Solving inter grid interoperability issues: example of WISDOM and molecular dynamics Jean Salzemann, LPC Clermont-Ferrand, CNRS/IN2P3 Morris Riedel, Jülich.

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Presentation transcript:

Solving inter grid interoperability issues: example of WISDOM and molecular dynamics Jean Salzemann, LPC Clermont-Ferrand, CNRS/IN2P3 Morris Riedel, Jülich Supercomputing Center, Germany Credits: Vincent Bloch, Matthieu Reichstadt, Ana Lucia Da Costa (LPC Clermont, France) Sehoon Lee, Namgyu Kim, Jincheol Kim (KISTI, Korea)

Introduction Why Interoperability? – Access more resources – Benefit from more functionalities: each infrastructure fitted for specific requirements – Ease human and scientific collaboration – Share knowledge and expertise without increasing workload of users and complexity of interfaces and workflows!

Long term vision

Issues of Interoperability Issues of protocols Issues of APIs and clients Issues of Security infrastructure 2 approaches: o Virtualize specificities with meta-middleware layer o Use of standardized mechanisms

WISDOM Production Environment Fi le IS Bi o IS WISDOM Information System AMGA WISDOM Information System Client Services Local Data Repositor y Data Manager Local Data Repository Database Service Database Service Data Manager Data Management APIs Transfer Manager FTPHTTP EGEE SESE SESE CECE CECE DIGITAL RIBBON SESE SESE EGEE EGEE SE CE SE CE OSG Data Metadata Job Manager Job Submitter Jobs Task Manager Tasks Management APIs

WISDOM Production Environment Features and specifications - Transfer Managers manage specific grid data transfer protocols. (one manager per protocol) - Task and agent management is independent from middleware specifications. - Job Submitters manage specific wms. (one job submitter per wms type) - Integration of new middleware requires development of specific Transfer Manager and Job Submitter with the middleware client APIs. - Grid credentials of the environment used on behalf of the end-users. Each infrastructure requires specific credentials (no common security infrastructure nor virtual organization): suitable for bioinformaticians. - Workload management is done by the system. Users just have to focus on business logics: SoA model.

Integration of MD on DEISA

MD deployment Features and specifications - Interoperability relies on the use of standard protocols: - OGSA – BES (Basic Execution Services) - JSDL (Job Submission Description Language) - CSP (common security profile) with SAML-based voms. - All jobs are submitted with user credentials. - Deployments require each grid to adopt these standards. Once standards are adopted: no need to further modify the system. - Inter grid file transfers still requires manual intervention. - No virtualization of workload management. Users still need to understand how the resources have to be used and managed. Users need to take care of both business logics and workload management workflows.

Conclusion WISDOM PE: – Pragmatic approach that is already implemented and in production at this time and offer good performances. – Users only focus on business-logics, no need for them to learn the grid in order to use it: virtualization of middleware logics. – Allows multiple types of clients. SOA added-value: users work directly with operations and services of their knowledge domain. – More focused on a specific type of application and usage policy. OMII: – medium to long term approach: requires middlewares to fit the specifications in order to be used in production – Less constraints for integration: no need for specific development, only specifications. – Fit all types of applications, and usage policies. The 2 approaches are complementary: once standards are decided and implemented, specific business virtualization can be done on top of it.