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The GANGA Interface & ATLAS Development Alvin Tan (Birmingham) Alvin Tan (Birmingham)

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Presentation on theme: "The GANGA Interface & ATLAS Development Alvin Tan (Birmingham) Alvin Tan (Birmingham)"— Presentation transcript:

1 The GANGA Interface & ATLAS Development Alvin Tan (Birmingham) Alvin Tan (Birmingham)

2 Agenda ATLAS - DC2 - ATLAS/LCG Integration Tests - Automatic Software Packaging and Installation - Distributed Metadata Services - ATLAS Distributed Analysis (ADA) GANGA - Role in ADA - Current status - Job Options Editor (JOE) - Future plans ATLAS - DC2 - ATLAS/LCG Integration Tests - Automatic Software Packaging and Installation - Distributed Metadata Services - ATLAS Distributed Analysis (ADA) GANGA - Role in ADA - Current status - Job Options Editor (JOE) - Future plans

3 ATLAS DC2 September 2003 – July Analysis phase. DC2 goals include: Full use of Geant4; POOL; LCG applications Pile-up and digitization in Athena Deployment of the complete Event Data Model and the Detector Description Simulation of full ATLAS and 2004 combined Testbeam Test the calibration and alignment procedures Use widely the GRID middleware and tools Large scale physics analysis Computing model studies (document end 2004) Run as much as possible of the production on LCG-1/2 DC2 is essentially a slice test of the ATLAS Computing Model.

4 ATLAS DC2 - Schedule September 03: Release7 Mid-November 03: pre- production release February 27 th 04: Release 8 (production) April 1 st 04: June 1 st 04: DC2 July 15th Slide from Gilbert Poulard Put in place, understand & validate: Geant4; POOL; LCG applications Event Data Model Digitization; pile-up; byte-stream Conversion of DC1 data to POOL; large scale persistency tests and reconstruction Testing and validation: Run test-production Start final validation Start simulation; Pile-up & digitization Event mixing Transfer data to CERN Intensive Reconstruction on Tier0 Distribution of ESD & AOD Calibration; alignment Start Physics analysis Reprocessing Put in place, understand & validate: Geant4; POOL; LCG applications Event Data Model Digitization; pile-up; byte-stream Conversion of DC1 data to POOL; large scale persistency tests and reconstruction Testing and validation: Run test-production Start final validation Start simulation; Pile-up & digitization Event mixing Transfer data to CERN Intensive Reconstruction on Tier0 Distribution of ESD & AOD Calibration; alignment Start Physics analysis Reprocessing

5 ATLAS/LCG Integration Test LCG is deployed in over 20 sites across the world and the number is increasing. ATLAS and some EDG WP1 bug fixes are included in this release. To test the readiness of ATLAS code on LCG, simulation and reconstruction were executed using a test suite implemented in Perl. LCG is deployed in over 20 sites across the world and the number is increasing. ATLAS and some EDG WP1 bug fixes are included in this release. To test the readiness of ATLAS code on LCG, simulation and reconstruction were executed using a test suite implemented in Perl.

6 Integration Test Results (1) SiteReplicaSimulReco IFICOKX(1) KRAKOWX(2) RALOK IFCAOKX(3) CNAFOKX(4) IFAEOKOK(5) BNLOKX(6) FZKOKX(7) CERN 15OKX(1) CERN 18OK X(1) PRAGUEOK

7 Integration Test Results (2) SiteReplicaSimulReco CIEMATOK TAIWANOK UAMOKX(1) CESGAOKX(3) TOKYOOKX(1) MSUOKX(1) ECM-UBX(8) IMPERIALOKX(6)

8 Integration Test Results (key) (1): IFIC,CERN,UAM,MSU,TOKYO: Abort (Caught GLOBUS error 3 (I/O related) from IFIC) (2):KRAKOW:MDS Error: Invalid/ no SE registered. (3):IFCA,CESGA: no file access to SE data from WN (NFS?) (4):CNAF: Missing AtlasRelease directory (5) IFAE:YPBINDPROC_DOMAIN Domain not bound messages… (6):BNL,IMPERIAL:could not connect to MDS (7):FZK:javax.naming.NameNotFoundexception: LDAP Error 42… (8):BARCELONA: no local mapping for GLOBUS ID (1): IFIC,CERN,UAM,MSU,TOKYO: Abort (Caught GLOBUS error 3 (I/O related) from IFIC) (2):KRAKOW:MDS Error: Invalid/ no SE registered. (3):IFCA,CESGA: no file access to SE data from WN (NFS?) (4):CNAF: Missing AtlasRelease directory (5) IFAE:YPBINDPROC_DOMAIN Domain not bound messages… (6):BNL,IMPERIAL:could not connect to MDS (7):FZK:javax.naming.NameNotFoundexception: LDAP Error 42… (8):BARCELONA: no local mapping for GLOBUS ID

9 Integration Test Conclusion With only 6 out of 19 sites passing the simul test, a couple of sites suffering Aborts at submission time and the rest experiencing various other problems, the tests were inconclusive and further investigation is needed.

