This document looks at some possibilities of extending version 1.0 of the KNSG Architecture to include semantic technologies that will improve the framework. KNSG is a non-domain specific application framework that is built upon Bard, PTPFlow, and MyProxy for setting up, launching and managing HPC application workflows through an easy to use set of user interfaces. This document is intended to lay the foundation of the core components and views provided by the KNSG version 2.0 application framework and inform users how they can extend the various parts for their domain specific application.
The central management piece for each KNSG application is KNSGFrame, an extension of BardFrame that registers tupelo utility methods for CETBeans used by the KNSG framework. In this document, we will will use the name BardFrame since our extension only overrides the method for registering beans, the rest is the same. BardFrame provides an interface for working with the Tupelo semantic content repository and is responsible for managing contexts, bean sessions, data, etc. The use of beans will be a core concept for persisting information in the KNSG framework so all beans will need to descend from CETBean. Because every application will have its own bean requirements, each KNSG application should have its own instance of BardFrame to handle this as well as an ontology to define domain specific concepts. All application bean types should register with BardFrame and the IBardFrameService should provide the correct instance of BardFrame at runtime.
These are the bean classes that will be required for the KNSG framework. Where possible, the core CETBeans will be used to minimize the work required and maximize compatibility across projects. Some beans will be marked optional if they are part of PTPFlow and it is uncertain that they will be managed by Tupelo or continue to be managed by PTPFlow's current repository.
A scenario bean will be used to organize things such as user data and workflows specific to a scenario (or project). This will include datasets (input and output), workflows, and possibly the RMI service for launching jobs. A snippet of what the scenario bean might look like is below:
private String title; // scenario title private String description; // scenario description private Date date = new Date(); // date scenario created private PersonBean creator; // scenario creator private Set<DatasetBean> dataSets; // datasets associated with scenario private List<WorkflowBean> workflows; // workflows associated with this scenario, if possible, this needs to be able to wrap ptpflow workflow xml files, or we need our own bean type |
This scenario bean will evolve as the application framework is built and more final documentation will be put here as the design matures. The main parts of this bean are: DatasetBean's will be used to manage all of the input/output datasets and the WorkflowBean List will contain the workflows associated with this scenario. A user might extend the ScenarioBean if their application has other things that logically belong to their scenarios, but this is unlikely. Most changes will happen at the metadata level (e.g. this dataset is a mesh, a result, etc).
This section is intended to talk about the types of concepts that the Ontology needs to capture. We will break this into two parts: general framework concepts (e.g. result) and eAIRS specific (e.g. mesh). We don't anticipate any changes to the DatasetBean class that is provided as part edu.uiuc.ncsa.cet.bean plug-in.
Below you will find an example of a PTPFlow workflow.xml file. This file cannot be altered since it is understood by PTPFlow and outlines the steps in the workflow including which resource to run on, executables that will be launched, input files to use, etc. Ideally, this file would be wrapped into the current WorkflowBean and/or WorkflowStepBean in the edu.uiuc.ncsa.cet.bean plug-in. If this is not possible, the KNSG framework will need its own workflow bean.
<workflow-builder name="eAIRS-Single" experimentId="singleCFDWorkflow" eventLevel="DEBUG"> <!-- <global-resource>grid-abe.ncsa.teragrid.org</global-resource> --> <global-resource></global-resource> <scheduling> <profile name="batch"> <property name="submissionType"> <value>batch</value> </property> </profile> </scheduling> <execution> <profile name="mesh0"> <property name="RESULT_LOC"> <value>some-file-uri</value> </property> <property name="executable"> <value>some-file-uri</value> </property> <property name="meshType"> <value>some-file-uri</value> </property> <property name="inputParam"> <value>some-file-uri</value> </property> </profile> </execution> <graph> <execute name="compute0"> <scheduler-constraints>batch</scheduler-constraints> <execute-profiles>mesh0</execute-profiles> <payload>2DComp</payload> </execute> </graph> <scripts> <payload name="2DComp" type="elf"> <elf> <serial-scripts> <ogrescript> <echo message="Result location = file:${RESULT_LOC}/${service.job.name} result directory is file:${runtime.dir}/result, copy target is file:${RESULT_LOC}/${service.job.name}"/> <simple-process execution-dir="${runtime.dir}" out-file="cfd.out" > <command-line>${executable} -mesh ${meshType} -param ${inputParam}</command-line> <!-- <command-line>${runtime.dir}/2D_Comp-2.0 -mesh ${meshType} -param ${inputParam}</command-line> --> </simple-process> <mkdir> <uri>file:${RESULT_LOC}/${service.job.name}</uri> </mkdir> <copy sourceDir="file:${runtime.dir}/result" target="file:${RESULT_LOC}/${service.job.name}"/> </ogrescript> </serial-scripts> </elf> </payload> </scripts> </workflow-builder> |
The information about each service installation will be stored in an RMIServiceBean and will be used to launch and start the service. All of this information is currently used in PTPFlow and is stored in xml files. Bringing in tupelo to the service stack will allow us to store this information in tupelo.
