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Grids in EDA Software Development

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EDA is the slowest industry to adopt massive parallel processing grids. ... EDA is one of these. ... The EDA industry deploys this kind of grid, but in a UNIX ... – PowerPoint PPT presentation

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Title: Grids in EDA Software Development


1
Grids in EDA Software Development
gridMatrix Technology
Tom Grotton Cadence Design Systems,
Inc. Director, IT Server Farm Initiative
2
Corporate Needs
  • Need more computing capacity
  • Products are becoming more complex and taking
    additional cycles to build and test.
  • Products need to be supported on multiple
    platforms (OS and version)
  • Process and machine utilization measurements are
    inadequate to effectively plan and manage capital
    equipment requirements. We continue to add more
    and more servers to meet this unplanned demand.
  • Need a more reliable hardware, storage and
    network
  • Nightly runs of product builds and tests fail too
    often due to machine or infrastructure problems
  • To decrease the dependency on individual hardware
    resources
  • Need more cost-effective IT contribution
  • System administration costs are ever increasing
    as more and more hardware is added. According to
    Gartner and based on our experience, TCO costs
    are being primarily driven by support costs and
    not capital. For every 20 cents spent on
    equipment, 80 cents is spent supporting it.

3
How We Address these Needs
  • Manage Cost (Total Cost of Ownership)
  • Agility (Adaptive IT infrastructure)
  • Increase Quality (Product and Service)
  • Virtualization (Computing, Networking, Storage,
    Security, File systems, Monitoring, and Common
    Process Architecture)
  • Federation (Brokering, Provisioning, Resource
    Sharing, Globalization)
  • Automation (Process, Workflow and Ease-of-use)

4
Capitalizing On Our Expertise
  • The key point of coordination, information
    exchange and collaboration for those involved in
    large-scale grid projects in the US, Europe,
    Canada and Asia-Pacific is the Global Grid Forum
    (GGF). GGFs platinum and silver sponsors are
    Compaq, HP, IBM, Sun, Microsoft, Platform
    Computing, AVAKI and Entropia.
  • As a member of the GGF, Cadence chairs and leads
    the
  • GGF Common Use Case Model Architecture Working
    Group, formerly known as NPi
  • This Working Group is responsible for defining a
    particular lightweight, high-level architecture
    for distributed computing management. Creating an
    overall Reference Model for advanced distributed
    computing management
  • GGF Job Submission Description Language working
    group
  • This Working Group is to define a standard Job
    Submission Description Language (JSDL) for
    describing a computational 'job' and its required
    execution environment for submission to a Grid.
    This language would be used to construct a
    document that would encapsulate all of the
    information needed by a Distributed Resource
    Management (DRM) system or a job submission
    system on a Grid, such as a Grid scheduler, to
    place a job in its required environment for
    execution.
  • GGF Grid Policy Architecture working group
  • This Working Group is developing the requirements
    and architecture for interoperable policy
    management, and for how they are described,
    evaluated, stored, managed, distributed, and
    enforced. Since policies may also be associated
    with instrumentation to provide feedback into
    evaluating the effectiveness of the policies, the
    requirements and architecture will also provide a
    framework for associating the appropriate metrics
    and instrumentation with the policies.
  • Is a seated member of the GGF DRMAA (Distributed
    Resource Management Application Architecture)
    working group.
  • Reference The 451 Group Grids 2004

5
Grids
  • Definition Grid computing refers to a network
    architecture designed for large-scale dynamic
    sharing computing resources. A grid works by
    taking the responsibility for input/output
    requests for storage, memory, processing, and/or
    communications resources away from individual
    machines and instead moves that responsibility to
    a network grid that searches for available
    resources to handle resource requests.
  • Usage A growing number of companies are
    considering deploying Grid Technology or have
    deployed it. These companies are finding the
    Total-Cost-of-Ownership to deployment, management
    and support Grid Technology to be overly costly.
  • EDA is the slowest industry to adopt massive
    parallel processing grids.
  • Partly because of the industry itself and partly
    because of the nature of the products.
  • Industries that are using Grid Technology are
    Life Science, Engineering, Commerce, Financial,
    Electronic Design Automation, Digital content
    creation, Testing, Server/Storage, Batch
    processing, Decision support/data mining.

6
Grid Industry
  • 2005 grid Hardware and Software solutions 18
    billion
  • 2005 grid Software solutions 4 billion
  • There are several middleware DRM (Distributed
    Resource Management) companies Platform, Sun,
    IBM, etc.
  • There is an increase in next-generation DRM
    products that are no-cost.
  • There are also products that have their DRM
    layer, GridIron, DataSynapse.
  • Enter Utility Computing - With the emergence of
    this universal computing grid, there will be a
    need for a new breed of utility provider.
    Although companies and individuals will retain
    some local computing capabilities, there will be
    a growing opportunity for trusted neutral parties
    to operate and manage shared resources within the
    grid. (ASPnews 9/02)
  • Projected growth of the software grid technology
    market is 25 until 2007, then it jumps up
    considerably due to the larger number of
    industries that will start to use grid
    technology. EDA is one of these.

Data sources http//www.gridpartners.com,
http//www.idc.com, http//www.econstrat.org/,
http//gridcomputingplanet.com,
http//www.bloor-research.com/,
http//www.gridforum.org/
7
Grid Technology Evolution
  • Compute Grids share excess PC compute cycles to
    provide a high-performance, low-cost computing
    environment. Their application is scientific
    research and engineering.
  • Example, SETI_at_Home.
  • Market leaders are Entropia, Sun, Platform, and
    United Devices.
  • The EDA industry deploys this kind of grid, but
    in a UNIX environment and not across the
    internet.
  • Information Grids are distributed architecture
    designed for large-scale dynamic sharing of
    commercial and technical applications, data, and
    compute power within the enterprise or across
    multiple external organizations. They are used
    in specialize industries, such as,
    pharmaceutical, biotech, medical, financial
    services, oil and gas exploration.
  • Example, IBM/Upenn Mammography research project.
  • Market leaders are AVAKI, Platform, IBM, Sun, and
    HP.

