mGrid: A load-balanced distributed computing environment for the
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1. 36 Tela the Tensor Language http www ava fmi fi prog tela html 37 Girvan R The battle for hearts and minds Scientific Computing World 2002 38 Apache HTTP Server Project http httpd apache org 39 Almeida JS Stanislaus R Krug E Arthur JM Normalization and analysis of residual variation in two dimensional gel electro phoresis for quantitative differential proteomics Proteomics 2005 5 5 1242 1249 40 GNU General Public License http www fsf org licensing licenses gpl html Publish with BioMed Central and every scientist can read your work free of charge BioMed Central will be the most significant development for disseminating the results of biomedical research in our lifetime Sir Paul Nurse Cancer Research UK Your research papers will be e available free of charge to the entire biomedical community e peer reviewed and published immediately upon acceptance e cited in PubMed and archived on PubMed Central e yours you keep the copyright Submit your manuscript here O BioMedcentral http www biomedcentral com info publishing_adv asp Page 12 of 12 page number not for citation purposes2. machines that maintain balanced workload distribution among workers in mGrid Figure 1 The main and backup systems maintain identical information on the availability of the worker machines to be targeted by remote calls Global eval function geval initially commu nicates with the main master server A request will always go to the same main server The backup master will be contacted only in the case of the main server not respond ing to the client s request thus preventing any downtime of the mGrid The mGrid will be temporarily unavailable in the case of both the main and the backup master servers being down simultaneously After geval receives the worker IP address it sends the job request to that worker Addition of workers to the mGrid requires a request to be sent via the volunteer command in Matlab to both mas ter servers so that a consistent view of the worker states is maintained Master servers have a check mechanism to prevent multiple additions of the same worker to the mGrid if volunteer command is executed more then once Thus repeated executions of the volunteer command will have no effect on the masters Master servers maintain workload information on the workers by periodically polling the workers about the number of their available CPU cycles This is done by crontab calling a PHP script update_busyinfo php which in turn contacts all the workers to get the workload infor mation by calling a PHP script busyinfo php on
3. of the help file bellow Function todoprocessor is a service started automatically at computer boot time It locates newly arrived requests starts the execution of the requests updates the status of the request to running and finally when request is com pleted it makes results available to the client Adding a master server to the mGrid As for the worker side toolbox the automatic installation scripts provided for the master side toolbox were written specifically for computers running the Linux operating Page 7 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 http www biomedcentral com 1471 2105 7 139 Cliant request for worker IP address SEPPE g 1040m BJENEAL 1388 Master Apache Web Server My F fea potential worker m of H f m a8 E SE z T Og a fe oo T 0 Oz Workload information file Update workloaginfo based on workers load reports Crontab workload information job GelWorkload report fim all workersat specified timbptervals Figure 3 Communication between processes on the master server Communication between processes on a master server configured strictly as a master server not also as a worker At the top the down pointing arrow indicates a client request for the IP of an available worker computer geval The Apache web server large oval accepts the request via a PHP script which gets the IP address of the currently best avail
4. pvm pym home html 22 Jini Network Technology http www sun com software jini 23 Akl S Parallel Computation Models and Methods Prentice Hall 1997 24 Tanenbaum A Steen M Distributed Systems Principles and Paradigms Prentice Hall 2002 25 PHP http www php net 26 Savageau MA Voit EO Recasting Nonlinear Differential Equa tions As S Systems A Canonical Nonlinear Form Math Bio science 987 87 83 115 27 Sorribas A Savageau MA Strategies for representing metabolic pathways within biochemical systems theory reversible pathways Math Bioscience 1989 94 2 239 269 28 Almeida JS Voit EO Neural Network Based Parameter Esti mation in S System Models of Biological Networks 2003 14 1 14 123 29 Voit EO J S A Decoupling Dynamical Systems for Pathway Identification from Metabolic Profiles Bioinformatics 2004 20 11 1670 1681 30 Weston AD Hood L Systems biology proteomics and the future of health care toward predictive preventative and personalized medicine Journal Proteome Research 2004 3 2 179 196 31 Mathworks Inc http www mathworks com 32 FreeMat http freemat sourceforge net 33 Octave http www octave org http ntu Page 11 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 http www biomedcentral com 1471 2105 7 139 34 Euler Software http mathsrv ku eichstaett de MGF homes grothmann euler 35 Scilab http www scilab org
