isc cloud 2013 - cloud architectures for hpc – industry case studies

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Private Cloud Architectures for HPC Industry Case Studies ISC Cloud 2013 Heidelberg, September 23rd, 2013 Ignacio M. Llorente Project Director © OpenNebula Project. Creative Commons Attribution-NonCommercial-ShareAlike License

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Page 1: ISC Cloud 2013 - Cloud Architectures for HPC – Industry Case Studies

Private Cloud Architectures for HPC Industry Case Studies

ISC Cloud 2013 Heidelberg, September 23rd, 2013

Ignacio M. Llorente Project Director

© OpenNebula Project. Creative Commons Attribution-NonCommercial-ShareAlike License

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Contents Private Cloud Architectures for HPC!

This presentation is about: •  The Private HPC Cloud Use Case

•  Main Challenges for Private HPC Cloud

•  Private HPC Cloud Case Studies •  Private Cloud Trends in Industry

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The Private HPC Cloud Use Case The Pre-cloud Era!

LRMS (LSF, PBS, SGE…)

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The Private HPC Cloud Use Case OpenNebula as an Infrastructure Tool – Enhanced Capabilities!

Virtual Worker Nodes

LRMS (LSF, PBS, SGE…)

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•  Common interfaces

•  Custom environments •  Dynamic elasticity

•  Consolidation of WNs •  Simplified management •  Physical – Virtual WNs •  Dynamic capacity partitioning •  Faster upgrades

Service/Provisioning Decoupling!

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The Private HPC Cloud Use Case OpenNebula as an Provisioning Tool – Enhanced Capabilities!

Pilot Jobs, SSH…

IaaS Interface Acc

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•  Simple Provisioning Interface •  Raw/Appliance VMs

•  Dynamic scalable computing •  Custom access to capacity •  Not only batch workloads •  Not only scientific workloads

•  Improve utilization •  Reduced service management •  Cost efficiency

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Main Challenges for Private HPC Cloud Main Demands from Engineering and Supercomputing !

Flexible Definition of Multi-tier Applications

Resource Management

Scale-out and Provisioning

Application Performance

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Main Challenges for Private HPC Cloud Using the Cloud – Execution of Multi-tiered Applications !Management of interconnected multi-VM applications: •  Definition of application flows •  Catalog with pre-defined applications •  Sharing between users and groups •  Management of persistent scientific data •  Automatic elasticity

Front-end

Worker Nodes

{ "name": ”Computing_Cluster", "deployment": "straight", "roles": [ { "name": "frontend", "vm_template": 0 }, { "name": "worker", "parents": frontend, "cardinality": 2, "vm_template": 3, "min_vms" : 1, "max_vms" : 5, "elasticity_policies" : { ”expressions" : ”CPU> 90%”, "type" : "CHANGE", "adjust" : 2, "period_number" : 3, "period" : 10 }, …

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Main Challenges for Private HPC Cloud Using the Cloud – Performance Penalty as a Small Tax You Have to Pay!

Overhead in Virtualization •  Single processor performance penalty between 1% and 5% •  NASA has reported an overhead between 9% and 25% (HPCC and NPB)1

•  Growing number of users demanding containers (OpenVZ and LXC)

Need for Low-Latency High-Bandwidth Interconnection •  Lower performance, 10 GigE typically, used in clouds has a significant

negative (x2-x10, especially latency) impact on HPC applications1 •  FermiCloud has reported MPI performance (HPL benchmark) on VMs and

SR-IOV/Infiniband with only a 4% overhead2

•  The Center for HPC at CSR has contributed the KVM SR-IOV Drivers for Infiniband3

(1)  An Application-Based Performance Evaluation of Cloud Computing, NASA Ames, 2013 (2)  FermiCloud Update, Keith Chadwick!, Fermilab, HePIX Spring Workshop 2013 (3)  http://wiki.chpc.ac.za/acelab:opennebula_sr-iov_vmm_driver , 2013

Overhead in Input/Output •  Growing number of Big Data apps •  Support for multiple datastores including automatic scheduling

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Main Challenges for Private HPC Cloud Operating the Cloud – Resource Management!

Optimal Placement of Virtual Machines •  Automatic placement of VM near input data •  Striping policy to maximize the resources available to VMs

Fair Share of Resources •  Resource quota management to allocate, track and limit resource utilization

Management of Different Hardware Profiles •  Resource pools (physical clusters) with specific Hw and Sw profiles, or

security levels for different workload profiles (HPC and HTC)

Isolated Execution of Applications •  Full Isolation of performance-sensitive applications

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Main Challenges for Private HPC Cloud Operating the Cloud – Scale out and Provisioning!

