Ganga: a User-Grid Interface for ATLAS and LHCb Motivation and background Objectives and design Low-level tools High-level tools and GUI Future plans and conclusions K. Harrison, P. Mato, A. Soroko and C. Tull

25/03/2003CHEP 2003, La Jolla, California 2 Motivation and background ATLAS and LHCb develop applications within a common framework: Gaudi/Athena Both collaborations aim to exploit potential of Grid for large-scale, data-intensive distributed computing ATLAS and LHCb develop applications within a common framework: Gaudi/Athena Both collaborations aim to exploit potential of Grid for large-scale, data-intensive distributed computing Simplify management of analysis and production jobs for end- user physicists by developing tools for accessing Grid services with built-in knowledge of how Gaudi/Athena works: Gaudi/Athena and Grid Alliance (GANGA) Generic tools interfacing to the Grid can be used at other experiments. Simplify management of analysis and production jobs for end- user physicists by developing tools for accessing Grid services with built-in knowledge of how Gaudi/Athena works: Gaudi/Athena and Grid Alliance (GANGA) Generic tools interfacing to the Grid can be used at other experiments.

25/03/2003CHEP 2003, La Jolla, California 3 Athena/GAUDI GANGA GUI JobOptions Algorithms Collective & Resource Grid Services Histograms Monitoring Results First ideas for GANGA were presented in summer 2001 (P.Mato and C.Tull) An Atlas/LHCb design team was set up, including US representatives Motivation and background

25/03/2003CHEP 2003, La Jolla, California 4 Objectives and design The user interacts with a single application integrating all stages of job life-time. Modular design. Each module can be accessed via Python interface or is entirely written in Python. Although Atlas and LHCb use the same framework and the same software management tool, there are significant differences in what is expected from the software, and Ganga must have the flexibility to cope. Ganga provides a set of tools to manipulate jobs and data. Tools are accessible from CLI (other scripts) or from GUI. Ganga allows access both to the local resources (LSF batch system) and to the GRID. Should follow, and contribute to, developments in LCG. The user interacts with a single application integrating all stages of job life-time. Modular design. Each module can be accessed via Python interface or is entirely written in Python. Although Atlas and LHCb use the same framework and the same software management tool, there are significant differences in what is expected from the software, and Ganga must have the flexibility to cope. Ganga provides a set of tools to manipulate jobs and data. Tools are accessible from CLI (other scripts) or from GUI. Ganga allows access both to the local resources (LSF batch system) and to the GRID. Should follow, and contribute to, developments in LCG.

25/03/2003CHEP 2003, La Jolla, California 5 Required Functionality Job preparation and configuration Resource booking Job submission User can choose between Grid and local resource management system Job monitoring and control GUI for the resource browsing VO active services CEs SEs Query existing files in the Grid GUI for data management tools e.g., Dataset registration to the Grid (used by Production Manager) Copy file from a Computing Element to a Storage Element Replication of files Job preparation and configuration Resource booking Job submission User can choose between Grid and local resource management system Job monitoring and control GUI for the resource browsing VO active services CEs SEs Query existing files in the Grid GUI for data management tools e.g., Dataset registration to the Grid (used by Production Manager) Copy file from a Computing Element to a Storage Element Replication of files

25/03/2003CHEP 2003, La Jolla, California 6 Athena/Gaudi Architecture Converter Algorithm Event Data Service Persistency Service Data Files Algorithm Transient Event Store Detec. Data Service Persistency Service Data Files Transient Detector Store Message Service JobOptions Service Particle Prop. Service Other Services Histogram Service Persistency Service Data Files Transient Histogram Store Application Manager Converter

25/03/2003CHEP 2003, La Jolla, California 7 Ganga: Python Bus Design Server Bookkeeping DB Production DB EDG UI PYTHON SW BUS XML RPC server XML RPC module GANGA Core Module OS Module Athena\ GAUDI GaudiPython PythonROOT PYTHON SW BUS GUI Job Configuration DB Remote user (client) Local Job DB LAN/WAN GRID LRMS

25/03/2003CHEP 2003, La Jolla, California 8 Class Diagram of Ganga Core Module JobHandler Requirements JobAttributes Credentials 1 1… Job JobsRegistryJobsCatalog Application GaudiApplicationHandler Configuration ConfDataBase ParameterExecutable 1 0… …

25/03/2003CHEP 2003, La Jolla, California 9 Ganga Job and Application Handlers ApplicationHandler AnotherApplicationHandler GaudiApplicationHandler DaVinchiApplicationHandler Address different types of applications JobHandler AnotherJobHandler GridJobHandler PBSJobHandlerLSFJobHandler LocalJobHandler Address different types of batch systems