5. remote machines The information returned includes CPU idle time amount of available memory and processor speed Based on the results returned by each worker the work load of each worker is accurately updated If a worker becomes unavailable then all three of the above resources are set to zero and that particular worker will no longer be considered for incoming requests Also after a particu lar server assigns a job to a worker the workload informa tion stored on that master server is updated by incrementing the record of the worker s workload by a constant load percentage A load percentage of 15 empirically found to be sufficient for the purpose of stati cally estimating the expected workload increase on that computer and thus making it no longer the least busy worker Page 4 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 The basic call to mGrid is mediated by the function geval global evaluation that selects a main master server from a list of two candidate mGrid master server machines A message is then sent to the chosen master server request ing the IP address of the current best available worker known Upon receiving the IP address of the best available worker geval packs all the information necessary for the command to execute successfully on the remote machine e converts this command to a string encoded in a format appropriate for use within a Unified Resource Locator URL
6. requirements are overly complicated and have decided to implement a simpler solution using PHP 25 and hyper text transfer protocol HTTP A second feature of mGrid is support for parallel remote Matlab command execution Thus mGrid includes the ability to distribute computations in parallel although in a basic sense i e what is commonly called embarrass ingly parallel computations 23 In the code distribution by mGrid this is achieved by coarse grained paralleliza tion at the function level The specific goal of this research was to advance the auto matic distribution of algorithms written in Matlab by developing a library for distributed computing on blade servers at the Bioinformatics Core of the NHLBI Proteom ics Center at MUSC The original motivation was to speed the reverse engineering of biological networks using S Sys tems 26 27 by allowing numerical decoupling of the ensuing system of coupled differential equations 28 29 The bioinformatics justification and likely usefulness of the code distribution scheme proposed here is a reflection Page 3 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 of the particular need to systemically integrate a variety of data and models 30 which themselves may change in structure and even in purpose over time Furthermore tackling the systems biology challenge is increasingly not just a matter of coping with large amounts and large vari ety
7. BMC Bioinformatics sion Gocco Software mGrid A load balanced distributed computing environment for the remote execution of the user defined Matlab code Yultya V Karpievitch and Jonas S Almeida Address Department of Biostatistics Bioinformatics and Epidemiology Medical University of South Carolina 135 Cannon Street Suite 303 Charleston SC 29425 USA and 2Department of Biostatistics and Applied Mathematics Dept Biostatistics and Applied Mathematics Univ Texas MDAnderson Cancer Center unit 447 1515 Holcombe Blvd Houston TX 77030 4009 USA USA Email Yuliya V Karpievitch karpik musc edu Jonas S Almeida jalmeida mdanderson org Corresponding author Published 15 March 2006 Received 7 May 2005 BMC Bioinformatics2006 7 139 doi 10 1 186 1471 2105 7 139 Ee E EE This article is available from http www biomedcentral com 471 2105 7 139 2006Karpievitch and Almeida licensee BioMed Central Ltd This is an Open Access article distributed under the terms of the Creative Commons Attribution License http creativecommons org licenses by 2 0 which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited Abstract Background Matlab a powerful and productive language that allows for rapid prototyping modeling and simulation is widely used in computational biology Modeling and simulation of large biological systems often require more computational resourc
8. Download mGrid client toolbox 2 Start using mGrid Page 5 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 1 function s my powiaj http www biomedcentral com 1471 2105 7 139 Yo WY POV raises parameter ato power of 2 2 S a7a Wlatlab command window gt gt b gt gt c 10 tu Yo script creates structured variable wksp with fields b and c Yo le all the variables present in the current workspace 5 gt worksp B gt omd 1 r b4 2 fo gt omd 2 c squared my_pow c 5 gt params wksp wksp g 10 gt result gevalicmd params 11 result_ 1x1 struct 1x1 struct gt gt params tbox tmp o location of my pow function 0 to add the variables created on remote machines to the local Yo workspace run script q2 uworksp So Unpack workspace see bellow 13 r 4 14 c squared 100 Figure 2 Code example A client constructs proper parameters to the geval procedure and executes it Upon receiving the results cli ent unpacks resulting variables into the local workspace The toolbox comes with a text file masterservers listing the IP addresses of the two mGrid servers the main machine and its backup see Implementation section available to that user This text file can be generated by the system manager and made available to the users as a separate download or the user can edit its contents to include the correct IP a