10 Automatic Software Packaging and Installation Based on Pacman 2, CMT, tar/rpm and some shell scripts. It satisfies the requirements set out for binary kit distribution and developers kit distribution. - Kits exist for recent releases (e.g , 7.4.0, 7.5.0). Early adopters have given useful feedback and it is now being imported into Grid production systems. - At RHUL, students and RAs have been doing their physics studies using the kit since November Based on Pacman 2, CMT, tar/rpm and some shell scripts. It satisfies the requirements set out for binary kit distribution and developers kit distribution. - Kits exist for recent releases (e.g , 7.4.0, 7.5.0). Early adopters have given useful feedback and it is now being imported into Grid production systems. - At RHUL, students and RAs have been doing their physics studies using the kit since November 2003.

11 Automatic Software Packaging and Installation (cont) The LCG has recently confirmed the method/format of publishing kits. Future plans include (this deliverable is complete) : - integration with GANGA for user code distribution, - full source kit distribution, and - Pacman 3 integration. The LCG has recently confirmed the method/format of publishing kits. Future plans include (this deliverable is complete) : - integration with GANGA for user code distribution, - full source kit distribution, and - Pacman 3 integration.

12 Distributed Metadata Services Main objectives: To understanding of the existing ATLAS metadata structures and its use-cases. Develop metadata to support navigational use- cases. Understand analysis use-cases, optimise event to file granularity for different types of analysis data and develop automated ways of obtaining optimal event data granularity. Implement a working solution that will integrate with existing ATLAS software, in particular, the ATLAS Metadata Infrastructure (AMI) product. Main objectives: To understanding of the existing ATLAS metadata structures and its use-cases. Develop metadata to support navigational use- cases. Understand analysis use-cases, optimise event to file granularity for different types of analysis data and develop automated ways of obtaining optimal event data granularity. Implement a working solution that will integrate with existing ATLAS software, in particular, the ATLAS Metadata Infrastructure (AMI) product.

13 Distributed Metadata Services (cont) The plan: To deliver a distributed metadata web service with a GANGA interface that will facilitate distributed analysis within the existing ATLAS analysis framework, consistent with ARDA, and function effectively when deployed as a full scale production service. The plan: To deliver a distributed metadata web service with a GANGA interface that will facilitate distributed analysis within the existing ATLAS analysis framework, consistent with ARDA, and function effectively when deployed as a full scale production service.

14 ATLAS Distributed Analysis (ADA) The ATLAS effort for distributed analysis in the context of ARDA is lead by David Adams (BNL) who is responsible for coordinating the development of software tools for distributed analysis and their integration into the ATLAS software environment. He is involved in the DIAL project and is currently the ATLAS coordinator of GANGA project.

15 ADA Scope Analysis (not necessarily distributed) Supports the manipulation and extraction of summary data (e.g. histograms) from any type of event data e.g. AOD, ESD, … Supports user-level production of event data e.g. MC generation, simulation and reconstruction. Distributed analysis Extends the extraction and production support to include distributed processing, data and users. Natural extension of non-distributed analysis. Easily invoked from any ATLAS analysis environment including Python, ROOT and command line while easily ported to any other environments (e.g. JAS).

16 ADA - The early days A number of projects relevant to distributed analysis and production already exist in ATLAS DC2 production system Supervisor/executor model allows grid-based production of data on different grid flavors Includes DMS: file replica service combining all the ATLAS replica catalogs The AMI Database Just introduced a web service interface to bookkeeping DIAL: Distributed Interactive Analysis of Large Datasets Running analysis web service with ROOT-based client GANGA User-friendly interface for distributed Athena/Gaudi processing These constitute the starting point for evolution to ADA.

17 RB Chimera RB Task (Dataset) Partition Transf. Definition Task Transf. Definition + physics signature Executable name Release version signature Supervisor 1Supervisor 2Supervisor 4 US GridLCGNG Local Batch Task = [job]* Dataset = [partition]* JOB DESCRIPTION Human intervention Data Management System US Grid Executer LCG Executer NG Executer LSF Executer Supervisor 3 Job Run Info Rob GardnerAlessandro De Salvo Oxana Smirnova Luc Goossens Luc Goossens Kaushik De Luc Goossens Location Hint (Task) Location Hint (Job) Job (Partition) Automatic Production System (Windmill)

18 ADA Strategy Implement ADA as a collection of grid services As described in ARDA document Use ARDA components where possible Add missing and ATLAS-specific pieces Identify high-level services users interact directly with Job submission (aka analysis service) Catalogs Define language for interaction with these services AJDL: Analysis Job Description Language Objects exchanged between clients and services Service interfaces expressed in terms of these objects Implement ADA as a collection of grid services As described in ARDA document Use ARDA components where possible Add missing and ATLAS-specific pieces Identify high-level services users interact directly with Job submission (aka analysis service) Catalogs Define language for interaction with these services AJDL: Analysis Job Description Language Objects exchanged between clients and services Service interfaces expressed in terms of these objects

19 ADA - AJDL AJDL

20 ADA Strategy (cont) Implement high-level services Reuse existing software where possible. Re-implement as requirements become clearer and new middleware becomes available. Provide clients for ATLAS analysis environments Python (GANGA), ROOT, command line Also web portal and java Look to common projects required pieces e.g. ARDA, GANGA, DIAL, … Share as much as possible with ATLAS production which is also distributed and possess similar interfaces and code for bulk and user-level production. Implement high-level services Reuse existing software where possible. Re-implement as requirements become clearer and new middleware becomes available. Provide clients for ATLAS analysis environments Python (GANGA), ROOT, command line Also web portal and java Look to common projects required pieces e.g. ARDA, GANGA, DIAL, … Share as much as possible with ATLAS production which is also distributed and possess similar interfaces and code for bulk and user-level production.

