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Scalable Application Execution Management in XtreemOS: A Linux-Based Grid Solution

This document provides an overview of XtreemOS, a Linux-based operating system designed to support Virtual Organizations in Grid computing. It outlines the architecture and components of the Application Execution Manager, emphasizing job execution flow, monitoring, performance, and scalability aspects. Key features include fault tolerance, extensibility, and the ability to manage complex job structures efficiently. This approach allows for distributed and asynchronous job management, catering to the needs of high-performance computing environments.

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Scalable Application Execution Management in XtreemOS: A Linux-Based Grid Solution

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  1. XtreemOSApplicationExecution Management: A ScalableApproach RamonNou, Jacobo Giralt, Julita Corbalan, Enric Tejedor, J.OriolFitó, Josep M. Perez, Toni Cortes Barcelona Supercomputing Center (BSC – CNS) XtreemOSis funded by the European Commission through the Information Society Technology under contract IST-FP6-033576.

  2. Outline • XtreemOSOverview • ApplicationExecution Manager • Job ExecutionFlow • Monitoring • Performance and scalability • Job Execution • Job Status • Future

  3. XtreemOSoverview • Whatis? • A Linux-basedoperatingsystemtosupport Virtual OrganizationsforGrid. • Severallayers

  4. XtreemOSoverview • Somekeyfeatures: • TheGrideasyto use (like a Linux) • Highlyscalable. • FaultTolerant. • Abletoruninteractivejobs. • Extensible • 3 nodestypes (can be replicated): • Core • Resource • Client

  5. ApplicationExecution Manager • Job management, Monitoringand resourcemanagement. • Access Point tosubmit and control jobs. • Distributed and asynchronous. • Extensible • Linux concepts in Gridworld: • Process-Threadparadigm. • Signals.

  6. ApplicationExecution Manager • Severaldistributedservices: • Job Manager. • Execution Manager. • Reservation Manager. • … • Semantics: • JobUnit • Set of processes of a Job running in a resource. • Job • Set of JobUnits. Identifiedby a JobID. [Process-Thread]

  7. Job ExecutionFlow runJob(JID) Any XOSD JID = createJob(JSDL) User Job finished (allprocessesfinished) Kernel XOSD JobMng XOSD ExecMng JobDirectory JID Schedules & Executesprocess RSS getResources(JSDL)

  8. Monitoring • Systemmetrics. • Userdefinedmetrics. • Differentlevels of information. • Buffering. • Eachservicemantainsitsmonitoringinformation (SCOPE). • ExecMng has informationaboutprocesses. • JobMng has informationaboutjobs. • ResMng has informationaboutresources.

  9. Performance & scalability • Key points: • Collaborationwith Linux Kernel. • No central storage. (DHT’s) • Can be replicated. • Don’tsearchforbest global scheduling, onlyfor a goodenough local scheduling. • Whatisthe performance withoutDHT’s? • Typical VO, small (100 nodes) local grid.

  10. Job Execution • O(X2): • Needresourcemanagementforeachsubmittedprocess. • Allprocesses are fromthesamejob. (in othersystemstheywould be independentjobs)

  11. Job status • Ask allprocessesinformation of thejobwithlowoverhead. • Look jobfinished status in 0.012 seconds (0.014 in GT5) withoutcontactingExecMng’s

  12. Futureimprovements • Reducedinternalcommunication times. • Cachingto reduce overhead. • Someconclusions: • KernelCollaborationwith «middleware» isimportant. • DHT’s (notevaluated) are a goodoptiontodistribute data. • Butstill no high performance. • Includingthe concept 1 Job-> n Processgivestheuser a lot of benefits. • Easytounderstand, easytomanage.

  13. XtreemOSApplicationExecution Management: A ScalableApproach RamonNou, Jacobo Giralt, Julita Corbalan, Enric Tejedor, J.OriolFitó, Josep M. Perez, Toni Cortes Barcelona Supercomputing Center (BSC – CNS) XtreemOSis funded by the European Commission through the Information Society Technology under contract IST-FP6-033576.

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