9. able worker from the worker workload information file rectangle and returns it to the client The worker workload file is updated periodically by a crontab job which polls the necessary information form the workers Each new worker outside the Master rectangle on the right willing to participate in mGrid executes a volunteer command which calls a PHP script on the master node going through Apache to update the workers workload file Note that if a given worker is already registered with this master the request will simply be ignored If a worker is new then before add ing it to the list the master will request the workload information from the potential worker and only upon successful receipt of the workload information which verifies that the worker responds to the HTTP requests will this volunteering computer be added to the pool of workers Page 8 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 system and the Apache web server Equivalent versions for other combinations of other operating system web server should be straight forward The automatic configuration consists of three easy steps 1 Download the mGrid Master Server Toolbox 2 Execute the masterconfig script Upon completion the Matlab function todoprocessor will be running as a back ground process At this time the master is ready to issue IP addresses for the best available workers 3 Execute the volunteer command from Ma
10. arallel applications can now be done with a single easy to use Matlab command Because mGrid utilizes only Matlab light weight PHP scripts and the Apache web server installation and configuration are very simple Moreover the web based infrastructure of mGrid allows for it to be easily extensible over the Internet Background and engineering 1 Today Grids seek to provide seam The term grid was coined in the mid 1990s and desig less scalable high performance and secure mechanisms nates distributed computing infrastructures for science for locating and negotiating access to remote and possibly Page 1 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 heterogeneous resources 2 3 The specific goal underly ing the Grid concept is coordinated resource sharing and problem solving in dynamic multi institutional virtual organizations 4 Computational biology applications with large memory and CPU requirements have been a significant driving force behind grid development 2 5 9 However the dis covery mode of many computational biology initiatives which favours the autonomous use of rapid prototyping environments by small groups or even individual researchers which does not bode well with the predomi nant heavier distributed computational infrastructures available In this regard it is useful to recall the context of their development and in particular the eroding distinc tion between data and c
11. d as described here with a wider range of scientific and engineering applications within and beyond Bioinformatics Although the implementa tion described is specific to the Matlab programming envi ronment it is simple enough to be readily portable to its open source publicly licensed clones such as Octave and FreeMat 32 33 and to Matlab like environments such as Euler Tela or SciLab 34 36 The remaining software components of mGrid Apache and PHP are themselves mainstream open source public license applications The future development of mGrid is hereby opened to the community by releasing it under GNU General Public License see Availability and will likely include a version for Octave and FreeMat and a graphical user interface GUI with time information and various statistics on cur rent remote executions to assist in identifying optimal load balancing schemes Some modifications to the installation scripts are also immediately anticipated to tai lor the installation to the particular design of the operat ing system for example implementing todoprocessor as a SysV Init script under Linux It is immediately apparent that the proposed implementa tion requires fast communication among participanting machines Therefore mGrid is not suitable for speeding up processes that would run in a few seconds on a single machine A more suitable scenario is the one where the execution of an algorithm takes a long time to complete t
12. ddresses for the target mGrid server installa tion Page 6 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 Client toolbox functions There are only three functions that need to be learned to use mGrid though the client toolbox consists of approxi mately twenty geval global eval procedure evaluates command s on remote machine s participating in mGrid line 10 Figure 2 worksp Matlab script packs workspace variables into one structured variable wksp line 5 Figure 2 uworksp Matlab script places fields of the structured variable result_ into workspace line 12 Figure 2 Figure 2 shows an example of using mGrid It illustrates the ease of using function geval to specify a list of com mands to be executed in parallel in this case 2 com mands If the first parameter is a cell array of commands geval will execute them in parallel Second parameter is a structures variable which allows the user to pass user defined code workspace variables and memory require ments to the grid Memory requirement allows user to specify if larger amounts of random access memory RAM is needed otherwise the CPU speed and its idle cycles will be used for deciding on the best available worker for a particular request Second parameter can be omitted or only parts of it may be specified depending on user needs Because of the simple design of mGrid the user is required to read very little docume
