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XTREEMOS APPLICATION EXECUTION MANAGEMENT: A SCALABLE APPROACH Ramon Nou, Jacobo Giralt, Julita Corbalan, Enric Tejedor, J.Oriol Fitó, Josep M. Perez,

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Presentation on theme: "XTREEMOS APPLICATION EXECUTION MANAGEMENT: A SCALABLE APPROACH Ramon Nou, Jacobo Giralt, Julita Corbalan, Enric Tejedor, J.Oriol Fitó, Josep M. Perez,"— Presentation transcript:

1 XTREEMOS APPLICATION EXECUTION MANAGEMENT: A SCALABLE APPROACH Ramon Nou, Jacobo Giralt, Julita Corbalan, Enric Tejedor, J.Oriol Fitó, Josep M. Perez, Toni Cortes Barcelona Supercomputing Center (BSC – CNS) XtreemOS is funded by the European Commission through the Information Society Technology under contract IST-FP6-033576.

2 Outline XtreemOS Overview Application Execution Manager Job Execution Flow Monitoring Performance and scalability Job Execution Job Status Future

3 XtreemOS overview What is? A Linux-based operating system to support Virtual Organizations for Grid. Several layers

4 XtreemOS overview Some key features: The Grid easy to use (like a Linux) Highly scalable. Fault Tolerant. Able to run interactive jobs. Extensible 3 nodes types (can be replicated): Core Resource Client

5 Application Execution Manager Job management, Monitoring and resource management. Access Point to submit and control jobs. Distributed and asynchronous. Extensible Linux concepts in Grid world: Process-Thread paradigm. Signals.

6 Application Execution Manager Several distributed services: Job Manager. Execution Manager. Reservation Manager. … Semantics: JobUnit Set of processes of a Job running in a resource. Job Set of JobUnits. Identified by a JobID. [Process- Thread]

7 Job Execution Flow XOSD JobMng User XOSD ExecMng JobDirectory RSS Any XOSD Kernel JID = createJob(JSDL) JID runJob(JID) getResources(JSDL) Schedules & Executes process Job finished (all processes finished)

8 Monitoring System metrics. User defined metrics. Different levels of information. Buffering. Each service mantains its monitoring information (SCOPE). ExecMng has information about processes. JobMng has information about jobs. ResMng has information about resources.

9 Performance & scalability Key points: Collaboration with Linux Kernel. No central storage. (DHT’s) Can be replicated. Don’t search for best global scheduling, only for a good enough local scheduling. What is the performance without DHT’s? Typical VO, small (100 nodes) local grid.

10 Job Execution O(X 2 ): Need resource management for each submitted process. All processes are from the same job. (in other systems they would be independent jobs)

11 Job status Ask all processes information of the job with low overhead. Look job finished status in 0.012 seconds (0.014 in GT5) without contacting ExecMng’s

12 Future improvements Reduced internal communication times. Caching to reduce overhead. Some conclusions: Kernel Collaboration with «middleware» is important. DHT’s (not evaluated) are a good option to distribute data. But still no high performance. Including the concept 1 Job-> n Process gives the user a lot of benefits. Easy to understand, easy to manage.

13 XTREEMOS APPLICATION EXECUTION MANAGEMENT: A SCALABLE APPROACH Ramon Nou, Jacobo Giralt, Julita Corbalan, Enric Tejedor, J.Oriol Fitó, Josep M. Perez, Toni Cortes Barcelona Supercomputing Center (BSC – CNS) XtreemOS is funded by the European Commission through the Information Society Technology under contract IST-FP6-033576.


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