1. Eddy Caron Join work with Jonathan Rouzaud-Cornabas, Frédéric Desprez, Rajesh Palanichamy and the DIET Team Ecole Normale Supérieure de Lyon AVALON Research Team SysFera

2. DIET’s Goals Our goals To develop a toolbox for the deployment of environments using the Application Service Provider (ASP) paradigm with different applications Use as much as possible public domain and standard software To obtain a high performance and scalable environment Implement and validate our more theoretical results Scheduling for heterogeneous platforms, data (re)distribution and replication, performance evaluation, algorithmic for heterogeneous and distributed platforms, … Based on CORBA and our own software developments FAST for performance evaluation, LogService for monitoring, VizDIET for the visualization, GoDIET for the deployment Several applications in different fields (simulation, bioinformatics, …) Release 2.8 available on the web since november ACI Grid ASP, RNTL GASP, ANR LEGO CIGC-05-11, ANR Gwendia, Celtic-plus Project SEED4C http://graal.ens-lyon.fr/DIET/ 6/03/12DIET a Cloud Middleware for Seed4C

3. RPC and Grid-Computing: Grid-RPC One simple idea – Implementing the RPC programming model over the grid – Using resources accessible through the network – Mixed parallelism model (data-parallel model at the server level and task parallelism between the servers) Features needed – Load-balancing (resource localization and performance evaluation, scheduling), – IDL, – Data and replica management, – Security, – Fault-tolerance, – Interoperability with other systems, – … Design of a standard interface – within the OGF (Grid-RPC and SAGA WG) – Existing implementations: NetSolve/GridSolve, Ninf, DIET, OmniRPC 6/03/12DIET a Cloud Middleware for Seed4C

4. RPC and Grid Computing: Grid-RPC AGENT(s) S1S2 S3 S4 A, B, C Answer (C) S2 ! Request Op(C, A, B) Client 6/03/12DIET a Cloud Middleware for Seed4C

5. Client and server interface Client side So easy … Multi-interface (C, C++, Fortran, Java, Python, Scilab, Web, etc.) Grid-RPC compliant Server side Install and submit new server to agent (LA) Problem and parameter description Client IDL transfer from server Dynamic services new service new version security update outdated service Etc. 6/03/12DIET a Cloud Middleware for Seed4C

6. Architecture overview 6/03/12DIET a Cloud Middleware for Seed4C

7. Workflow Management Workflow representation Direct Acyclic Graph (DAG) Each vertex is a task Each directed edge represents communication between tasks Goals Build and execute workflows Use different heuristics to solve scheduling problems Extensibility to address multi-workflows submission and large grid platform Manage heterogeneity and variability of environment ANR Gwendia Language definition (MOTEUR & MADAG) Comparison on Grid’5000 vs EGI Idle timeData transfertExecution time EGI (Glite)32.857s132.143 s274.643 s Grid’5000 (DIET) 0.214s 3.371 s540.614 s 6/03/12DIET a Cloud Middleware for Seed4C

8. DIET Scheduling: Plug-in Schedulers SeD level Performance estimation function Estimation Metric Vector - dynamic collection of performance estimation values Performance measures available through DIET FAST-NWS performance metrics Time elapsed since the last execution CoRI (Collector of Resource Information) Developer defined values Aggregation Methods Defining mechanism to sort SeD responses: associated with the service and defined at SeD level Tunable comparison/aggregation routines for scheduling Priority Scheduler Performs pairwise server estimation comparisons returning a sorted list of server responses; Can minimize or maximize based on SeD estimations and taking into consideration the order in which the request for those performance estimations was specified at SeD level. 6/03/12DIET a Cloud Middleware for Seed4C

9. Data Management DAGDA Joining task scheduling and data management Standardized through GridRPC OGF WG. Data Arrangement for Grid and Distributed Applications Explicit data replication: Using the API. Implicit data replication. Data replacement algorithm: LRU, LFU AND FIFO Transfer optimization by selecting the more convenient source. Storage resources usage management. Data status backup/restoration. 6/03/12DIET a Cloud Middleware for Seed4C Join work with Gaël LeMahec (UPJV/MIS)

10. Parallel & sequential jobs transparent for the user system dependent submission SeD Batch Many batch systems Batch schedulers behaviour Internal scheduling process Monitoring & Performance prediction Simulation (Simbatch) Parallel and batch submissions SeD OAROGE LSF PBSLoadleveler SeD Batch SeD // NFS 6/03/12DIET a Cloud Middleware for Seed4C SLURM

11. DIET Cloud: Prototype Inside the Cloud DIET platform is virtualized inside the cloud. (as Xen image for example) Very flexible and scalable as DIET nodes can be launched Scheduling is more complex DIET as a Cloud manager Eucalyptus interface Eucalyptus is treated as a new Batch System Provide a new implementation for the BatchSystem abstract class 6/03/12DIET a Cloud Middleware for Seed4C

12. DIET Cloud: New Architecture 6/03/12DIET a Cloud Middleware for Seed4C

13. Building a nation wide experimental platform for Grid & P2P researches (like a particle accelerator for the computer scientists) 9 geographically distributed sites hosting clusters with 256 CPUs to 1K CPUs) All sites are connected by RENATER (French Res. and Edu. Net.) Design and develop a system/middleware environment for safely test and repeat experiments Use the platform for Grid experiments in real life conditions 4 main features: A high security for Grid’5000 and the Internet, despite the deep reconfiguration feature Single sign-on High-performance LRMS: OAR A user toolkit to reconfigure the nodes and monitor experiment: Kadeploy Grid’5000 Grid’5000 DIET deployment over a maximum of processors 1 MA, 8 LA, 540 SeDs 1120 clients on 140 machines DGEMM requests (2000x2000 matrices) Simple round-robin scheduling 6/03/12DIET a Cloud Middleware for Seed4C

14. Conclusions http://www.grid5000.org/ Grid-RPC Interesting approach for several applications Simple, flexible, and efficient Many interesting research issues (scheduling, data management, resource discovery and reservation, deployment, fault-tolerance, …) DIET Scalable, open-source, and multi-application platform Concentration on several issues like resource discovery, scheduling (distributed scheduling and plugin schedulers), deployment (GoDIET), performance evaluation (CoRI), monitoring (LogService and VizDIET), data management and replication (DAGDA), Cloud support Large scale validation on the Grid’5000 platform A middleware designed and tunable for different applications 6/03/12DIET a Cloud Middleware for Seed4C

15. Results A complete Middleware for heterogeneous infrastructure DIET is light to use Dedicated to many applications Designed for Grid and Cloud Efficient even in comparison to commercial tools DIET is high tunability middleware Used in production The DIET Team SysFera Compagny (16 persons today) http://www.sysfera.com 6/03/12DIET a Cloud Middleware for Seed4C

16. http://graal.ens-lyon.fr/DIET