Introduction to HPC in Canada - WestGrid · PDF fileIntroduction to HPC in Canada Erming Pei...
Transcript of Introduction to HPC in Canada - WestGrid · PDF fileIntroduction to HPC in Canada Erming Pei...
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Introduction to HPC in Canada
Erming Pei
Research Computing Group, UAlbertaCompute Canada / WestGrid
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Outline & Schedule
• 10:00 Introduction to Compute Canada (15’)• 10:15 Introduction to WestGrid (15’)• 10:30 Q&A -1 (5’)• 10:35 Break (10’)• 10:45 Introduction to HPC (40’)• 11:25 Q&A -2 (5’)
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Introduction to Compute Canada
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About Compute Canada
• Compute Canada integrates 4 regional HPC consortia across the country– provides a shared HPC/ARC infrastructure across Canada– supports world-level leading-edge research activities.
• CC aggregates petaflops of computing power and petabytes storage capacity over Canada's high-performance networks.
• CC provides overall services including infrastructure, application, operation and user support for national-wide users.
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Compute ConsortiaPreviously, there were 7 consortia.• ACENET • CLUMEQ • RQCHP• HPCVL• SciNet• SHARCNET • WestGrid
Currently, it has been consolidated into four consortia.• WestGrid• Compute Ontario• Calcul Québec• ACENET
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Existing Systems & Resources
• ~40 Universities• ~27 Data Centers• ~50 Systems • ~200,000 cores, 2 Pflops, 20PB• ~100 of research software packages • ~200 experts in utilization of ARC for research
https://www.westgrid.ca/events/responding-to-canadas-research-computing-needs
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New CC Systems
• UVic, GP1 (Cloud)
• SFU, GP2 (General Purpose)
• UW, GP3 (General Purpose)
• UofT, LP (Large Parallel)
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Schedule of New CC SystemsSite/Service Description Availability Resource
GP1 - UVic Large Openstack Cloud
Sept., 2016 3000cores + 40% expansion (2017)
GP2 - SFU General purpose cluster + Cloud partition
Feb., 2017 18,000cores+ 40% expansion (2017)1923 GPU nodes
GP3 - Waterloo Ditto May, 2017 19,000 cores + 40% expansion (2017)64 GPU nodes
LP - UToronto Large parallel Dec., 2017 66,000 cores
National Storage Infrastructure
HSM + Object Storage (All 4 sites)
Oct., 2016 Dozens PBs10PB to start
https://www.computecanada.ca/renewing-canadas-advanced-research-computing-platform/new-systems-at-four-national-sites/
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Continuing Development
• Consolidation by 2018– 5-10 Data Centres– 300,000 cores, 12 Pflops, 50+ PB
• 2016-17: Commissioning new systems while decommissioning old systems
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CC New Organization Chart
https://staff.computecanada.ca/national_teams/chart
TLC SLC
CloudGP2 GP1
MONLP GP3
NW PSNT RS Storage
SWG
EOT VIZ DH Bio-M SPNTBio-Info
SC
Administration
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CC Cloud Service
• Currently Compute Canada has mainly two cloud systems: Cloud West and Cloud East
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Access CC clouds
• Cloud East: http://east.cloud.computecanada.ca
• Cloud West: http://west.cloud.computecanada.ca
• Can access with your CC account
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CC Cloud Service
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OwnCloud
• A Dropbox-like cloud storage service– hosted by WestGrid
• Can access with WestGrid user/password
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Globus Online
• High performance data transfer service• https://globus.computecanada.ca
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Globus Online
• Needs MyProxy authentication (WestGrid login/passwd)• Can select existing endpoints (GridFTP service in sites)• Can create your personal endpoint with “Globus Connect
Personal”
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Intro to WestGrid
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About WestGrid
USask
UBC
SFUUVi
c
UNBC
ULeth
UofC Uof
MUofW
UofR
UofA
Banff Center
BU
AU
• WestGrid is one of four regional HPC consortia of Compute Canada
• WestGrid itself has 15 partner institutions across British Columbia, Alberta, Saskatchewan and Manitoba.