13. e access Anyone within the university can be an mGrid client Virtual Private Network VPN can be set up to enhance security by utilizing data tunnel ling and encryption to work over the Internet Results User defined code distribution User code distribution is the defining feature of mGrid allowing a user to provide and operate a new function or a library of functions that is not kept on the grid itself mGrid supports client functionality to pack the user s http www biomedcentral com 1471 2105 7 139 unique code and variables transfer them over a network to a remote worker machine where they are unpacked and evaluated This makes mGrid a desirable tool for scientists that write their own functions and want them to be exe cuted on one or more remote computers without having to install those functions on all of the machines partici pating in the mGrid This is a convenient and more secure feature than process distribution because it eliminates the need to require that users have permissions to install or write files on the distributed computers It also eliminates having to propagate every small user code changes to all of the machines A client can issue a command to a specific worker machine possibly passing local work space variables and functions or entire Matlab toolboxes necessary for compu tation In this basic remote evaluation mode of operation not the optimal setting as detailed later the worker machine autonomousl
14. e computers is 2 8 This speedup is slightly less then the theoretical maximum of three due to the overhead of user code transfer time and remote request assembly time Computations that can be formulated as a composition of independently computed parallel results as exemplified by the suprapositioning of Parzen kernels illustrated above often occurs in computational biology applica tions The applications typically include multiple inde pendent time consuming operations such as querying public databases non linear regression and numerical simulations Conclusion Distribution of user defined Matlab toolboxes and rapid prototyping of many coarse grained parallel applications can now be done with a single easy to use Matlab com mand The implementation is made available as a suite of Page 10 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 three Matlab toolboxes collectively described as mGrid with client master and worker implementations Multiple roles can be assigned to the same machine Because mGrid utilizes only Matlab light weight PHP scripts and Apache web server the installation and configuration are very sim ple Moreover the web based infrastructure of mGrid allows for it to be easily extensible over the Internet The implementation of mGrid is being made freely avail able under a GNU General Public License 40 where contributions for further development are invited partic ular
15. e encodes any workspace variables e encodes client toolbox geval then calls the reval procedure which is responsible for data transfer to the remote worker s and collection of the results after worker s complete the assigned jobs The task of adding the master server to the mGrid needs to be performed before any other components are installed as both client and worker installations require the address of two master servers to which they relay their requests and accept reassignments to worker machines On the contrary as mentioned before dynamic accommodation of new participants is provided by the master servers so the constellation of worker machines available to the mas ter servers for assignment of incoming jobs can be changed at anytime without interruption of ongoing jobs or submission of new jobs Two additional functions dis tinguish master servers from the workers add_worker php and get_worker php The first function add_worker php allows a new worker machine to be added to the grid This function verifies that the worker is accessible via HTTP on top of TCP IP protocol and that it is ready to accept the remote jobs Function get_worker php is used by mGrid to provide client with the IP address es of the current best available worker s At this time mGrid does not incorporate a client control system Control is managed by the network configuration currently mGrid is located behind a university firewall preventing outsid
16. e those com mands and run time variables to be passed to the remote machines automatically This involves run time alloca tion of resources such as available CPU cycles memory and user code and data distribution A reliable file transfer capability is provided by GridFIP which could be used for transferring the necessary user code in mGrid Using GridFIP for our purposes would Page 2 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 Provide results to the client 7 a k p s _ _ en worker Y atli a a worker Figure http www biomedcentral com 1471 2105 7 139 mGrid architecture and client communication Architecture of full mGrid implementation load management and multi ple parallel remote calls are mediated by dedicated mGrid master server machines upon receipt of a global evaluation calls using command geval by client machine geval requests the IP address of the current best available worker form one of the masters then sends the job request to the worker which IP address was returned by the master For parallel evaluation geval will simply ask for multiple IP addresses and issue the job requests to multiple worker computers require the installation of both the GridFTP client on the client machines and the GridFIP server on the worker sys tems Furthermore the worker machines must also have the Globus Toolkit installed The authors believe that these installation
