Polish InfrastructurePolish Infrastructurefor Supporting Computational Sciencefor Supporting Computational Science

in the European Research Spacein the European Research Space

FiVO/QStorMan: toolkit for supporting FiVO/QStorMan: toolkit for supporting data-oriented applications in PL-Griddata-oriented applications in PL-Grid

R. Slota (1,2), D. Król (1), R. Slota (1,2), D. Król (1), K. Skalkowski (1), B. Kryza (1), K. Skalkowski (1), B. Kryza (1),

D. Nikolow (1,2), and J. Kitowski (1,2)D. Nikolow (1,2), and J. Kitowski (1,2)

(1) ACC Cyfronet AGH, Kraków, Poland(1) ACC Cyfronet AGH, Kraków, Poland(2) Institute of Computer Science AGH-(2) Institute of Computer Science AGH-

UST, Krakow, PolandUST, Krakow, Poland

KU KDM 2011

Zakopane, 9-11.03.2011

AgendaAgenda

1. Data intensive applications2. Research and implementation goals3. Non-functional requirements in data management4. FiVO/QStorMan toolkit components and architecture5. FiVO/QStorMan usage6. Testing scenarios7. Results8. Conclusions

Data intensive applicationsData intensive applications

Main features:Generate gigabytes (or more) of data per day.Different types of data which require different types of storage.Heavily uses read/write operations.The run time of an application heavily depends on storage access time and transfer speed rather than the computation time.

Scientific examples (from wikipedia):The LHC experiment produces 15 PB/year = ~42 TB/day = ~1 GB/sThe German Climate Computing Center (DKRZ) has a storage capacity of 60 petabytes of climate data.

Research and implementation goalsResearch and implementation goals

The main objective of the presented research is to manage the data coming from Grid applications using the following concepts:

allowing users to define non-functional requirements for storage devices explicitly,

exploiting a knowledge base of the VO extended with descriptions of storage elements

exploiting information from storage monitoring systems and VO knowledge base to find the most suitable storage device complient with the defined requirements

Non-functional requirements in data Non-functional requirements in data managementmanagement

Data intensive applications may have different requirements, e.g. important data should be replicated

Abstraction of storage elements prevents users from influencing the actual location of data

Distribution of data among available storage elements according to the defined requirements

Sample non-functional requirements:• freeCapacity• currentReadTransferRate• averageWriteTransferRate

FiVO/QStorMan toolkitFiVO/QStorMan toolkit

FiVO/QStorMan usageFiVO/QStorMan usage

1. Using QStorMan portal: Declare your non-functional requirements in the QStorMan portlet. Copy and paste the returned text from the portlet to your JDL file.

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);

3. Using system C library: declare your non-functional requirements in the GOM knowledge base export LD_PRELOAD=<path_to_libses_wrapper_librart>

FiVO/QStorMan testing environmentFiVO/QStorMan testing environment

ACC Cyfronet AGH (Cracow) Scientific Linux SL release 5.5 (Boron) 2x Intel(R) Xeon(R) CPU L5420 @ 2.50GHz (4 cores, 1 thread per core) 16056 MB RAM ~ 12 TB storage capacity, ~150 MB/s read transfer rate, ~70 MB/s write

transfer rate

PCSS (Poznan): Scientific Linux CERN SLC release 5.5 (Boron) Intel(R) Xeon(R) CPU 5160 @ 3.00GHz (2 cores, 1 thread per core) 1000 MB RAM ~ 14 TB storage capacity, ~55 MB/s read trasfer rate, ~46 MB/s write

trasfer rate

ICM (Warsaw): CentOS release 5.5 (Final) Intel(R) Xeon(R) CPU X3430 @ 2.40GHz (4 cores, 1 thread per core) 7975 MB RAM ~ 5 TB storage capacity, ~50 MB/s read trasfer rate, ~27 MB/s write

trasfer rate

Testing scenario Testing scenario

Scenario: Aims to simulate a Grid job which is scheduled to

run in the most suitable data center. The job performs computation and then writes data.

Scenario parameters:• Number of users – 3 (2 users used QStorMan)

and 4 • File size – 512 MB• Number of files to write – 20 , 30 , 40

Scenario: Aims to simulate a Grid job which is scheduled to

run in the most suitable data center. The job performs computation and then writes data.

Scenario parameters:• Number of users – 3 (2 users used QStorMan) • File size – 512 MB• Number of files to write – 20 , 30 , 40

ResultsResults

Conclusions and Future workConclusions and Future work

The presented research goal is to develop new approaches to issues of storage management in the Grid environment

Explicit definitions of non-functional requirements are necessary in data intensive applications

Allowing to accelerate data-oriented Grid applications by ~45% without any modifications in source code

Future work: Integration with Grid Queuing Systems Integration with Virtual Organizations

Do you want to know more ?

www.plgrid.pl

or

dkrol@agh.edu.pl