TRU
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Overall Resources
2012/13
• By far, WestGrid has more than 40,000 compute cores and 9PB storage space.
• About 1,000 Compute Canada users from 475 projects are currently using WestGrid systems.
Text and image source: Lindsay Sill, Intro to WestGrid 2013
* HQP stands for highly qualified personnel
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Text and image source: Lindsay Sill, Intro to WestGrid 2013
WestGrid Staff
• Executive Director (Lindsay Sill)• Director of Operations (Patrick Mann)• Collaboration Coordinator• Visualization Coordinator• Site Leads• Programmers• System Analysts• System Administrators
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WestGrid Facilities, UofA (Jasper)
• Processors: 4160 cores– 240 nodes with Xeon X5675 processors, 12 cores (2 x 6) and 24 GB of memory. – 160 nodes with Xeon L5420 processors, 8 cores (2 x 4) and 16 GB of memory.
– Interconnect: • Infiniband QDR, 40 Gbit/s, with a 1:1 blocking factor• Infiniband DDR, 20 Gbit/s, with a 2:1 blocking factor
– Storage: ~830TB (356TB Lustre + 280 TB storage servers + 192TB IS10K)– Quickstart: http://www.westgrid.ca/support/quickstart/jasper
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WestGrid Facilities, UofA (Hungabee)
• Processors: 2048 coresShared-memory multiprocessor, comprises an SGI UV100 login node and an SGI UV1000 computational node, 16TB memory.
• Interconnect: ccNUMA(cache-coherent non-uniform memory access ), combination of Intel's Quickpath and SGI's NUMAlink
• Storage: 53TB NFS, and 356TB Lustre shared with Jasper• Quickstart: www.westgrid.ca/support/quickstart/hungabee
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WestGrid Facilities, UBC (Orcinus)
• Processors: 9600 cores (3072 Intel Xeon E5450 quad-core/16GB RAM + 6528 Xeon X5650 six-core/24GB RAM)
• Storage: ~450TB, Lustre• QuickStart: www.westgrid.ca/support/quickstart/orcinus
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WestGrid Facilities, UofC (Breezy)
• Processors: 384 cores (16 node Appro AMD cluster with quad-socket, 6-core AMD Istanbul processors (24 cores @ 2.4 GHz) per node, 256GB RAM/node)
• Interconnect: 4X DDR InfiniBand• Storage: ~450TB, IBRIX• Quickstart: http://www.westgrid.ca/support/quickstart/breezy
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WestGrid Facilities, UofC (Lattice)
• Processors: 4096 cores– 512 nodes with Intel Xeon L5520 8-core processor, 12 GB of memory.
– Interconnect: • InfiniBand 4X QDR (Quad Data Rate) 40 Gbit/s, 2:1 blocking
– Storage: 160 TB shared with Lattice and Breezy– Quickstart: http://www.westgrid.ca/support/quickstart/lattice
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WestGrid Facilities, UofC (Parallel)
• Processors: 7056 cores– 528 12-core standard Xeon E5649 nodes, 24 GB of RAM.– 60 special nodes with 3 GPGPUs each (NVIDIA Tesla M2070s, 5.5 GB Memory).
