SAGA: A Simple API for Grid Applications High-Level Application ...

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8 COMPUTATIONAL METHODS IN SCIENCE AND TECHNOLOGYalso be queried for its current state, error conditions etc. Inputand output data files and streams are, if required, defined inthe job description.In order to further simplify the job submission, a job servicealso offers a job run method, which requires only the essentialjob information to be given, and creates the job descriptioninternally. The call returns the standard input, output and errorstreams for the remotely run job. The code example in Figure 6illustrated the usage of the job run method in Perl.Fig. 6. Code Example: Start a remote /bin/date, and retrieve output (justfor a change, that example is given in Perl)#!/usr/bin/perl -wBEGIN {use strict;use saga;}eval {# create job servicemy $js = new saga::job_service ();# and submit a jobmy ($job, IN, OUT, ERR)= $js.runJob ("ssh.university.edu","/bin/date");# print any job outputwhile ( $job.getJobState () !˜ /ˆDone/io ){print STDOUT ;print STDERR ;}# status is ’Done’ here};# catch all saga exceptionif ( $@ =˜ /ˆsaga/io ){die "saga error: $@\n";}2) Tasks: To manage the potentially large latencies ingrid environments, SAGA introduces an asynchronous Taskmodel. For each synchronous method call (e.g. file.read(target)), that model introduces a asynchronous counterpart(file.asynch.copy (target)). That asynchronousmethod call returns a saga::task object, whichoffers methods to watch the state and progress of the operation,and to cancel it if required. The code example in Figure 7shows the SAGA task model applied to a remote mkdiroperation 3 .The SAGA Task Model does also include a container classfor tasks, which allows to handle large numbers of task objectsefficiently (e.g. wait for all of them to complete). There areconsiderations to extend that task model by allowing to havedependencies between tasks, and so to effectively introduceworkflow, but we consider such extensions to be out of scopefor SAGA for now.3 It must be noted that the SAGA Task Model is currently under discussion,and might change to some extend (without loss of functionality). So theexample given here should be considered very preliminary.Fig. 7. Code Example: asynchronous version of the remote mkdir example:This example should be compared to the synchronous version in Figure 3.#include #include void sample_async_mkdir (){try{// open a remote directorysaga::directory d("gsiftp://ftp.host.net/pub/");// create a mkdir tasksaga::task t = d.async.mkdir ("data/");// showing the task stateif ( saga::task::Running == t.get_state () ){std::cout
SAGA ET AL.: THE SIMPLE API FOR GRID APPLICATIONS 9Fig. 8.Code Example: Create a streaming clientFig. 9.Code Example: Potential RPC representation in SAGA#include int main (int argc, char** argv){// create stream to server contact in argv[1]saga::stream s (argv[1]);}// open the connections.connect ();// message to write in argv[2]s.write (argv[2]);// the stream gets destroyed at and of scope,// connection is closed in destructorE. Possible SAGA Extensions (Future Work)As described above, the current scope of the SAGA APIspecification is intentionally very limited, and drawn from afinite set of use cases. However, the SAGA-WG has receiveda number of requests to widen the scope of the API, and anumber of additional use cases for the respective areas havebeen submitted. SAGA is intended to follow up with theserequests in future versions of the specification. This sectionallows the reader a glimpse of the SAGA future, and describesthese extensions. It must be noted though that all materialdescribed here is very preliminary, and represents by no meansany part of the current SAGA specification.1) Monitoring and Steering: The ability to monitor remoteapplications (and in fact any remote grid resource) is integralpart of a number of received use cases. SAGA currently onlyallows polling of specific monitorables, such as the state ofjobs and tasks. Application level monitoring and steering iscurrently not supported. A number of use cases have beensubmitted to the group though, which require monitoring andsteering, in particular in the context of visualization.The UK-eScience project ‘RealityGrid’ [5] designed andimplemented a grid monitoring and steering infrastructure[36]. The RealityGrid Steering API has been used acrossa wide range of different scientific applications — rangingfrom classical molecular dynamics, lattice-Boltzmann simulationsand Monte-Carlo simulations of polymers — providingtestimony to its flexibility and breadth. Together withthe monitoring capabilities of GAT (which derive from themonitoring package Mercury [37]), the RealityGrid API willprobably form the basic input for a future SAGA monitoringand steering API.2) Remote Procedure Calls: As described in section III, theGridRPC Working Group in GGF defined another applicationoriented API, which provides Remote Procedure Calls (RPCs)in grid environments. The GridRPC-WG and the SAGA-WGstarted to actively pursue the integration of GridRPC intoSAGA. That would provide a consistent look & feel for bothAPIs, and provide grid application programmers with a morecomplete and more consistent set of programming paradigms.An example for the current candidate API extension is shownin Figure 9.#include #include #include void sample_rpc (){try{// initialize rpc function handlesaga::rpc handle("gridrpc://remote.host.net/bin_date");// initialize in/out argument stackstd::list stack;// call the remote functionhandle.call (stack);std::cout
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