Data source The Grid Report, Bloor Research,
November 2002
8
Grid Technology Evolution
  • Service Grids make use of the intersection of
    grid and web services technology concepts. As
    such, the service grid provides the underlying
    architecture for Utility Computing model. Sun
    describes a Service Grid as collections of
    services brought together from across the
    network. Service Grid are composed of services
    that you need at a particular time mail, stock
    feeds, word-processing, or flight information,
    etc. The idea of the service grid is that each
    piece comes from a source that specializes in an
    external function.
  • Examples, Sun ONE and HPs Utility Data Center
    OGSA.
  • Market leaders are HP, IBM and Sun.
  • Intelligent Grids are self-managing utility
    architectures that go beyond the bounds of
    department and enterprise massive extended
    enterprises encompassing partners, suppliers,
    and customers. Currently, intelligent grids use
    homogeneous resources.
  • Examples of intelligent grids are IBMs eLiza
    IBM Workload Manager, HPs Planetary Computing
    project, and Suns Management Center, N1.
  • Market leaders are IBM, Sun, and HP.

Data source The Grid Report, Bloor Research,
November 2002
9
Grid Technology What to do?
  • Utility Grids are to some extent conceptual to
    the grid industry. They use the power utility
    model, where there are main generation grids and
    peak request or overflow local grids. Utility
    grids takes the position that computing resources
    and the DRM layer are commodities, because these
    resources can be provisioned on demand. Utility
    grids are capable of managing higher-level
    functions, such as, security, data access and
    transformation in a massively parallel
    environment across the enterprise.
  • According to several industry sources, Compute,
    Information, and Service grids will likely
    converge into Intelligent grids in the future.
    The fifth grid type Utility Grids or Corporate
    Utility Computing Grids are evolving and will
    likely replace the Service Grid and Intelligent
    Grid in time. This grid is designed to make
    heterogeneous computing power and heterogeneous
    resources available on-demand.

10
What does the future look like? Utility Grids
11
Cadence Grid
  • Inside Cadence we are deploying Grid Technology
    today! So far, it has resulted in an average of
    67 reduction in process job run-time for RD and
    Services business units worldwide.
  • We have around 3000 CPUs in our grid. Next year
    we are looking at doubling this!
  • RD and Services business units require IT
    provide grid control, monitoring, statusing,
    error/alert reporting, performance reporting and
    job optimizing for massively parallel processes
    across hundreds and thousands of heterogeneous
    computer resources, ranging from Microsoft
    Windows, Linux and UNIX (AIX, HP-UX, Solaris).
  • Cadence has developed and deployed patented grid
    technology.
  • As most of you have done or are trying to do, we
    have developed an abstraction layer that performs
    Grid Automated Process Control allowing a
    Developer, CM, PV, Flow, Support engineer to
    interface with complex job definitions in a
    natural manner. Today, LSF is the Distributed
    Resource Management (DRM) layer and networked to
    this are Data Grids, which make computer
    resources, networking and storage virtually
    invisible.
  • Results - Significant reduction of
    Total-Cost-of-Ownership by reducing cost of
    adoption and deployment, job run-time, costs in
    support, capital equipment, personnel and the
    technical knowledge.

12
Yesterdays Process
Harness Scripts (fire up DRM - bsub)
Logs Email Reporting (Some Web Reporting)
Run Job or Tool
Hardware (Servers/Workstations)
13
Todays Process
This is the only interface that is seen!
Engineer submits a grid-enabled job
Intelligent Job Controlincluding web-based
monitoring and job control
DRM
Hardware (Servers/Workstations)
Resource Monitoring Alert Handling(DRM, system
and system configuration)
14
What is Needed
Standard means to grid-enable EDA Toolby thread
Engineer submits a grid-enabled job
Intelligent Job Controlincluding web-based
monitoring and job control
DRM
Hardware (Servers/Workstations)
Resource Monitoring Alert Handling(DRM, system
and system configuration)
15
Where are we?
Intelligent Grid Technology
Dependency Management
Site Grid Health
Site
Workspace Management
Heterogeneous Resources
Heterogeneous Process
Natural Language
Compute Grid Health(Commission Platform)
Local
Job Definition(Process Control)
Process
Multi-Site/Cluster
Job Control
Job Priorities
Job Execution
Platform Definition
Utility Grid
Workspace Management(RCS, ClearCase, CVS, VNC,
Extendable)
Alert Handling(GRS)
Dynamic Web Reporting(Customizable)
Self-Healing
Process Metrics
Job Statistics
Metrics
Job Monitoring
Queue Definition Optimization
Host Groups and Host Partitions
Workspaces
Pool Configuration
DRM Grid
Job Distribution
Res. Control
Commission and Monitoring
16
Site Grid Status
17
Horizons
Cycle-times reduced 67
Examples - 4 Hrs to 17 Mins - 13 Hrs to 2 Hrs -
6 Hrs to 30 Mins- 24 Hrs to 3.5 Hrs
  • Corporate Grid (2005)
  • Multiple site grids sharing resources and data
    intelligently across the WAN.
  • gt50 utilization

Site Grid (2003) Combines compute farms to
facilitate the sharing of capital resources
across multiple departments, projects, and
groups Increase server utilization from gt30
Compute Farms (2002) Enables shared system usage
across departmentsIncrease Utilization from gt11
18
QA
19
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