• Interconnect: – InfiniBand 4X QDR (Quad Data Rate) 40 Gbit/s, 2:1 blocking
– Storage: 160 TB shared with Lattice and Breezy– Quickstart: http://www.westgrid.ca/support/quickstart/lattice
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WestGrid Facilities, UM (Grex)
• Processors: 3792 cores (316 SGI Altix XE cluster, with two 6-core Intel Xeon X5650 2.66GHz processors, 48-96GB RAM/node
• Interconnect: Non-blocking Infiniband 4X QDR• Storage: >100TB• Quickstart: www.westgrid.ca/support/quickstart/glacier
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WestGrid Facilities, UVic (Hermes/Nestor)
• Processors: 4416 cores [2112 (Hermes), 2304 (Nestor) ]– IBM iDataplex server with eight 2.67-GHz Xeon x5550 cores with 24 GB of RAM– Dell C6100 servers with twelve 2.66-GHz Xeon x5650 cores and 24 GB of RAM
• Interconnect: – 84 Hermes nodes use two bonded Gigabit/s Ethernet links– New Hermes 4X QDR non-blocking, 32-40Gb/s
• Storage: 1.2PB, GPFS• Quickstart: www.westgrid.ca/support/quickstart/hermes_nestor
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WestGrid Facilities, SFU (Bugaboo)
• Processors: 4584 cores– 16 nodes with Intel Xeon E5430 4-core, 16GB/node;– 254 node with Xeon X5650 6-core processor, 24GB/node – 16 Xeon X5355 quad-core processor, 16GB/node
• Interconnect: Infiniband using a 288-port QLogic switch• Storage: ~700TB• Quickstart: www.westgrid.ca/support/quickstart/bugaboo
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WestGrid Facilities, USask(Silo)
• Disk: 4.2 PB raw total, 3.15 PB usable– 600 x 1TB SATA drives, RAID 6– 1800 x 2TB SATA drives, RAID 6
• Tape: IBM LTO 3584 tape library– ~3PB total, 1460 x LTO4 tapes, 920 LTO5 tapes.
• Backup System: IBM Tivoli Storage Manager (TSM)– Quickstart: http://www.westgrid.ca/support/quickstart/silo
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Site Status
https://www.westgrid.ca/support/system_status
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Use CC/WestGrid
• Apply for a CC/WestGrid account• Get a Grid Certificate / Proxy• Existing Resource Classification• New Resource Allocation• Software • Site status• Technical Support
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CC/WestGrid Account1. First ask your PI to apply for a Compute Canada account if he/she doesn’t have.
2. Then, you yourself apply for Compute Canada account as part of your PI’s project.
https://www.westgrid.ca/support/accounts/getting_account
3. Your PI approves your application
4. You apply for an consortia account, e.g. WestGrid, ACEnet
Note: It takes a couple of days for your account to be created on all sites.
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Grid Certificate 1. Log in to http://portal.westgrid.ca and “Request a Grid Certificate”2. In “My Account” webpage, you will see two buttons for downloading you Grid certificate and private key.
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Grid Proxy• Grid proxy is used in submitting Grid jobs or transferring
files across Grid. (Limited lifetime and limited privileges)
• Users just need log in to any WestGrid site and then run: – myproxy-logon
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Resource Classification
Program Type SitesSerial Bugaboo, Hermes, JasperParallel Bugaboo, Nestor, Orcinus, Lattice, Parallel,
Jasper, GrexSMP Parallel Breezy, HungabeeLarge memory Grex, Breezy, HungabeeVisualization ParallelGaussian GrexMatlab Orcinus (distributed computing toolbox),
Jasper/Hungabee (UofA license), etc.Storage Silo, Bugaboo
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Software
• WestGrid has both free and commercial software.
• You can use software packages in WestGrid– check this webpage to see if certain
software release is already avaliable on WestGrid
• Software list webpagehttps://www.westgrid.ca/support/software
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New Resource Allocation
• RAC (Resource Allocation Competition)– https://www.westgrid.ca/support/accounts/resource_allocations
• RAC = RPP + RRG– RPP: Research Platforms and Portals (scientific/technical review needed)
– RRG: Resources for Research Groups (scientific/technical review needed)
• RAS: Rapid Access Service (formerly “Default Allocation”). No scientific/technical review needed
Email to:[email protected] / [email protected]
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New RAC Schedule
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Introduction to HPC
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Outline• What is HPC• Capability vs. Capacity• Programming model
– Serial/Parallel
• Architecture– SMP/DSM/MPP, UMA/NUMA/COMA
• Interconnect– PCI(E)/Infiniband/NUMALink
• Storage– RAID, Multipathing, Data Bus– DAS/NAS/SAN– Parallel File Systems
• Evolution of Computing– Mainframe, Cluster, Grid, Cloud, Big Data
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What is HPC?