25/03/2003CHEP 2003, La Jolla, California 10 Core Module Implementation Most of base classes are developed. Serialization of objects (user jobs) is implemented with the Python pickle module. GaudiApplicationHandler can access Configuration DB for some Gaudi applications (Brunel). It is implemented with the xmlrpclib module. Ganga can create user-customized Job Options files using this DB. DaVinci and AtlFast application handlers are in the last stage of development. LSFJobHandler is implemented. It allows to submit and to get simple monitoring information for a job at LSF batch system. Much of GRID-related functionality is already implemented in GridJobHandler using EDG testbed 1.4 software. Ganga can submit, monitor, and get output from GRID jobs. JobsRegistry class provides jobs monitoring via multithreaded environment based on Python threading module Most of base classes are developed. Serialization of objects (user jobs) is implemented with the Python pickle module. GaudiApplicationHandler can access Configuration DB for some Gaudi applications (Brunel). It is implemented with the xmlrpclib module. Ganga can create user-customized Job Options files using this DB. DaVinci and AtlFast application handlers are in the last stage of development. LSFJobHandler is implemented. It allows to submit and to get simple monitoring information for a job at LSF batch system. Much of GRID-related functionality is already implemented in GridJobHandler using EDG testbed 1.4 software. Ganga can submit, monitor, and get output from GRID jobs. JobsRegistry class provides jobs monitoring via multithreaded environment based on Python threading module

25/03/2003CHEP 2003, La Jolla, California 11 EDG Grid Interface Job class JobsRegistry class Job Handler class Data management service Job submission Job monitoring Security service dg-job-list-match dg-job-submit dg-job-cancel dg-job-list-match dg-job-submit dg-job-cancel grid-proxy-init MyProxy grid-proxy-init MyProxy dg-job-status dg-job-get-logging-info GRM/PROVE dg-job-status dg-job-get-logging-info GRM/PROVE edg-replica-manager dg-job-get-output globus-url-copy GDMP edg-replica-manager dg-job-get-output globus-url-copy GDMP EDG UI

25/03/2003CHEP 2003, La Jolla, California 12 Ganga: low-level tools  In Ganga, components used to define a job are mapped to Python classes.  The low-level software needs to provide representations of the most basic components, and must allow flexibility in manipulating them.  Users will have access to low-level data and methods at the command line, but in most cases shouldn’t need them  Low-level software works, but is preliminary.  Some details of component representations and their interfaces are still being discussed by development team, but most of them have already been defined.  In Ganga, components used to define a job are mapped to Python classes.  The low-level software needs to provide representations of the most basic components, and must allow flexibility in manipulating them.  Users will have access to low-level data and methods at the command line, but in most cases shouldn’t need them  Low-level software works, but is preliminary.  Some details of component representations and their interfaces are still being discussed by development team, but most of them have already been defined.

25/03/2003CHEP 2003, La Jolla, California 13 Low-level tools: Atlas example (AtlFast) atlasSetup = GangaCommand(“source /afs/cern.ch/user/h/harrison/public/atlasSetup.sh”) atlfast = GangaCMTApplication(“TestRelease”, “TestRelease ”,”athena.exe”, “run/AtlasfastOptions.txt”) atlfastOutput = GangaOutputFile(“atlfast.ntup”) workStep1 = GangaWorkStep([atlasSetup,atlfast,atlfastOutput]) workFlow = GangaWorkFlow([workStep1]) lsfJob = GangaLSFJob(“atlfastTest”,workFlow) lsfJob.build() lsfJob.run() atlasSetup = GangaCommand(“source /afs/cern.ch/user/h/harrison/public/atlasSetup.sh”) atlfast = GangaCMTApplication(“TestRelease”, “TestRelease ”,”athena.exe”, “run/AtlasfastOptions.txt”) atlfastOutput = GangaOutputFile(“atlfast.ntup”) workStep1 = GangaWorkStep([atlasSetup,atlfast,atlfastOutput]) workFlow = GangaWorkFlow([workStep1]) lsfJob = GangaLSFJob(“atlfastTest”,workFlow) lsfJob.build() lsfJob.run() At this level, there is less built-in intelligence than in ASK, but a lot of flexibility