Multi-tier Deployment •  Management of multiple cloud instances

that may be hosted in different sites

Provide VOs with Isolated Cloud Environ •  Automatic provision of Virtual Data Centers

Hybrid Cloud Computing •  Cloudbursting to address peak or fluctuating

demands for no critical and HTC workloads

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Private HPC Cloud Case Studies One of Our Main User Communities!

Supercomputing Centers

Research Centers

Distributed Computing Infrastructures

Industry

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Private HPC Cloud Case Studies FermiCloud!

Nodes KVM on 23 nodes (1 TB RAM - 368 cores) Koi Computer

Network Gigabit and Infiniband

Storage CLVM+GFS2 on shared 120TB NexSAN SataBeats

AuthN X509

Linux Scientific Linux

Interface Sunstone Self-service and EC2 API

App Profile Legacy, HTC and MPI HPC

http://www-fermicloud.fnal.gov/

Typical Workloads •  Scientific stakeholders get access to on-

demand VMs •  Developers & integrators of new Grid

applications

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Private HPC Cloud Case Studies CESGA Cloud!

Nodes KVM on 27 nodes (0.5 TB RAM – 216 cores) HP ProLiant

Network 2 x Gigabit (1G and 10G)

Storage ssh from remote EMC storage server

AuthN X509 and core password

Linux Scientific Linux

Interface Sunstone Self-service and OCCI

App Profile Individual VMs and virtualised computing clusters

Typical Workloads •  103 users •  Genomic, rendering… •  Grid services on production at CESGA •  Node at FedCloud project •  UMD middleware testing

http://cloud.cesga.es/

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Private HPC Cloud Case Studies SARA Cloud!

Nodes KVM on 19 HPC nodes (256 GB RAM 608 cores) Dell PowerEdge and 10 “light” nodes (64 GB RAM 80 cores) Supermicro

Network 4 x Gigabit (10G) with Arista switch

Storage NFS on 400 GB NAS for HPC and ssh for “light”

AuthN Core password

Linux CentOS

Interface Sunstone and OCCI

App Profile MPI clusters, windows clusters and independent VMs

ww.cloud.sara.nl

Typical Workloads •  Ad-hoc clusters with MPI and pilot jobs •  Windows clusters for Windows-bound

software •  Single VMs, sometimes acting as web

servers to disseminate results

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Private HPC Cloud Case Studies SZTAKI Cloud!

Nodes KVM on 7 nodes (1.8 TB RAM – 448 cores) DELL PowerEdge

Network 2 x Gigabit (1G and 10G)

Storage iSCSI on DELL storage server 72 TB shared

AuthN X509

Linux CentOS

Interface Sunstone Self-service, EC2 and OCCI

App Profile Individual VMs and virtualised computing cluster

http://cloud.sztaki.hu/

.

Typical Workloads •  Run standard and grid services (e.g.:web

servers, grid middlewares…) •  Development and testing of new codes •  Research on performance and

opportunistic computing

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Private HPC Cloud Case Studies KTh Cloud!

Nodes KVM on 768 cores (768 GB RAM) HP ProLiant

Network Infiniband and Gigabit

Storage NFS and LVM

AuthN X509 and core password

Linux Ubuntu

Interface Sunstone self-service, OCCI and EC2

App Profile Individual VMs and virtualised computing cluster

http://www.pdc.kth.se/

Typical Workloads •  Mainly BIO •  Hadoop, Spark, Galaxy, Cloud Bio Linux…

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Private Cloud Trends in Industry Experimenting with ARM for the Private Cloud!Why? •  Decrease power consumption, reduce costs, simplify solutions… •  Mostly managing bare metal and early experiences with virtualization

Tiniest Cloud Ever! (by Citrix and Linaro at LCU 2013)

Ubuntu on Versatile Express Cortex-A15 Dual core

Ubuntu on Arndale Board Cortex-A15 Dual core

http://www.youtube.com/watch?v=xZP9YKv3P_E

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Private Cloud Trends in Industry Cloud for Mission-critical Applications!Availability and redundancy to keep it running in case of failure •  Cloud services availability => HA Architectures •  Application availability => Failover Solutions

Service Continuity (by European Aeronautic Company)

OpenNebula 4.0

Automatic failover and recovery within 1 minute

KVM

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Private Cloud Trends in Industry Hybrid Cloud Deployments !Transparent and automatic access to the public cloud •  Dev&testing to the public cloud •  Security and performance sensitive workloads on the private cloud

Cloudbursting Deployment (by Telecom Company)

Public  Cloud  1  

Public  Cloud  2  

Local data center

OpenNebula  

Private Cloud

Cloud API is not relevant

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Try it Out! OpenNebula Sandboxes!

● OpenNebula pre-installed in a VM: VirtualBox, KVM, VMware, Amazon

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Join Us at OpenNebulaConf 2013!

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Thanks to People and Organizations that Provided Info to Prepare this Presentation!Questions?

OpenNebula.org @OpenNebula