17. es then are available on a single computer Existing distributed computing environments like the Distributed Computing Toolbox MatlabMPI Matlab G and others allow for the remote and possibly parallel execution of Matlab commands with varying support for features like an easy to use application programming interface load balanced utilization of resources extensibility over the wide area network and minimal system administration skill requirements However all of these environments require some level of access to participating machines to manually distribute the user defined libraries that the remote call may invoke Results mGrid augments the usual process distribution seen in other similar distributed systems by adding facilities for user code distribution mGrid s client side interface is an easy to use native Matlab toolbox that transparently executes user defined code on remote machines i e the user is unaware that the code is executing somewhere else Run time variables are automatically packed and distributed with the user defined code and automated load balancing of remote resources enables smooth concurrent execution mGrid is an open source environment Apart from the programming language itself all other components are also open source freely available tools light weight PHP scripts and the Apache web server Conclusion Transparent load balanced distribution of user defined Matlab toolboxes and rapid prototyping of many simple p
18. etSolve http icl cs utk edu netsolve index html 7 Globus Toolkit http www globus org toolkit 8 9 l https sourceforge net projects North Carolina BioGrid http www ncbiogrid org caBIG https cabig nci nih gov 0 Kakazu KK Cheung LW Lynne W The Cancer Biomedical Informatics Grid caBIG pioneering an expansive network of information and tools for collaborative cancer research Hawaii Medical Journal 2004 63 9 273 275 Il Stevens RD Robinson AJ Goble CA myGrid personalised bioin formatics on the information grid Bioinformatics 2003 19 90001 302i 304 12 Stevens RD Tipney HJ Wroe CJ Oinn TM Senger M Lord PW Goble CA Brass A Tassabehji M Exploring Williams Beuren syndrome using myGrid Bioinformatics 2004 20 suppl_1 i303 3 10 13 Gilat A Matlab an Introduction with Applications Wiley 2003 14 MatlabMPI http www Ilmit edu MatlabMPI 15 Distributed Computing Toolbox http www mathworks com products distribtb 16 Parallel Matlab Survey http supertech Ics mit edu cly sur vey html I7 MultiMATLAB http www cs cornell edu Info People Int multi matlab html 18 MATLAB G A Grid Based Parallel Matlab cg ntu edu sg Grid_competition report grid 9 pdf 19 Menon V TA MultiMatlab integrating MATLAB with high performance parallel computing 1997 20 Message Passing Interface http www mpi forum org 2I Parallel Virtual Machine http www csm ornl gov
19. for that choice of OS and web server However both Apache and PHP are widely available in equally open source and freely distrib uted implementations for other operating systems Simi larly porting the automatic configuration scripts for other web servers should be straight forward Authors contributions YVK performed software development design coding testing debugging and elaboration of manuscript JSA developed the original concept and drafted the imple mentation layout Acknowledgements This work was partially supported by the NHLBI Proteomics Initiative through contract NOI HV 28181 http proteomics musc edu and by the http www biomedcentral com 1471 2105 7 139 training grant 1 T15 LM07438 01 training of toolmakers for Biomedical Informatics of the National Library of Medicine of the National Institutes of Health USA NLM NIH http www nim nih gov ep T 15 Training html The authors thank Anthony Leclerc Ph D for revising the paper and pro viding technical advice and Chuming Chen for assisting in configuration of computers References Foster KC The Grid Blueprint for a new Computing Infra structure Morgan Kaufmann Publishers 1999 2 MALICE Grid Computing Project http www comp nus edu sg teoym alice htm 3 mGrid project homepage mgrid 4 Berman F FGHA Grid Computing Making the Global Infra structure a Reality Wiley 2003 5 Folding Home http folding stanford edu 6 N
20. hus justifying the migration of the libraries to different computers Figure 4 displays the execution time for the identification of the density distribution using Parzen ker nels for different sizes of the resulting matrix mGrid was used to distribute this computation among two and later among three computers The results were compared with a sample run where no distribution was used at all Parzen kernels superimpose Gaussian hat distributions to determine the density distribution for a scatter plot This is a very convenient alternative to discretizing the scale and representing the histogram of frequencies The com Page 9 of 12 page number not for citation purposes BMC Bioinformatics 2006 7 139 ho So So m on So So ane ce gi kinoni ce E _ o _ d Pi Lu 20x20 50x50 100x100 http www biomedcentral com 1471 2105 7 139 worker s workers a 3 workers 150x150 200x200 Matrix Size Figure 4 Execution time comparison of Parzen kernels superpositioning algorithm on one two and three computers The Parzen kernel is applied to a replicate series of microarrays to identify a reference conditional cumulative distribution to access Statistical significance of observed differential expression The number of possible comparisons in a replicate series with N genes and M arrays is NM I thus the computation can be quite time consuming The number of kernel evaluations