• High Performance Computing– most generally refers to the practice of aggregating
computing power in a way that delivers much higher performance than one could get out of a typical desktop computer or workstation in order to solve large problems in science, engineering, or business.
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Capability vs. Capacity
• Capability computing is typically thought of as using the maximum computing power to solve a single large problem in the shortest time. – e.g. A real-time weather simulation and prediction application.
• Capacity computing in contrast is typically thought of as using multiple cost-effective computing power to solve a big number of small problems or a small number of big problems. – e.g. Tons of user access to a web service simultaneously or, – To analyze huge amount HEP data: split it into many small
pieces and distribute them across multiple cluster nodes.
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Spectrum
• Capability → Capacity
Hungabee• Single system • 2048 cores• 16TB• Hi-speed interconnet
Breezy• 16 fat node cluster• 256GB/node
Bugaboo• 256+ node cluster• 16-24GB/node
BlueGene/Q• 4096 low power nodes• 65536 processor cores
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Architectures
• By processor– SMP (Symmetric Multi-Processors )– DSM (Distributed Shared Memory)– MPP (Massive Parallel Processors)
• By memory– UMA (Uniform Memory Access)– NUMA (Non-Uniform Memory Access)– COMA (Cache Only Memory Access)
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Evolution of Architectures
Message Passing UMA
COMANUMA
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Programming Model
• Serial– Instructions are executed one after another on
a single CPU.• Parallel
– Computations are carried out concurrently on multiple processors.
• SPMD: single program multiple data • MPMD: multiple programs multiple data
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Parallel Programming Paradigms/Tools
– Data Parallel• HPF (High Performance Fortran)
– Task Parallel• OpenMP (Open Multi-Processing)
– Message Passing• PVM (Parallel Virtual Machine)• MPI (Message Passing Interface)
– MPICH, Open MPI, etc.
– Hybrid (MPI+OpenMP, MPI+GPGPU)– Advanced: Chapel, PGAS(Partitioned Global Address
Space)
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Interconnect
• PCI• PCI Express• Infiniband
• HyperTransport (AMD)• QPI/Omni-path (Intel)• NUMAlink (SGI)
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Serial vs. Parallel
• In early days, serial connections were reliable but quite slow, so parallel connections was developed to send multiple pieces of data simultaneously.
• While later it turned out that parallel connections have their own problems – electromagnetical interference between wires.
• So the pendulum swung back to highly-optimized serial connections.
Serial → Parallel → Serial
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PCI/PCI-X
• PCI: Peripheral Component Interconnect (32bit)• PCI-X: PCI-eXtended (64bit)
Image source: http://www.altera.com/products/ip/altera/t-alt-pci_soln.html
Electromagnetic interference and signal degradation are common in parallel connections, which slows the connection down. The additional bandwidth of the PCI-X bus means it can carry more data but generates even more noise.
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PCI-Express
A single PCI Express lane, can handle 200 MB/s. A 16X PCI-E connector can reach 6.4 GB/s.
• Instead of using the parallel connections, PCI-E has a switch controlled point-to-point serial connections.
• Every device has its own dedicated connection, so devices no longer share bandwidth like they do on a normal data bus.
Image source: http://computer.howstuffworks.com/pci-express2.htm
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Infiniband
Image source: http://wiki.expertiza.ncsu.edu/index.php/CSC/ECE_506_Fall_2007/wiki4_001_a1
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Infiniband• The internal connections in most computers are inflexible and
relatively slow. • As I/O increases, the existing bus system becomes a bottleneck.• While through InfiniBand switches, Infiniband channels are created
to connect hosts (HCAs) and I/O targets (TCAs) • Instead of sending data in parallel across the backplane bus,
Infiniband specifies a serial bus– The serial bus can also carry multiple channels of data at the same time
in a multiplexing signal.
