Workflow, Planning and Performance Information, information, information Dr Andrew Stephen M c Gough

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1 Workflow, Planning and Performance Information, information, information Dr Andrew Stephen M c Gough Technical Coordinator London e-science Centre Imperial College London 17 th March 2006

2 Outline Where does this work come from? Types of workflow Workflow Pipeline The Planner Information, Information, Information Using Information Component Deployment Conclusion 2

3 Where does this work come from? Performance Workflow Execution JSDL-WG OGSA-WG 3

4 ICENI: Imperial College e-science Network Infrastructure Integrated end2end Grid Middleware Solution Interoperability between architectures, APIs Added value layer to other middleware Usability: Interactive Grid Workflows Role and policy driven security Foundation for higher-level Services and Autonomous Composition ICENI Open Source licence (extended SISSL) Collect and provide relevant Grid Meta-Data Pluggable architecture Test Architecture for Grid Research The Iceni, under Queen Boudicca, united the tribes of South-East England in a revolt against the occupying Roman forces in AD60. 4

5 GridSAM Overview Grid Job Submission And Monitoring Service What is GridSAM? Funded by the OMII Managed Programme (Started in Sept, 04) Client Perspective Job Submission and Monitoring Web Service that bridges to existing systems (e.g. Condor, SGE) Job described in Job Submission Description Language File input and output staging Tools and simplified Java API for submission and monitoring Developer Perspective Extensible JobManager API interfacing with existing Distributed Resource Managers (DRM) Fault-tolerance and persistence Can be used as an embedded library (e.g. in Job Submission Portal, Grid Applications) Part of ICENI II 5

6 What is GRIDCC Grid enabled Remote Instrumentation with Distributed Control and Computation Adding real time control of instruments to the Grid What makes this unique: Instruments may only be ready at specific times Reservations Need to ensure other Grid services are available with instruments Reservations / SLA s Real-time visualisation of live results and steering Through Virtual Control Room (VCR) Reservations / SLA s 6

7 Types of Workflow Different users of the Grid have different views of what a workflow is

8 The Scientists Plan Conceptual Workflow 8

9 The Scientists Plan Middleware Workflow 9

10 Workflow mapping components user workflow VCR Data Process Control Process CE SE 10

11 Abstract Workflow Pipeline Decompose into interacting levels Specification Observation Planning Execution Security 11

12 Workflow Pipeline The stages that the workflow will go through from the users concept through to the executing application

13 Specification End-users High-level Abstract Workflow + QoS Preferences + Security Constraints Developers and Deployers Functional Description + Performance Annotation + Availability Realisation Syntactic and Semantic Validation Performance Data P2P / UDDI Static Workflow Optimisation Equivalent Workflow Candidates Performance Profiles Performance Repository Dynamic Optimisation and Scheduling Workflow Orchestration and Re-optimisation Discovery Component and Resource Availability Concrete Workflow + QoS constraints + Security constraints Execution Makes reservation Service Arranges deployment Execution Environment Service Co-ordinates message exchange Virtualised Component Container Service Environment Monitoring Reacts to opportunities and failures Component Packaging and Deployment Component Component Component

14 GRIDCC 14

15 OGSA Architecture London e-science Centre Execution Provisioning Deployment Configuration Reservation Information Services Planning Candidate Set Generator (Work - Resource mapping) Execution Planning Services Optimisation& Scheduling Service Container Data Container Job Manager Accounting Services Observation 15

16 The Planner Tasked with deciding where each part of the workflow should be deployed

17 Optimisation A good planner should be able to select an optimal set of resources and implementations of components Execution of workflows on the Grid is an NP-Hard problem Large number of resources available for use Multiple implementations of code that can be deployed onto resources Performance aware scheduling goes a long way to achieving a good selection 17

18 Workflow Scheduling with Performance Component Repository Deployment Service Planner Performance Repository 18

19 However: Algorithms for determining the best resources and implementations become slow as the search space increases Performance Information is often slow to obtain Current status of resources is often slow to obtain thus out of date by the time you get it We need to reduce the search space before doing performance aware planning 19

20 Information, Information, Information There is a vast amount of information available Lots of systems throw this information away

21 Information DISCARD user DISCARD Domain expert Problem space knowledge, Application knowledge Component knowledge Problem space knowledge Resource information Resource information Grid Structure information Component developer Resource Owner Grid Manager DISCARD 21

22 Using the Information Using this information to better perform the tasks that the user requires

23 Using information for Optimisation We can use Information for: Validation of the Workflow Make sure that only correct workflows are submitted Workflow Optimisation By altering the workflow to make it more optimal Resource Optimisation Pruning the set of resources that are considered 23

24 Workflow Validation London e-science Centre Goal: Ensure that a workflow is correct before it is accepted into the Grid. Reduce the chance of wasted time Requirements: Only look at the workflow and component information Achieve the goal through: Syntactic Validation Semantic Validation 24

25 Syntactic Validation Verify that the connections between components can be made An in-port can accept the data produced by the connected out-port Size and shape of the data matches A Out: Array int size x Information from the component description and workflow document B In: Array int size x 25

26 Semantic Validation The use of problem space knowledge To determine if the workflow Makes sense Will produce what the user intended Can equate to grammar checking Problem space knowledge exists for Mathematics already Need to expand to other areas Can be collected from Users and domain experts 26

27 Workflow Optimisation London e-science Centre Goal : optimise the runtime execution of workflow before it is executed Requirements: No performance or resource information is used Achieves the goal through: Re-ordering of components Substitution of components Addition of components Pruning of the workflow 27

28 Component Re-ordering London e-science Centre Workflows (often composed from composite workflows) may contain nonoptimal ordering of components Use re-ordering to improve performance - Domain knowledge Matrix Gen Matrix Gen multiply multiply Matrix Gen Matrix Gen multiply Vector Gen Vector Gen multiply 28

29 Component Substitution A Jacobi Iteration linear solver replaced by Conjugate Gradient linear solver according to the output of the Discretizer (FEM) Based on observing the meta-data associated with previous components A (sparse and diagonally dominant) FEM JI linear solver b 29

30 Component Addition To use an optimal component it may be necessary to transform the output of a previous component Need to identify optimal alternatives How to transform data for input Allows more optimal components to be used together Input required in C 1 Output in LP format LP to MPS MPS format C 2 30

31 Workflow Pruning Workflows may contain unused components Especially when composed from other subworkflows Remove redundant components a b d c f e g Not needed h Not needed 31

32 Resource Optimisation Goal : Reduce the number of resources that are considered for use Requirements: No workflow or resource current state information is used Achieves the goal through: Authorisation Hardware / Software requirements Problem Specific requirements Out of bounds 32

33 Component Deployment Abstracting the component developer from the underlying heterogeneity of the Grid

34 Deployment & Virtualisation Component Component transfers Deployment Service Prepare Workflow Pipeline deploy instantiate monitor Inter component communication Service Service Service Container Virtualised Operating System Operating System Hardware 34

35 Conclusion Information can be practically used to help in the manipulation and optimisation of workflows This is by no means a completed task Much more information can be collected There are other ways in which the information can be used 35

36 Any Questions? Thank you for listening

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