21. is also dependent on the dimension of the resulting matrix K of the conditional distribution The number of kernel evaluations would therefore be K2 N M I The speedup gained by using mGrid and separating the task into three independent subtasks for larger matrices 150 x 150 or 200 x 200 is 2 8 This is considered excellent as the maximum theoretical execution time spee dup possible is 3 As the problem size increases the data transfer time becomes relatively insignificant putation of this kernel consists of centering a Gaussian hat on each available point in the scatter plot Each indi vidual hat has unitary volume so the superimposed dis tribution can simply be divided by the number of points to get a unitary density distribution The illustration described here applies the Parzen kernel to a replicate series of microarrays with the purpose of identifying a ref erence conditional cumulative distribution to access the statistical significance of observed differential expression The rationale for this empirical solution to statistical modeling was recently illustrated by one of the authors for a proteomics dataset 39 The superimposition of Gaus sian hats is an additive procedure that can be independ ently computed in parallel As can be seen from figure 4 even computations that take several minutes to complete can benefit greatly from using mGrid In this case the speedup in execution time of the parallel algorithm on thre
22. iverse service grid Although the above implementations are excellent examples of the working bioinformatics grids their scope is far beyond the scope of the solution proposed in this report and most importantly none of these grids allow for distribution of user defined libraries on remote machines at runtime which is the main goal of mGrid Matlab is a particularly popular computing environment for rapid prototyping 13 The potential advantages of building a distributed computing capability in Matlab http www biomedcentral com 1471 2105 7 139 were reflected by the development of over twenty infra structures to distribute and or parallelize Matlab 14 19 Some examples are MultiMatlab MatlabMPI MAT LAB G Distributed Computing Toolbox Most of the existing tools require an underlying parallel library or lan guage such as Message Passing Interface MPI 20 Par allel Virtual Machine PVM 21 or a communication technology like Jini 22 or ALICE 2 The installation and configuration of such environments often require a signif icant level of system administration knowledge and makes systems less secure Also message passing and shared memory tools are designed to work best on a local area network LAN for example on a cluster of machines These tools are not easily extensible to span across large heterogeneous wide area networks WANs such as the Internet 23 24 Moreover none of these environments allow for distributi
23. ly in regards to developing a version that relies entirely on public license components A particular note regarding copyright issues is warranted for implementations relying on Mathworks Inc Matlab environment 31 The proto type described here relies on a set of machines served by the same concurrent license manager For more distrib uted implementations attention should be paid to the details of the particular license agreement associated with the purchase In that regard porting the implementation to Octave FreeMat or porting the code distribution envi ronment to support other advanced programming lan guages such as Python may be an alternative worth exploring Considering the fact that all the communica tion is done via PHP scripts modifications to accommo date more languages will be minimal Availability and requirements The client worker and master mGrid toolboxes are made freely available with open source at http source forge net projects mgrid The code distribution toolbox was developed and tested for Matlab version 8 release 14 PHP 4 and Apache HTTP Web Server version 2 0 40 The client side toolbox dis tributed is Operating system independent and uses only native functions of Matlab itself available for Linux Sola ris Windows and MacOS 31 The worker and master server toolboxes were developed for Linux OS Accord ingly the automatic configuration scripts for those two toolboxes are only guaranteed to work
24. me is true for the other components of mGrid Apache web server package and its PHP module Therefore the grid comput ing implementation described here is truly platform inde pendent Finally this is also the environment of choice for training in scientific computing and computational statis tics in academia Connectivity At the heart of every Grid is a network that links together distributed resources It is important to note that mGrid uses the standard HTTP protocol which runs on top of TCP IP which facilitates interoperability extensibility and portability of the software TCP IP also provides reli able delivery of the data as it automatically detects errors and requests retransmission until all data is received mGrid uses the Apache web server 38 to establish com munication with contributing computers and PHP 25 to structure the data transferred between participating com puters http www biomedcentral com 1471 2105 7 139 mGrid architecture The full mGrid implementation includes dedicated medi ating server machines to manage the client requests and select the best available workers following a semi hierar chical architecture Figure 1 This architecture consists of two master servers main and backup master servers that can independently decide which worker to send a given request to based on user requirements for CPU speed available RAM and workload The master servers are defined as a redundant set of two