Infiniband theoretical throughput in Gb/s
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Infiniband vs. PCI/PCI-Express
http://www.mellanox.com/pdf/whitepapers/PCI_3GIO_IB_WP_120.pdf
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Storage• Storage Protocol• I/O BUS
– Serial vs. Parallel• Redundancy
– RAID (Redundant Array of Inexpensive Disks)– Multipathing (Redundant physical paths )
• Storage Attaching Approaches– DAS (Direct Attached Storage)– NAS (Network Attached Storage)– SAN (Storage Area Network)
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Storage Protocol• CIFS/SMB (Common Internet File System)
– application-layer network protocol mainly used to provide shared access to files, printers, etc. between nodes
• NFS (Network File System) – application-layer network protocol only allows access to files over an
Ethernet network.
• SCSI/iSCSI (Internet Small Computer System Interface)– iSCSI is a mapping of regular SCSI protocol over TCP/IP
• FC (Fibre Channel)– transport protocol which mainly transports SCSI commands over
Fibre Channel networks• FCoE (Fibre Channel over Ethernet)
– This allows Fibre Channel to use 10 Gigabit Ethernet networks (or higher speeds) while preserving the Fibre Channel protocol.
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I/O Bus
• ATA → SATA– ATA (Advanced Technology Attachment)– SATA (Serial ATA)
• SCSI → SAS– SCSI (Small Computer System Interface)– SAS (Serially Attached SCSI)
Parallel → Serial
synchronizationelectromagnetic interference
cost
http://www.denali.com/wordpress/index.php/dmr/2010/02/02/ssd-interfaces-and-performance-effects
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RAIDRedundant Array of Independent Disks
• RAID 0: Striping, without parity or mirroring. • RAID 1: Mirroring, without parity or striping.• RAID 2: Bit-level striping with dedicated parity.• RAID 3: Byte-level striping with dedicated parity.• RAID 4: Block-level striping with dedicated parity.• RAID 5: Striping with single distributed parity. • RAID 6: Block-level striping with double distributed
parity.• Nested RAID: RAID 10, RAID 50, RAID 60, etc.
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Example: RAID 0, 1, 5
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Example: Nested RAID 10, 50
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Comparison
http://www.techwarelabs.com/10-things-to-consider-before-setting-up-raid/
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Multipathing
• Multipath I/O – Is a fault-tolerance and performance
enhancement technique. – To create multiple logical paths between the
server and the storage devices.• via adapters, cables, and switches, etc.
– In the event that one path fails, multipathing uses an alternate path so that applications can still continuingly access their data.
https://access.redhat.com/site/documentation/en-US/Red_Hat_Enterprise_Linux/6/html-single/DM_Multipath/
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DAS/NAS/SAN
http://abdullrhmanfarram.wordpress.com/2013/04/08/storage-technologies-das-nas-and-san/
• Storage directly attached• High cost of management• Inflexible• Expensive to scale
• Storage access through Ethernet
• Scalable and flexible
• Storage access through FC/IB• Much better performance• More flexible and scalable• Increases data availability
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Parallel File System
• Distribute data into multiple storage nodes and access via high-speed network.
• Concurrent (often coordinated) access from many clients
• Provide global shared meta data (locations, file names, sizes, etc)
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Parallel File Systems
• Lustre• GPFS• Panasas• NFSv4??
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Parallel File Systems
• Lustre• GlusterFS• OrangeFS• GPFS• IBRIX• CXFS• Panasys• PVFS2• PNFS (NFSv4.1)• GoogleFS• Ceph
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Example: Lustre
Image source: http://wiki.lustre.org/manual/LustreManual18_HTML/figures/LustreArch.png
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Object storage• Object storage appears as a collection of objects.• An object typically includes not only data itself, but some extra
information such as meta data, OID, attributes, etc.• It moves lower-level functionalities such as space management,
security functions into the storage device itself, accessing the device through a standard object interface.
• Especially good for storing unstructured data such as photos, songs, etc.