// Service Info private String name; private String platform; private String deployUsingURI; // e.g. file:/ private String launchUsingURI; private String installLocation; // e.g. /home/user_home/ptpflow private String rmiContactURI; private int rmiPortLowerBound; private int rmiPortUpperBound; private int gridftpPortLowerBound; private int gridftpPortUpperBound; private Date installedDate; private boolean running; private Set<HostResourceBean> knownHosts; // all of the known hosts associated with this service |
Below is the bean structure that is anticipated:
A HostResourceBean defines the hpc host and its properties.
private String osName; // host os name private String osVersion; // host os version private String architecture; // host architecture private String id; // host id private Set<PropertyBean> envProperties; // environment properties on host private Set<NodeBean> nodes; // properties of each node private Set<UserPropertyBean> users; // user properties on the host - userHome, userNameOnHost, userName |
A NodeBean defines an HPC nodes properties such as the protocols used and nodeId.
private String nodeId; // id of the node, e.g. grid-abe.ncsa.teragrid.org private List<FileProtocolBean> fileProtocols; private List<BatchProtocolBean> batchProtocols; private List<InteractiveProtocolBean> interactiveProtocols; |
A UserPropertyBean defines the users properties on the host
private String userHome; private String userName; private String userNameOnHost; |
What we need to capture:
What we need to capture:
Mime types of the files that are outputs from the eAIRS workflow
A primary view provided by the KNSG framework will be the ScenariosView that displays user scenario(s) and all sub-parts (most likely in some kinda of Tree viewer). A scenario is similar to the concept of a project and is simply a way of organizing things that belong together. The scenario is responsible for managing all of the pieces that it contains including input datasets, output datasets and workflows. Users will be able to launch jobs on available HPC machines through an RMI Service (provided by PTPFlow) that use the inputs in their scenario and when a project completes, the outputs should be added back to that scenario, possibly through a thread that is polling the Tupelo server for new data). A user can have multiple scenarios open at once, close scenarios, or even delete scenarios from their scenario view (deleted from the view, but still in the repository) so we'll need to manage which scenarios are in a session and possibly what is their current state (open/closed). It is anticipated that new applications might extend this view to organize their view differently for their specific domain (e.g. use different icons, possibly organize data into different categories, etc).
This view shows all of the machines defined as available to the user for installing the RMI service and PTPFlow plugins required to run HPC jobs and return status information to the client. Below you will see a partial specification for what an RMI Service stored as a tupelo bean might look like. This is not a requirement for version 2.0.
This view will display the datasets that are stored in the tupelo context that the system is connected to. Users should be able to import/export datasets from this view, tag datasets, etc.
Rather than a single repository view, this will be multiple views that are configured to show a particular type of bean(s) coming from a content provider. The content provider would get the data required from the configured tupelo context(s). For example, we will need a "Dataset Repository View" that shows all datasets (e.g. input/output datasets) and a way to manipulate them (e.g. add tags, annotations, etc), "Workflow Repository View" that shows all imported workflows, "Scenario Repository View" that shows all saved scenarios, "Service Repository View" that shows defined RMI service endpoints for launching jobs, and a "Known Hosts View" for showing known hosts that can accept jobs. This seems like too much disparate information to display in a single view. All Repository views will descend from BardFrameView since the BardFrame will be required to get the data required for each view.
Functional Requirements
This view will display the workflows that have been run and the parameters they were ran with (possibly for re-running a workflow).
Functional Requirements
This view will provide general information about what is selected (e.g. a scenario, a dataset, etc). It will display things like who the creator was, date created, etc. If possible, it will provide a preview of what is selected (e.g. a dataset).
View for working with tags. It will display all tags associated with the current selection and allow users to manage the tags.
This view contains a list of defined HPC hosts that the user can launch jobs on. This view will provide the user with the ability to change/view/add properties such as environment settings, user information for the host (username, user home, etc), host operating system, node properties, new hosts, etc. These changes should be propogated to the defined RMI services so they can be used immediately.
The analysis framework will allow users to register HPC workflows, modify the workflow inputs through a graphical user interface, and execute HPC jobs when all inputs are satisfied.