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Wide Area Workload Management Work Package DATAGRID project

Wide Area Workload Management Work Package DATAGRID project. Tasks List:. Job description and resource spec Job decomposition partitioning Scheduling Co-allocator+adv reservation Resource management Services and access control. Scheduling.

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Wide Area Workload Management Work Package DATAGRID project

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  1. Wide Area Workload ManagementWork PackageDATAGRID project

  2. Tasks List: • Job description and resource spec • Job decomposition partitioning • Scheduling • Co-allocator+adv reservation • Resource management • Services and access control

  3. Scheduling • Definition of scheduling policies in order to find the best match between job requirements and available resources • Network • Storage • Cpu

  4. Deliverables D1.1 (Report) Month 3: Report on current technologyD1.2 (Report) Month 6: Definition of architecture , technical plan and evaluation criteria for scheduling , resource management.security and job description.D1.3 (Prototype) Month 9: Components and documentation for the 1st release: Initial workload management system integrating existing technology and implementing computing resources brokerage.D1.4 (Report) Month 18: Definition of the architecture, technical plan and evaluation criteria for the resource co-allocation framework and mechanisms for parallel job partitioning.D1.5 (Prototype) Month 21: Components and documentation of the workload management system implementing code migration , user interface for task management., services for logging and bookkeepingD1.6 (Prototype) Month 33: Components and documentation for the workload management system implementing data migration and remote access, co-allocation of resources, job description and users interface, services for bookkeeping and accounting and mechanism to specify job flowsD1.7 (Report) Month 36: Final evaluation report.

  5. Milestonesand expected result M1.1 Month 9: Components and documentation for the 1 release: Initial workload management system based on existing technology integration M1.2 Month 21:Components and documentation for the 2 release: Workload management scheduling implementing code migration M1.3 Month 33:Components and documentation for the final release Workload management scheduling implementing data migration and remote access

  6. 1 Release PM 9 • Job and resource required description: • using class-ads language. • a possible high level interface based on XML will be investigated. • first release of command line tool for job management (to submit, cancel, monitor jobs). • job policy and admission control. • policies on resource usage based on user and user community identity.

  7. 1 Release PM 9 • available resource selection using code migration paradigm. This selection will take into account: • available CPU in different farms spread in different sites. • location of input data. • cost of executable migration. • available resources (disk space) for output data. • first release of accounting and bookkeeping services: • monitoring of job status about processed data, • output data produced, processing evaluation. The globus GRAM protocol is the uniform interface to the localresources. The local resources are "cluster" of nodes, mainly PCs,managed by the PBS, LSF, Condor etc. software.The basic information system for this release is the Grid InformationService by the Globus project.

  8. 2 Release PM 21 • Improvement of the first release also for high performance jobs takinginto account: • job monitoring data • resources (Computing, Storage, Network) monitoring data • performance prediction • cost of data migration • fault tolerance • The scheduling activity will also consider co-allocation of multipleresources, cost of data movement/replication,remote data access. • Improvement of the high level job descriptioninterface and user services interface. • Evaluation and adoption of a proper security framework for allocationand authentication of resources usage.

  9. 3 Release PM 33 • Exploitation of data/task parallelism • Advance reservation of resources • Optimal scheduling or rescheduling using performance monitoring tools

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