Eddy CaronJoin work with Jonathan Rouzaud-Cornabas, Frédéric Desprez,

Rajesh Palanichamy and the DIET Team

Ecole Normale Supérieure de LyonAVALON Research Team

SysFera

DIET’s GoalsDIET’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/

6/03/12 DIET a Cloud Middleware for Seed4C

RPC and Grid-Computing: Grid-RPCRPC 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

6/03/12 DIET a Cloud Middleware for Seed4C

RPC and Grid Computing: Grid-RPCRPC and Grid Computing: Grid-RPC

AGENT(s)

S1 S2 S3 S4

A, B, C

Answer (C)

S2 !

Request

Op(C, A, B)

Client

6/03/12 DIET a Cloud Middleware for Seed4C

Client and server interfaceClient 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new service new version security update outdated service Etc.

6/03/12 DIET a Cloud Middleware for Seed4C

Architecture overviewArchitecture overview

6/03/12 DIET a Cloud Middleware for Seed4C

Workflow ManagementWorkflow 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 time Data transfert

Execution time

EGI (Glite) 32.857s 132.143 s 274.643 s

Grid’5000 (DIET)

0.214s 3.371 s 540.614 s6/03/12 DIET a Cloud Middleware for Seed4C

DIET Scheduling: Plug-in Schedulers 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.

6/03/12 DIET a Cloud Middleware for Seed4C

Data ManagementData Management

DAGDA Joining task scheduling and data

managementStandardized 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.

6/03/12 DIET a Cloud Middleware for Seed4C

Join work with Gaël LeMahec (UPJV/MIS)

Parallel & sequential jobstransparent for the usersystem dependent submission

SeDBatch

Many batch systemsBatch schedulers behaviourInternal scheduling process

Monitoring & Performance prediction Simulation (Simbatch)

Parallel and batch submissionsParallel and batch submissions

SeDSeD

OAR

OGELSF

PBS

Loadleveler

SeDBatch

SeD//

NFS

6/03/12 DIET a Cloud Middleware for Seed4C

SLURM

DIET Cloud: PrototypeDIET Cloud: Prototype

Inside the CloudDIET 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 managerEucalyptus interfaceEucalyptus is treated as a new Batch SystemProvide a new implementation for the BatchSystem

abstract class

6/03/12 DIET a Cloud Middleware for Seed4C

DIET Cloud: New ArchitectureDIET Cloud: New Architecture

6/03/12 DIET a Cloud Middleware for Seed4C

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’5000Grid’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

6/03/12 DIET a Cloud Middleware for Seed4C

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

6/03/12 DIET a Cloud Middleware for Seed4C

ResultsResults

A complete Middleware for heterogeneous infrastructureDIET is light to useDedicated to many applicationsDesigned for Grid and Cloud Efficient even in comparison to commercial toolsDIET is high tunability middlewareUsed in production

The DIET Team

SysFera Compagny (16 persons today) http://www.sysfera.com

6/03/12 DIET a Cloud Middleware for Seed4C

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