25. ng computer to the list of the available workers if that computer is able to respond to the request for the workload information Discussion This paper presents an easy to use configurable distrib uted system that allows for parallel Matlab user code dis tribution The main objective was to allow users to execute exclusive Matlab code possibly in parallel on a remote perhaps more powerful machines with minimal learning curve To use mGrid the user familiar with the simple Matlab programming language only needs to learn a sin gle new command the global eval procedure geval http www biomedcentral com 1471 2105 7 139 described in this paper The implementation which is based on two redundant master servers that hand down the jobs submitted to a fluid set of worker machines Fig ure 1 further contributes to the user not having to be at all aware about the resources recruited to support distrib uted execution Furthermore committing new workers to mGrid is like the code distribution itself entirely web based and automated through the execution of a single automatic command Although the initial specific motivation for the develop ment of mGrid was to assist in experimenting with paral lelizing data collocation schemes for numerical decoupling of systems of differential equations describing metabolic networks the use of code distribution was found to have a more general applicability Consequently mGrid was develope
26. ntation in order to begin writing parallel Matlab computations Therefore the user manual is minimal Return variables After the completion of a geval procedure one structured variable result_ is returned to the client with the new var iables or new values of original variables The return value should be assigned to the variable result_ if the use of the script uworksp to automatically unpack the values to the client s local workspace is desired Server side of mGrid The configuration of an mGrid facility requires the config uration of master server and worker machines Both are fairly simple to follow The worker configuration in partic ular is designed to be accessible to the average Matlab user wanting to contribute a machine to a local mGrid infra structure This requires minimal system administration expertise At this time automated server side installers are only provided for Linux machines Client side is platform independent A worker can be a client of mGrid at the same time http www biomedcentral com 1471 2105 7 139 Adding a worker to the mGrid To ensure that mGrid can dynamically accommodate new participants across different platforms the worker side toolbox includes a function to mediate volunteering their CPU cycles any computer with a copy of Matlab and a web server can be made a worker without interruption or reconfiguration of ongoing processes The automatic con figuration of a new worker consists of th
27. of data and applications but also of testing alternative theoretical foundations Consequently the challenge that mGrid seeks to address is the creation of a user friendly programming environment tailored to rapid prototyping such that algorithm and theory development could share a common programming environment Implementation The m in mGrid The letter m in mGrid refers to Matlab a programming environment by Mathworks Inc 31 the implementa tion language of the mGrid software and also the language of the code being distributed The choice of Matlab to implement code distribution is a reflection of its popular ity for rapid prototyping of scientific and engineering applications The combination of user friendliness and support for high end applications makes it a natural choice for the implementation of grid computing through code distribution Nevertheless it should also be noted that Matlab is a commercial product witch raises a cost barrier to access and scaling up the proposed implemen tation Nevertheless there are free open source Matlab like tools available Octave FreeMat SciLab Tela Euler 32 37 onto which the implementation described here can be easily ported Other then the language itself this is an open source freely distributed tool see Availability Matlab was chosen for being the most complete of these environments and for the availability of implementations for all the major operating systems The sa
28. omputational grids Some grid middleware has evolved to bind data resources scattered across a network into a unified environment to make it appear to the user as if all the data is stored locally on that user s desktop data grids Computational grids on the other hand provide the ability to perform compu tations remotely possibly in parallel without the user having to know anything about networking and commu nication between the computers distribution transpar ency Majority of grids today act as both data and computational grids 6 9 Particularly illustrative examples of working grid systems for computational biology are Folding home North Carolina BioGrid caBig and myGrid The goal of Fold ing home is understanding protein folding protein aggregation and related diseases by utilizing idle CPU cycles i e computational grid over a collection of com puters 5 NC BioGrid combines computing and data resources into a unified environment for genomic research data and computational grid 8 caBig is the cancer Biomedical Informatics Grid it is made up of net work of individuals and institutions to enable the sharing of data and tools for cancer research 9 10 Another example of the grid that is being used in bioinformatics is myGrid 11 12 myGrid is an infrastructure specifically designed to support biological applications It provides access to analysis tools computations or database serv ices thus making it a d
