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HPC Cloud: Hype or Reality?. Terry Fisher Global Sales Leader - HPC Cloud IBM Platform Computing. CHPC Conference – December 2013.

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HPC Cloud: Hype or Reality?


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slide1

HPC Cloud: Hype or Reality?

Terry Fisher

Global Sales Leader - HPC Cloud

IBM Platform Computing

CHPC Conference – December 2013

slide2

Based on HPC cloud’s potential impact, many organizations are evolving their infrastructures to enable private cloud deployments, exploring hybrid clouds, and considering public clouds

Private

Clouds

Hybrid

Clouds

Public

Clouds

Evolve existing infrastructure to

HPC cloud to enhance responsiveness, flexibility, and

cost effectiveness.

Enable integrated approach to improve HPC cost and capability

Access additional HPC capacity with variable cost model

60%

Considering

Implementing

Exploring

slide3
HPC clouds may need to address advanced requirements that extend beyond core HPC workload management on a cluster or grid

If you have ever wondered:

  • Can I share infrastructure between multiple clusters (simulation, design, analytics, Big Data) in one integrated environment?
  • Can I move resources (compute nodes) from one cluster to another when the clusters are already deployed?
  • Can I selectively run specific HPC jobs in dynamically created VMs?
  • Can I re-provision my infrastructure based on my workload requirements?
  • Can I extent my HPC environment by bursting to a public cloud for peak loads?
  • Can I support a new business model and deliver an analytics or HPC service in a multi-tenant environment?

With IBM Platform Computing solutions, the answer to all of these questions is “YES”!

what requirements does a hpc cloud fulfill
What requirements does a HPC cloud fulfill?
  • Provides additional compute resources to meet peak demand (bursting)
  • Dynamically resizes HPC cluster based on demand (flexing)
  • Allows technical end users to run HPC jobs on-demand
  • Enables multiple groups to share an HPC environment managed by business policies with chargeback and reporting
  • Dynamically changes HPC cluster configurations (e.g. OS personality) based on workload requirements
  • Enables end users to self-service create custom HPC clusters on-demand

Fulfilling NIST Cloud Characteristics of enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction

Note: HPC cloud does not necessarily imply a public cloud deployment model or VMs

hpc cloud computer aided engineering cae customer example
HPC Cloud - Computer Aided Engineering (CAE) Customer Example

Customer Background:

  • A developer and distributor of Computer Aided Engineering software with a focus on

computation fluid dynamics

  • Primary I/T environment run on IBM servers with GPFS in an IBM ITS data center
  • Preparing to offer a new SaaS option

Customer Goals Addressed:

  • Enhancing “foundational” I/T capacity (e.g. servers, storage) for internal and external use with high-capacity
  • Establishing portal capability for self-service
  • Enabling multi-tenancy with remote visualization
  • Future extension to external “variable” I/T capacity for an integrated ability to support peak loads
hpc cloud higher education customer example
HPC Cloud – Higher Education Customer Example

Customer Background:

  • Resources for technical calculations are distributed in various

university institutes

  • Distributed workstations and compute servers are unevenly utilized
  • Faculty and researchers are unable to effectively perform both calculation intensive workloads (e.g. Ansys) and interactive work (e.g. Matlab) on their existing systems
  • Current I/T systems are heterogeneous
  • Which software is on which machines is not catalogued

Customer Goals Addressed:

  • An automated system providing technical computing resources to authorized users quickly and with little effort.
  • User self-service available through a GUI portal
  • Dynamic provisioning of physical and virtual machines
  • Supporting complex simulations and data intensive analysis
  • Automated instantiation of needed software
  • Ability to extend in future to access external resources

7

hpc cloud petroleum customer use case example
HPC Cloud – Petroleum Customer Use Case Example

Customer Background:

  • Seismic processing required to make multimillion dollar decisions on where to drill or how to best exploit oil fields
  • Seismic processing requirements for large amounts of processing power
  • Need for extensive data cleansing to filter out the noise measured along with the signals received by detectors
  • The ability to handle and store large volumes of data

Customer Goals Addressed:

  • On demand access to a cloud infrastructure to process very large amounts of seismic data quickly
  • Access to advanced HPC bare metal servers with the latest advanced high-core count Intel CPUs
  • Leverage of GPU nodes to accelerate workload processing up to 10X
  • Scalability up from a base of 120 nodes and back down again as needed all within a single location to avoid network bottlenecks
hpc saas client use cases
HPC SaaS Client Use Cases
  • Cloud Burst target for existing clients
    • The IBM Platform HPC SaaS offering will provide a cloud based burst target for existing Platform LSF and Symphony clients to extend or grow their on-premise clusters
    • When additional HPC capacity is needed, on-premise cluster resources will connect to a cluster running in the cloud
    • Additional capacity is desired when the on-premise cluster is temporarily overloaded with too many pending jobs, special projects are scheduled that will exceed the current capacity, and when access to special hardware not available on the on-premise cluster is needed (e.g., GPU, large memory, etc)
administrator and calendar driven bursting to hpc cloud
Administrator and Calendar Driven Bursting to HPC Cloud

Admin

User A

User B

User C

User N

On-premise LSF or Symphony cluster

Portal to launch

Cluster on Demand

Administrator and

Calendar Driven

Burst

Requests

LSF or

Symphony

MultiCluster

Temporary Platform LSF or Platform Symphony Cluster

SoftLayer Cloud

Bare-Metal, Private, Public

SoftLayer Cloud

Bare-Metal, Private, Public

Note: Planned availability 1Q14

IBM Confidential

policy driven bursting to hpc cloud
Policy Driven Bursting to HPC Cloud

User A

User B

User C

User N

On-premise LSF or Symphony cluster

Bursting

Policy

Grid Load

Information

LSF or

Symphony

MultiCluster

RESTful APICommunication

Temporary Platform LSF or Platform Symphony Cluster

SoftLayer Cloud

Bare-Metal, Private, Public

Note: Planned availability 2Q14

IBM Confidential

platform computing saas client use cases
Platform Computing SaaS Client Use Cases
  • IBM Platform SaaS Offering
    • Fully functioning and ready to use Platform LSF and Platform Symphony clusters that will be installed and operated in the Cloud (i.e. SoftLayer data centers)
    • Cloud bare metal machine instances, the operating systems, and the cluster software - Platform LSF or Platform Symphony.
    • Use as needed and pay for only the time they use the cluster, instead of purchasing perpetual licenses
    • Rent the cluster on a pay per use basis as an OPEX and not need to make a CAPEX investment in hardware and software
  • Hosted HPC for new clients
    • Provides an HPC (Platform LSF or Platform Symphony) cluster to new clients who do not have an on-premise HPC cluster, or the skills and budget to build one
    • When access to a HPC cluster is required, access a cluster running in the cloud to process workload
    • Provide an Analytics cluster (Platform Symphony, BigInsights) for new clients who need to perform Hadoop/MapReduce work
thank you

Thank-You!

Visit us at:

ibm.com/technicalcomputing

ibm.com/platformcomputing