C 2.600GHz, FDR 719
53 CNRS/IDRIS-GENCI BlueGene/Q, Power BQC 16C 1.60GHz, Custom 716
54 DOE/SC/Argonne National Laboratory BlueGene/Q, (4 racks) 716
55 EDF R&D BlueGene/Q, Power BQC 16C 1.60GHz 716
56 Swiss National Supercomputing Centre (CSCS) BlueGene/Q, Power BQC 16C 1.600GHz 716
57 Victorian Life Sciences Computation Initiative BlueGene/Q, Power BQC 16C 1.60GHz, Custom 716
58 Max-Planck-Gesellschaft MPI/IPP iDataPlex DX360M4, IVB 10C 2.8GHz, IB , NVIDIA K20x 710
60 ECMWF Power 775, POWER7 8C 3.836GHz 635
61 ECMWF Power 775, POWER7 8C 3.836GHz 635
68 High Energy Accelerator Research Org. /KEK BlueGene/Q, Power BQC 16C 1.600GHz 537
69 High Energy Accelerator Research Org./KEK BlueGene/Q, Power BQC 16C 1.60GHz, 537
78 United Kingdom Meteorological Office Power 775, POWER7 8C 3.836GHz 476
83 Exploration & Production - Eni S.p.A. iDataPlex DX360M4, Xeon E5-2670 8C 2.600GHz, FDR 454
84 Saudi Aramco iDataPlex DX360M4, Xeon E5-2670 8C 2.600GHz, QDR 442
85 China Meteorological Administration IBM Flex System p460, POWER7 8C 3.550GHz, QDR 435
86 China Meteorological Administration IBM Flex System p460, POWER7 8C 3.550GHz, QDR 435
92 NASA Center for Climate Simulation iDataPlex DX360M4, SB 2.8C 2.6GHz, QDR, Xeon Phi 417
98 United Kingdom Meteorological Office Power 775, POWER7 8C 3.836GHz 397
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Even though there is some stepping of the performance of the #1 system,
the relentless growth of the #500 clip level, #10 clip level and Total Aggregate
performance all are fairly straight line trends when plotted on log scale.
Source: www.top500.org
274 PF
33.86 PF
3.14 PF
134 TF
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IBM Platform Computing
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Over the long haul IBM has demonstrated continued leadership in various
TOP500 metrics, even as the performance continues it’s relentless growth.
Source: www.top500.org
Blue Square Markers Indicate IBM Leadership (Most Aggregate; #1 System; Most in TOP10; Most entries on TOP500 list)
IBM has most aggregate performance for last 30 listsIBM has #1 system for 11 out of last 20 lists (14 in total)
IBM has most in Top10 for 19 out of last 22 listsIBM has most systems 19 out of last 31 lists
33.86 PF
3.14 PF
134 TF
274 PF
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IBM Platform Computing
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Waves of Technology
Back-OfficeComputing
Client-Server PC - 1981
World Wide Web and eBusiness
Confluence of Social, Mobile, Cloud, Big Data / Analytics
90’s80’s60’s We are here
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Nova era de IT
Cloud Social
Analytics Mobile
Security
Garantindo a segurançadas transações
Eficiência e entregade novos produtosde forma rápida.
Manipulando grandesvolumes de dados e gerando insights emtempo real
Revolucionando o compartilhamento de informações.
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Explosion of data
Inflexible IT infrastructures
Escalating IT complexity
How to spot trends, predict outcomes and take meaningful actions?
How to manage inflexible, siloedsystems and business processes to improve business agility?
How to manage IT costs and complexity while speeding time-to-market for new services?
With this focus, IBM is addressing critical IT trends for
Technical Computing users
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Application
Businesses Need to Overcome Infrastructure Limitations To maximize the value of compute and data-intensive applications
ApplicationExamples• Simulation• Analysis• Design• Big data
IT constrained• Long wait times• Low utilization• IT Sprawl
Platform Computing
Application B (Custom, MPI)
Application A (Packaged ISV)
Application C (Big Data)
Today Future
Benefits• High utilization• Throughput• Performance• Prioritization• Reduced cost
Repeated for many
applications and groups
• Clusters• Grid• HPC Cloud
Faster time
to results
Use fewer
resources
Faster time
to results
Use fewer
resources
Faster time
to results
Repeated for many
applications and groups
Faster time
to results
Use fewer
resources
Faster time
to results
Use fewer
resources
Faster time
to results
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Optimization throughout the hardware and software stack from data ingest, thru run-time and output enables architectural tradeoffs to deliver business value
Low
Medium
High
# Cores DAS
External I/OInterconnect
Low
Medium
High
# Cores DAS
External I/OInterconnect
Low
Medium
High
# Cores DAS
External I/OInterconnect
Low
Medium
High
# Cores DAS
External I/OInterconnect
+ =+
Traditional HPC High Velocity Workloads High Volume WorkloadsWorkflow-Optimized Big
Data/Big Workloads
+ =+
Future architecture must handle data-centric locality issues
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Data Centric ComputingMoving Data is Expensive in Time and Energy
� Architecture and Solutions that support HPC (High Performance Computing) and HPA (High Performance Analytics) and Workflows Including Both
� Roadmap to Exascale for Data, Analytics and Modeling
� Putting Processing Near the Memory (in the Memory): Hybrid/Active Memory Cube
Data lives on disk and tapeMove data to CPU as neededDeep Storage Hierarchy
Data lives in persistent memoryMany CPU’’’’s surround and useShallow/Flat Storage Hierarchy
Old Compute-Centric Model New Data-Centric Model
Huge impact on hardware, systems software, and application design !
