Marie Curie Fellowship Project Nr. 509252

Hrachya AstsatryanInstitute for Informatics and Automation

Problems, NAS RARMKI KFKI

About me

2001- Ph.D. (Technical Sciences), Thesis: “Distributed Systems Software Management Organizing via Web Technology”

Last Projects ISTC A-823, ArmCluster: Creation of High-Performance

Computation Cluster and Databases in Armenia ISTC A-092.2, Database and Culture Collection of

Microorganisms Degradation Synthetic Polymers and Toxic Chemicals

Development of an Infrastructure for supporting High Performance Computations and Large scale Databases" project within the framework of an "Armenian State Scientific Computation System Development" program

Outline Plan

2. Analyze KFKI Grid site

3. To research KFKI Grid site including the benchmarking of performance and scalability parameters.

4. To develop a Web site which will include benchmarking results.

5. To develop a Web Scientific Computing Environment (WSCE).

KFKI LCG Grid Benchmarking, why?

Allows to compare the performance KFKI Grid computing resources with other parallel systems.

Allows to investigate performance properties of parallel systems under carefully tuned, benchmark-induced workloads that stress particular aspects of system performance.

Helpful for predicting the performance and scalability of a category of complex applications on a given system; to this end, kernels representative of this category of applications are produced and executed to estimate overall application performance.

KFKI LCG Grid Benchmarking Layers

The Resource, for example the cluster node (Dual AMD ATHLON MP 2000+ , AMD ATHLON XP 1900+ ), or the Storage Element (Elonex Disk Server ) interface to mass storage.

The Site, which is a collection of resources interconnected through a local- or system-area network, and belonging to one administrative domain (e.g. a cluster of PCs or a symmetric multiprocessor system);

The Middleware, that is the software layer providing access to shared resources of a Grid constellation and which gives the programmer the Grid as a shared resource.

KFKI LCG Grid Benchmarking Web Site Structure

Benchmarking

Resource Site

File System Performance Memory

HPL

Introduction Results Comparison On Line Information

Bonnie

Bonnie performs a series of tests on a file of known size. For each test, Bonnie reports the bytes processed per elapsed second, per CPU second, and the % CPU usage (user and system). The tests are:

1. Sequential Output Per-Character: The file is written using the putc() stdio macro. Block: The file is created using write(2). . Rewrite: Each Chunk of the file is read with read(2), dirtied, and

rewritten with write(2), requiring an lseek(2). 2. Sequential Input

Per-Character: The file is read using the getc() stdio macro. Block: The file is read using read(2).

3. Random Seeks

HPL - A Portable Implementation of the High-Performance Linpack Benchmark

HPL is a software package that solves a (random) dense linear system in double precision (64 bits) arithmetic on distributed-memory computers. It can thus be regarded as a portable as well as freely available implementation of the High Performance Computing Linpack Benchmark.

The HPL package provides a testing and timing program to quantify the accuracy of the obtained solution as well as the time it took to compute it. The best performance achievable by this software on your system depends on a large variety of factors. Nonetheless, with some restrictive assumptions on the interconnection network, the algorithm described here and its attached implementation are scalable in the sense that their parallel efficiency is maintained constant with respect to the per processor memory usage.

STREAM - Memory Benchmark

The STREAM benchmark is a simple synthetic benchmark program that measures sustainable memory bandwidth (in MB/s) and the corresponding computation rate for simple vector kernels.

The STREAM benchmark is specifically designed to work with datasets much larger than the available cache on any given system, so that the results are more indicative of the performance of very large, vector style applications. It does it so that there will be a single copy of the cache line in the system for which all the bytes are current and valid.

WSCE: Purpose

The goal of WSCE is to develop a Web scientific computing environment on top of Matlab (Scilab, Octave), which will enable users to run their tasks remotely on Grid systems easily by means of a Web interface that has the advantage of being very familiar to most users and that do not require to install (on the user machine) any piece of

software.

Well known Open source Matlab Implementations over Grid- Scilab, Octave

Scilab is a scientific software package for numerical computations providing a powerful open computing environment for engineering and scientific applications. Developed since 1990 by researchers from INRIA and ENPC, it is now maintained and developed by Scilab Consortium since its creation in May 2003. Scilab includes hundreds of mathematical functions with the possibility to add interactively programs from various languages (C, Fortran...).

GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with Matlab.

WSCE: Environment Description

Matlab User

WEB

Management Interface

Expertsie Request Final Results

Scilab Octave

Elementary Requests List Intermediary of Final Results

Matlab Grid Middlewares:

SciLab (FAST, DIET) - FAST (Fast Agent System Timers) is a tool for dynamic performance forecasting in a Grid environment. It uses a network and CPU monitoring software to handle dynamically changing resources, like workload or bandwidth. The integration of such libraries in high level applications using languages like Fortran or C is far from being easy.

Octave (Netsolve) - NetSolve is a client-server-agent system that enables users to solve complex scientific problems remotely using distributed resources on a computational Grid. The system provides users access to both hardware and software computational resources distributed across a network. When a user submits a problem to the NetSolve agent, the agent searches the network of computational resources that has registered with it, chooses the best one (or set) available, solves the problem, and then returns the solution to the user.

Grid

WSCE: Environment Description

FAST, DIET Netsolve

Matlab User

WEB

Management Interface

Expertsie Request Final Results

Scilab Octave

Elementary Requests List Intermediary of Final Results

WSCE: Management Interface

High level administrator interface for the definition, the deployment, and the exploitation of services over grid.

Launch executions on the Grid from requests•According to the scenario•Select solvers and architectures