Block Storage Object Storage
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Comparison of 3 storage types
NFS and SMB/CIFS Fibre Channel/iSCSI AWS S3https://insights.ubuntu.com/2015/05/18/what-are-the-different-types-of-storage-block-object-and-file/
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Comparison of 3 storage types
http://blog.sungardas.com/CTOLabs/2015/10/object-storage-the-alternator-of-cloud-computing/
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Evolution of Computing
• Mainframe: super power • Cluster: worker bees• Grid: global orchestration• Cloud: everything as a service • Big Data: find needle in the sea
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Evolution of Computing
Multiple sites (geographically distributed)Global SchedulingVirtualized OrganizationTransparent data accessUnified security infrastructure
Virtualized resourcesElastic computingBuild everything as a service!
Multiple nodesBatch job schedulingParallel computing
Single machineShared memory
Big volumeBig variety Big velocityFast analysis/decision
Mainframe
PC/Cluster
Grid
Cloud
Big Data
Image and test source: http://www.wikipedia.org/
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Mainframe
• Originally referred to large cabinets that housed powerful CPU and shared memory.
• Modern design:– Redundant internal engineering
resulting in high reliability and security
– Extensive I/O facilities – High utilization rates – Uses virtualization technology
to support massive throughput
Amdahl 470V/6
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Cluster
• Tightly connected computers that work together as a single system– Low cost– scalability– Flexibility
• Batch job scheduling/management• Parallel computing
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Grid
• Grid computing is the coordination on massive computer resources from multiple locations, to reach a common goal. The resources are:– loosely coupled – heterogeneous – Geographically dispersed– Dynamic
• Main features:– High level scheduling/Workload management– Unified security infrastructure – Global information system– Virtualized organization – Transparent data transfer interface
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Example: WLCG (Worldwide LHC Computing Grid)
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Cloud• Initially
– IAAS (Infrastructure as a Service)– PAAS (Platform as a Service)– SAAS (Software as a Service)
• Subsequently– HAAS (Hardware as a Service)– NAAS (Network as a Service)– DAAS (Database as a Service)– CAAS (Communication as a Service)– BPAAS (Business Process as a Service)
• Eventually– XAAS (Everything as a service!)
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Image source: www.telezent.com
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X
Image source: http://blueatoll.com/blog/the-next-generation-enterprise-business-as-a-service-in-the-cloud/
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Big Data
• What is Big Data– refers to technologies of handling data that is
too diverse, fast-changing or massive for conventional technologies to address efficiently.
– Today new technologies make it possible to realize value from Big Data.
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Big Data’s Four V’s
http://www.ibmbigdatahub.com/blog/how-big-data-and-cognitive-computing-are-transforming-insurance-part-2
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Big Data: Core Technology
• Foundation stone– Google (GFS, MapReduce, Big Table)
• Free version– Apache (HDFS, YARN, Hbase, Hive, Pig…)
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Big Data: MapReduce
Image source: http://www.slideshare.net/tothc/introduction-to-hadoop-and-map-reduce
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Big Data: Evolution
• New Troika– Google (Dremel, Pregel, Caffeine)
• Free version– Apache Drill, Apache Giraph, Stanford GPS
Image source: http://blog.mikiobraun.de/2013/02/big-data-beyond-map-reduce-googles-papers.html
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Example: MapReduce vs. Dremel
Query: SELECT SUM(CountWords(txtField)) / COUNT(*) FROM T1 (T1: 85 billion records, 87 TB, 3000 nodes)
Image source: http://www.cubrid.org/blog/dev-platform/meet-impala-open-source-real-time-sql-querying-on-hadoop/
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Big Data Ecosystem
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Summary
• Introduced Compute Canada and its consortia • Introduced WestGrid and the member sites• Introduced high performance computing from different
angles such as architecture, memory, interconnect, storage, file system, etc.
• Also briefed evolution of computing technologies from mainframe, cluster, grid, cloud, to the current hot topic —— Big Data.
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Follow-up Talks
• Sept.15, 2016 Tips for Submitting jobs & Moving Data (with Hands-on session)– Masao Fujinaga
• Sept. 27, 2016 Scheduling & Job Management (with Hands-on session)– Kamil Marcinkowski
See more details in: https://www.westgrid.ca/events
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Thanks!Questions?