Flash Phase Change
Manycore FPGA
Massive ParallelismPersistent Memory
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IBM Platform Computing
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The Complete Data Management Solution for Enterprise Environments
• Enabling a secure, reliable, transparent cloud storage tier in GPFS
• Single namespace for tiering, backup, DR and multi-cluster access• Transparently migrate data to cloud storage
• Allow for more than one tier of cloud storage possibly using multiple provider
Elastic Storage
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Building collaboration and innovation at all levels
Welcoming new members in all areas of the ecosystem
100+ inquiries and numerous active dialogues underway
Boards / Systems
I/O / Storage / Acceleration
Chip / SOC
System / Software / Services
Implementation / HPC / Research
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IBM Platform Computing
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What are Software Defined Environments (SDE)?
With IBM’s Software Defined Environment,
infrastructure is fully programmable to
rapidly deploy workloads on optimal
resources and to instantly respond to
changing business demands
Software
Defined
Environments
Abstracted and virtualized IT infrastructure resources managed by software
Applications that define infrastructure requirements and configuration
IT infrastructure that extends multiple environments to go beyond the data center
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Why OpenStack for Cloud?
� Provides an Open alternative to proprietary cloud stacks
� Protects clients current investment with simple path to new technology
� Open APIs provides great flexibility and agility
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Platform Computing – one integral solution for all your high performance application middleware requirements
Workload and Resource
Management
Data Management
Infrastructure Management
Platform LSF Family
Batch, MPI workloads with process mgmt, monitoring,
analytics, user portal, license mgmt
Platform HPC
Simplified, integrated HPC management software for
batch, MPI workloads integrated with systems
Platform Symphony Family
High throughput, near ‘real time’ parallel compute and Big Data / MapReduce workloads
Big Data / Hadoop
Simulation / Modeling
AnalyticsApplications
Heterogeneous
Resources
Compute Storage Network
Virtual, Physical, Desktop, Server, Cloud
Platform Cluster Manager Family (inc xCat)Provision and manage Single Cluster to Dynamic Clouds
Elastic Storage (GPFS)High performance, distributed parallel file system
Common Technology Foundation
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Platform LSF & Platform Symphony SaaS
IBM Platform Computing Cloud Service (SaaS)
IBM Platform LSF IBM Platform Symphony
24X7 CloudOps Support
Simulation / Modeling Analytics
IBM Elastic Storage (GPFS)
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Platform Computing Cloud Services
IBM Confidential20
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Customer examplesLeading Formula 1 race team• Complex simulations and analysis with short time frames and
strict regulations on cluster size• Ease-of-use, application license optimization, high IT productivity
Large global financial services provider• Global grid supporting market analysis, pricing and risk analytics/
compliance for 200+ applications• 14 business units sharing grid across 4 data centers
Leader in market driven innovation and science• Global research for HPC, big data and analytics with dynamic
compute and Hadoop clusters• Highly secure HPC cloud shareable across domains
Leading major aircraft manufacturer• Complete aircraft design and simulation across global teams• Reducing time to market with highly automated workflow driven
processes, application license optimization, heterogeneous shared services and optimal job placement
Repeated for many
applications and groups
Faster time
to results
Use fewer
resources
Faster time
to results
Use fewer
resources
Faster time
to results
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IBM Platform Computing
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Watson is cognitive computing
Understandsnatural
language
Generates and
evaluates hypotheses
Adaptsand learns
Existing technologies fall short of expectations� Business rules have to be created
manually
� System knows only what has been coded
� Manual monitoring and intervention required to update system
Watson is different■You don’t program Watson, you train and teach it
■There is an unlimited capacity to scale Watson’s knowledge
■Watson learns and adapts based on usage over time
© 2014 International Business Machines Corporation
Customers want self-serve solutions now
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IBM Platform Computing
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MD Anderson Cancer Center Oncology Expert AdvisorTM
Powered by IBM Watson and Power Systems
Patient Evaluation Rx and Management Plan Care Pathway Advisor Patient Driven Research
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IBM Platform Computing
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Human Systems
Service Systems
IBM Research Brazil: Research Areas
Natural Resources
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School X –Classroom
Transcription Systems Good
morning.Today we will be talking about an specific set of mathematic rules: trigonometry.
School X –Classroom
Transcription Systems
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Smart Devices
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Marcelo L. BraunsteinLatin America Platform Computing Sales Exec
Cel: (55-21) 99222-3500
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