29. on of user defined Matlab libraries It is noteworthy that our method relying on code distribu tion is not proposed in strict alternative to message pass ing Quite the opposite there is no fundamental reason why they cannot be mixed Some environments only allow for coarse grained paral lelization i e at the functional level or only paralleliza tion of matrix operations and for loops 15 18 For example the Distributed Computing Toolbox 15 is a Matlab native toolbox that enables users to execute inde pendent parallel algorithms on a set of machines simulta neously This library which works together with the Distributed Computing Engine requires Jini technology to facilitate communication between computers that com prise a distributed computing environment Jini is a Java based software and thus requires installation of the Java specific runtime environment and Jini servers on all machines Once again the Distributed Computing Tool box does not allow for the dynamic distribution of the user code The differentiating characteristic of mGrid is indeed user code distribution While this report focuses on a proof of concept of Matlab implementation of code distribution the concept itself is general and can be embedded in other programming environments mGrid allows unique user code to be dynamically migrated to heterogeneous com puters i e it allows for user defined Matlab commands and libraries of functions needed to execut
30. ree easy steps 1 Download the mGrid Worker Toolbox 2 Execute the workerconfig script Upon completion the Matlab function todoprocessor will be running as a back ground process 3 Execute the volunteer command from Matlab upon completion check for either an error or success message displayed Once a success message is displayed the worker system is ready to accept remote jobs A script for automatic Apache web server configuration is available for Linux computers The script is geared towards the default installation and configuration of Apache If some user modifications are present the script may not be able to perform all of its tasks The user then will have to make sure that Apache is running and is able to access users public_html directories manually A todopr is a startup script that is added to the list of jobs started upon boot up of the computer to automate the process of restarting todoprocessor in case of a shutdown or reboot of the machine todoprocessor can also be stopped started and restarted manually by executing the todopr shell script manually with proper arguments Worker toolbox functions There are two important functions in the worker toolbox volunteer requests that the current computer be added to the workers pool on the master servers This function should be executed after the installation of the toolbox todoprocessor executes commands that arrive from remote machines See display
31. tlab upon completion check for the display of either an error or suc cess message When a success message is displayed the worker component of the system is ready to accept remote jobs The masterconfig script is built on top of the workerconfig and has additional functionality necessary for the master server configuration Thus any master server has the full functionality of the worker and is added to the pool of worker machines by the volunteer command If a master is not intended to participate also as a worker then step 3 should be omitted A master can also be removed from the pool of workers at any time by manually removing its IP address from the workers file and stopping the todoproc essor by executing the todopr script with the option stop todopr stop Figure 3 shows communication between processes on a master server and communication of the master server with the other machines Apache web server accepts the requests from the clients executing geval a PHP script on the master looks up the workers information in the work ers workload files and provides the IP address of the best available worker machine to the client which sends its request directly to that worker Best available worker is determined as a combination of the available CPU cycles CPU speed and available memory Computers willing to bea part of the mGrid execute volunteer command which goes through the Apache to the PHP script which adds the volunteeri
32. y handles the request makes results available to the client and then removes the client code from its hard drive following a standard client server model 24 mGrid automatically handles the entire process such that user specification of parallel execution does not depend on the code unlike other parallel envi ronments like MPI or PVM 20 21 23 that require users to learn a parallel programming language in order to write code that can be run in parallel mGrid provides a fully parallel configuration where the user simply has to list the multiple commands to be exe cuted in an array Both the selection of worker machines and code distribution are automatically mediated by mGrid Of course for parallel execution the multiple Matlab commands given by the user have to be independ ent of each other 23 Client side of mGrid In order to access an existing mGrid infrastructure a potential client needs only to have a small Matlab toolbox and learn how to use three new commands As any other Matlab function these functions can be inserted any where into other scripts and functions in order to have the corresponding input argument command expression eval uated by mGrid Using mGrid From the user s perspective the toolbox is simple to install just download and use It runs on Windows Mac intosh and Linux systems Clients wanting to utilize mGrid on a computer with a current copy of Matlab must perform the following steps 1
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