25/03/2003CHEP 2003, La Jolla, California 14 Low-level tools: LHCb example (DaVinci) lhcbSetup = GangaCommand(“source /afs/cern.ch/lhcb/scripts/lhcbenv.sh”) daVinciSetup = GangaCommand(“source /afs/cern.ch/lhcb/scripts/ProjectEnv.sh DaVinci v7r2”) daVinci = GangaCMTApplication(“Phys/DaVinci”, “v7r2”,”DaVinci.exe”, “options/DaVinci.opts”) daVinciOutput = GangaOutputFile(“dvhistos.hbook”) workStep1 = GangaWorkStep([lhcbSetup,daVinciSetup,daVinci, daVinciOutput]) workFlow = GangaWorkFlow([workStep1]) lsfJob = GangaLSFJob(“daVinciTest”,workFlow) lsfJob.build() lsfJob.run() lhcbSetup = GangaCommand(“source /afs/cern.ch/lhcb/scripts/lhcbenv.sh”) daVinciSetup = GangaCommand(“source /afs/cern.ch/lhcb/scripts/ProjectEnv.sh DaVinci v7r2”) daVinci = GangaCMTApplication(“Phys/DaVinci”, “v7r2”,”DaVinci.exe”, “options/DaVinci.opts”) daVinciOutput = GangaOutputFile(“dvhistos.hbook”) workStep1 = GangaWorkStep([lhcbSetup,daVinciSetup,daVinci, daVinciOutput]) workFlow = GangaWorkFlow([workStep1]) lsfJob = GangaLSFJob(“daVinciTest”,workFlow) lsfJob.build() lsfJob.run() Command sequences for Atlas and LHCb are very similar

25/03/2003CHEP 2003, La Jolla, California 15 Ganga: high-level tools  In Ganga, common tasks are realized via methods of job and application handler classes (JobHandler, ApplicationHandler and their subclasses).  The low-level software needs to provide building blocks for these methods.  High-level tools are available both at the command line and through a GUI.  More advanced functionality will appear with the progress of low-level tools development.  In Ganga, common tasks are realized via methods of job and application handler classes (JobHandler, ApplicationHandler and their subclasses).  The low-level software needs to provide building blocks for these methods.  High-level tools are available both at the command line and through a GUI.  More advanced functionality will appear with the progress of low-level tools development.

25/03/2003CHEP 2003, La Jolla, California 16 Ganga: GUI Implementation GUI is created using wxPython extension module. All job configuration data are represented as a hierarchical structure accessible via tree control. Most important job parameters are brought to the top of the tree. All job parameters defined by the user can be edited via GUI dialogs. All implemented tools are available via GUI, but some of them require more elaborated interface, e.g., Job Options browser/editor. Python interpreter is embedded into the GUI and allows user to configure interface from the command line. GUI is created using wxPython extension module. All job configuration data are represented as a hierarchical structure accessible via tree control. Most important job parameters are brought to the top of the tree. All job parameters defined by the user can be edited via GUI dialogs. All implemented tools are available via GUI, but some of them require more elaborated interface, e.g., Job Options browser/editor. Python interpreter is embedded into the GUI and allows user to configure interface from the command line.

25/03/2003CHEP 2003, La Jolla, California 17 GUI Snapshots Embedded Python interpreter

25/03/2003CHEP 2003, La Jolla, California 18 GUI Snapshots Create a new job

25/03/2003CHEP 2003, La Jolla, California 19 GUI Snapshots Access Job (application) options downloaded from DB

25/03/2003CHEP 2003, La Jolla, California 20 GUI Snapshots Define batch system

25/03/2003CHEP 2003, La Jolla, California 21 GUI Snapshots Define necessary resources

25/03/2003CHEP 2003, La Jolla, California 22 GUI Snapshots Submit the job (after configuration)

25/03/2003CHEP 2003, La Jolla, California 23 GUI Snapshots Job has been submitted successfully

25/03/2003CHEP 2003, La Jolla, California 24 GUI Snapshots Job monitoring has been started automaticall y

25/03/2003CHEP 2003, La Jolla, California 25 GUI Snapshots Standard output for the “Hello World” LSF job

25/03/2003CHEP 2003, La Jolla, California 26 Future Plans and Conclusions One of the immediate plans is to complete implementation of Grid data management tools (interface to GDMP and replica-manager). Advanced Job Options Editor should be developed and integrated with Ganga. We plan to add new job handlers, e.g., for PBS and for local PC. While we assume that basic LHCb software is available at worker nodes, we can’t require the same for the user code. Therefore the possibility to build user software remotely with Ganga should be investigated. Web-based variant of GUI (or thin remote client) should be considered. Some questions remain related to the security issues, but we can try Globus PyCoG to overcome these problems. We plan to investigate possibilities for exploiting Grid Monitoring Architecture in Ganga. Code for the Ganga package can be obtained from Gaudi CVS repository. More information about GANGA development can be found in the web site One of the immediate plans is to complete implementation of Grid data management tools (interface to GDMP and replica-manager). Advanced Job Options Editor should be developed and integrated with Ganga. We plan to add new job handlers, e.g., for PBS and for local PC. While we assume that basic LHCb software is available at worker nodes, we can’t require the same for the user code. Therefore the possibility to build user software remotely with Ganga should be investigated. Web-based variant of GUI (or thin remote client) should be considered. Some questions remain related to the security issues, but we can try Globus PyCoG to overcome these problems. We plan to investigate possibilities for exploiting Grid Monitoring Architecture in Ganga. Code for the Ganga package can be obtained from Gaudi CVS repository. More information about GANGA development can be found in the web site