towards scalable, semantic-based virtualized storage resources provisioning

EUROPEAN UNION

Polish InfrastructurePolish Infrastructurefor Supporting Computational Sciencefor Supporting Computational Science

in the European Research Spacein the European Research Space

Towards scalable, semantic-based Towards scalable, semantic-based virtualized storage resources virtualized storage resources

provisioningprovisioning

Kornel Skałkowski, Renata Słota, Kornel Skałkowski, Renata Słota, Dariusz KrólDariusz Król, , Michał Orzechowski, Bartosz Kryza, Jacek KitowskiMichał Orzechowski, Bartosz Kryza, Jacek Kitowski

ACC Cyfronet AGH, Krakow, PolandACC Cyfronet AGH, Krakow, Poland

KU KDM 2012 : fifth ACC Cyfronet AGH users' conference : Zakopane, March 07–09, 2012

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OutlineOutline

Introduction The QStorMan toolkit overview The QStorMan toolkit architecture QStorMan usage Recent improvements Current status of QStorMan Test results Future Work

IntroductionIntroduction

Data intensive applications and the 4th science paradigm Resources virtualization becomes ubiquitous Storage resources virtualization is often provided by cluster file systems like

Lustre IT infrastructure users expect more and more computing and storage power

as well as an appropriate QoS level

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The QStorMan toolkitThe QStorMan toolkit

Main goal is to provide virtualized storage resources with QoS warrianties for data intensive applications

Users can define QoS requirements concerning storage resources on three levels: application, user, virtual organization

Currently we support the following non-functional requirements: Average Read/Write transfer rate, Current Read/Write transfer rate, Free capacity, Result cachability – dedicated for application, which generates a large number

of small files. The toolkit consists of three components:

Knowledge base (GOM) which stores semantic descriptions concerning storage resources and synchronizes the descriptions with a grid middleware

Dedicated monitoring service (SMED) which performs continuous, real-time monitoring of virtualized storage resources with semantic support

Intelligent resources matching service (SES) which combines information obtained from the GOM and SMED services as well as advanced semantic support in order to perfectly match a virtualized resource from the resources mesh

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The QStorMan toolkit architectureThe QStorMan toolkit architecture

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QStorMan usageQStorMan usage

1.Using system C library (libses-wrapper):declare your non-functional requirements in the GOM knowledge base export LD_PRELOAD=<path_to_libses_wrapper_librart>

2. Using C++ programming library (libses):

#include <LustreManager.h>

#include <StoragePolicyFactory.h>

using namespace lustre_api_library;

LustreManager manager;

StoragePolicy policy;

policy.setAverageReadTransferRate(50);

policy.setCapacity(100);

int descriptor = manager.createFile(„nazwa_pliku.dat”, &policy);

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Recent improvementsRecent improvements

General purpose of the improvements is to provide a scalable, fully semantic-based solution for efficient provisioning of virtualized storage resources

SMED improvements: Utilization of the enhanced C2MS storage resources semantic model for

description of high-level QoS parameters Application of semanatic reasoners on the monitoring level

SES improvements Cache mechanism on demand – supporting large number of files generation Automatic registration of users in knowledge base – decrease required

administration effort GOM improvements

Security enhancements Scripts for administration

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The QStorMan toolkit current statusThe QStorMan toolkit current status

Test installation is running at ACC Cyfronet AGH from over 1 year now A lot of tests were performed and no major bugs were found We have passed operational and security audits in PL-Grid succesfully We now waiting for official deployment in ACC Cyfronet, PCSS Poznan, TASK

Gdansk, and ICM Warsaw Official tutorials, workshops and other material are on the way Integrated with QoSCosGrid middleware from PCSS

We are willing to cooperate with anyone, who would like to test QStorMan in practice with an exisiting data intensive application

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Test descriptionTest description

Synthetic testThe toolkit evaluation was performed by simulation of 8 users which were executing their applications on the Grid infrastructure3 users used the QStorMan toolkit during the applications execution, the others used plain Lustre file systemEvery user periodically saved and read a 60 GB file with random sleep periods between the succeeding operations (10 reads and 10 writes)Users started their applications with random delays in order to simulate real conditions in a Grid environment

Test with real user’s applicationSimulation of sound wave propagation inside human headOut-of-core computationsNo source code modifications5 instances of application running in parallel in order to generate enough load for storage system

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Synthethic test resultsSynthethic test results

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• 12% speedup between two fastest applications• 26% speedup on average (~7:20 h vs ~10 h)• No source code modification

Real user’s application test resultReal user’s application test result

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• 15% speedup on average • Running on production infrastructure• No source code modification

Future workFuture work

Support for domain-oriented virtualized computing environments Implementation of new storage resources selection strategies Orientation toward Cloud computing environments

Dissemination and exploitation among possible users

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Questions?Questions?

dkrol@agh.edu.pldkrol@agh.edu.plrena@agh.edu.plrena@agh.edu.pl

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