21 GANGA in ADA A major player in the ADA, GANGA developers will work closely with DIAL developers. To facilitate ADA, GANGA will have an AJDL interface. GANGA and DIAL (ROOT) will be the first ADA clients and will provide some initial services based on existing functionality e.g. job submission and monitoring. GANGA will also provide an ADA scheduler service for other flavours of ADA clients. A major player in the ADA, GANGA developers will work closely with DIAL developers. To facilitate ADA, GANGA will have an AJDL interface. GANGA and DIAL (ROOT) will be the first ADA clients and will provide some initial services based on existing functionality e.g. job submission and monitoring. GANGA will also provide an ADA scheduler service for other flavours of ADA clients.

22 GANGA in ADA AJDL

23 GANGA - Status Update Work since September 2003 has focused on refactoring, to create a system that is more modular and more flexible In short-term (next 1-2 months), changes will mainly affect developers. In longer term (in time for DC2) will see significant gains for users: improvements in functionality, ease of use and stability. Have introduced PyBus software bus, developed by W. Lavrijsen with contributions from K. Harrison (released in LCG SEAL project) Allows dynamic association of modules and logical name. Forms the basis of a highly configurable framework: supports ATLAS/LHCb customizations and user add-ons. Work since September 2003 has focused on refactoring, to create a system that is more modular and more flexible In short-term (next 1-2 months), changes will mainly affect developers. In longer term (in time for DC2) will see significant gains for users: improvements in functionality, ease of use and stability. Have introduced PyBus software bus, developed by W. Lavrijsen with contributions from K. Harrison (released in LCG SEAL project) Allows dynamic association of modules and logical name. Forms the basis of a highly configurable framework: supports ATLAS/LHCb customizations and user add-ons.

24 GANGA Status Update (cont) Moving to XML-based job description. In the process of defining details of XML schema Aim to have job description consistent with DIAL (and others?) Working to separate client and service functionality implemented in GANGA V1.0 Functionality of Job Options Editor (JOE) being enhanced (more later). Moving to XML-based job description. In the process of defining details of XML schema Aim to have job description consistent with DIAL (and others?) Working to separate client and service functionality implemented in GANGA V1.0 Functionality of Job Options Editor (JOE) being enhanced (more later).

25 GANGA - JOE Job-options editor (JOE) is evolving to become a more powerful, standalone application, which can be loaded by GANGA. Assist user in the creation/modification of Gaudi/Athena job options by presenting the user with a hierarchical view of available options files and helping the user with value entry. Job-options editor (JOE) is evolving to become a more powerful, standalone application, which can be loaded by GANGA. Assist user in the creation/modification of Gaudi/Athena job options by presenting the user with a hierarchical view of available options files and helping the user with value entry.

26 GANGA - JOE (cont) In process of creating Job Options Information Resource (JOIR) database JOIR database of job options will facilitate validation by providing valid ranges, option choices, and option descriptions. Considering suggestions from LHCb for improving automated job-option extraction. Validation component of job option entry using a database created by automated extraction of job option attribute/value from Gaudi/Athena shared libraries. In process of creating Job Options Information Resource (JOIR) database JOIR database of job options will facilitate validation by providing valid ranges, option choices, and option descriptions. Considering suggestions from LHCb for improving automated job-option extraction. Validation component of job option entry using a database created by automated extraction of job option attribute/value from Gaudi/Athena shared libraries.

27 GANGA Future Plans Work towards GANGA/DIAL integration within ADA More tentatively, looking at possibilities for interfacing to Atlantis for displaying event data. Task Editor (TEd) will build on JOE by providing access to other information relating to a user task (e.g. user code). Currently in planning stage. Demo of GANGA in the context of ADA at next ATLAS Software Workshop (1-5 March) ADA/GANGA tutorial at ATLAS Software Workshop at BNL (24-28 May). Full functionality foreseen for GANGA V2.0. (GridPP milestone for end-March). Work towards GANGA/DIAL integration within ADA More tentatively, looking at possibilities for interfacing to Atlantis for displaying event data. Task Editor (TEd) will build on JOE by providing access to other information relating to a user task (e.g. user code). Currently in planning stage. Demo of GANGA in the context of ADA at next ATLAS Software Workshop (1-5 March) ADA/GANGA tutorial at ATLAS Software Workshop at BNL (24-28 May). Full functionality foreseen for GANGA V2.0. (GridPP milestone for end-March).

28 End.


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