m. richter, d. r ö rich, s. bablok (ift, university of bergen) p.t. hille (university of oslo)

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Status of implementation of Detector Algorithms in the HLT framework

Calibration Session – OFFLINE week(16-03-2007)

M. Richter, D. Rörich, S. Bablok(IFT, University of Bergen)

P.T. Hille(University of Oslo)

M. Ploskon(IKF, University of Frankfurt)

S. Popescu, V. Lindenstruth(KIP, University of Heidelberg)

Indranil Das

(Saha Institute of Nuclear Physics)


TOC• HLT functionality• HLT interfaces• HLT DCS• HLT OFFLINE • HLT interface to AliEve• Synchronisation via ECS• Status of Detector Algorithms

– generell remarks– TPC– TRD– PHOS– DiMuon


HLT functionality• Trigger

– Accept/reject events• verify dielectron candidates

• sharpen dimuon transverse momentum cut

• identify jets

• ...

• Select – Select regions of interest within an event

• remove pile-up in p-p

• filter out low momentum tracks

• ...

• Compress– Reduce the amount of data required to encode the event as far as possible without

loosing physics information


HLT interfaces• ECS:

– Controls the HLT via well defined states (SMI)

– Provides general experiment settings (type of collision, run number, …)

• DCS:– Provides HLT with current Detector parameters (voltages, temperature, …)

Pendolino

– Provides DCS processed data from HLT (TPC drift velocity, …) FED-portal (Front-End-Device portal)

• OFFLINE:– Interface to fetch data from the OCDB TAXI, (OFFLINE HLT)

– Provides OFFLINE with calculated calibration data Shuttle-portal, (HLT OFFLINE)

• HOMER:– HLT interface to AliEve for online event monitoring


OFFLINE

DCS

TaskManager

ArchiveDB

PVSS

FES

MySQL

FEDportal

Shuttle

Pendolino

ECS-proxy

Data flow in HLT

spec Datasink(Subscriber)

Pendolino-portal

intern

extern

DADA

HLT

OCDB(Conditions)

AliEnTaxi

HCDB(local Cache)

Taxi-HCDB

ECS

AliRoot CDB access

Detector responsibility

FrameworkcomponentsInterface

DA_HCDB

DA_HCDB

AliEve

HomerPubSub

Detectordata

HLT cluster data

DIM-Subscriber


OFF

INITIALIZING<< intermediate state>>

DEINITIALIZING<< intermediate state>>

INITIALIZED

CONFIGURED

READY

RUNNINGRUNNING

CONFIGURING<< intermediate state>>

ENGAGING<< intermediate state>>

DISENGAGING<< intermediate state>>

INITIALIZE

implicit transtion

SHUTDOWNCONFIGURE

+ params

RESET

ENGANGE

DISENGAGE

START

STOP

implicit transtion

implicit transtion

implicit transtion

implicit transtion

COMPLETINGCOMPLETING

implicit transtion

Distribution of current version of

HCDB to DA nodes (DA_HCDB)

Filling of FileExchange

Server (FES) and MySQL DB

Offline Shuttle can fetch data

DAs request their

DA_HCDB

Pendolino fetches data from DCS archive DB and stores data to DA_HCDB

Synchronisation via ECS

ECS interface


HLT DCS interface• FED portal:

– Dim Channels (Services published on the HLT side)

– implementing partially the FEDApi

– Subscriber component of the HLT framework

– PVSS panels on DCS side integrate data in DCS system

– storing of DCS related data in the DCS Archive DB (HLT-cluster monitoring [HLT]; TPC drift velocity, …[detector specific])

• Pendolino:– contacts the DCS Amanda server (DCS Archive DB)

– fetches current running conditions (temperature, voltages, …)

– feeds content into DA_HCDB

– requests in regular time intervals: • three Pendolinos, each with a different frequency (fast, medium, slow)

Normal text - click to edit DCS

portal-dcs(dcs-vobox)

Detector responsibility

FrameworkcomponentsInterface

Pendolino (incl. detector preproc)

portal-dcs(Dim Subscriber)

Interface (PubSub –FED API [DIM ])

FEDAPI

ArchiveDB

PVSS

DA_HCDB

Pendolinofile catalogue

SysMes

Interface to SysMes

triggers sync

DADA

AliRoot CDB access classes

HLT DCS interface


HLT DCS interface

• Pendolino details:– Three different frequencies:

• fast Pendolino: 10 sec - 1 min

• normal Pendolino: 1 min - 5 min

• slow Pendolino: over 5 min

– Response time: • ~13000 values per second

– Remark:• The requested values can be up to 2 min old.

(This is the time, that can pass until the data is shifted from the DCS PVSS to the DCS Archive DB)


HLT OFFLINE interface• Taxi portal

– Requests OCDB and caches content locally (HCDB)

– Provides calibration objects to Detector Algorithms (DA) inside the HLT• copied locally to DA nodes before each run (DA_HCDB)

– DA_HCDB accessible via AliRoot CDB access classes

• Shuttle portal– Collects calibration data from Detector Algorithms

– Provides the data to OFFLINE, fetched after each run by Offline Shuttle

– Data exchanged via FileExchangeServer (FES)

– Meta data stored in MySQL DB


OFFLINE

HLT OFFLINE interface• Taxi portal:

TaskManager

DADA

1.Taxi0

HCDB0portal-taxi0(vobox-taxi0)

DA_HCDB

ECS-proxy

OCDB

current run number

triggersupdate

ECS

AliRoot CDB access classes

DADA AliRoot CDB access classes

SysMes

DA_HCDB


OFFLINE

HLT OFFLINE interface• Shuttle portal:

OCDB

DADA

FES MySQL

portal-shuttle0(Subscriber)

Shuttle

DADA

TaskManager

ECS-proxy

ECSnotifies:

“collecting finished”


AliEVE HLT event display (example TPC)

• existing infrastructure (M. Tadel)adopted to HLT with minimaleffort

• connect to HLT from anywherewithin GPN

• ONE monitoring infrastructurefor all detectors

• using HOMER data transportabstraction


Status Detector Algorithms(general remark)

HLT provides service and infrastructure to run Detector Algorithms, e.g. reconstruction and calibration algorithms

offline code can be run on the HLT, if it fulfills the requirements, given by the constraints due to:

limited accessibility of (global) AliRoot data structures

processing of each event is distributed over many nodes

none of the nodes have the full event data of all stages available

Detector algorithm interfaces via a processing component to the HLT data chain

Processing component implements the HLT component interface

General principle:

HLTData

Input

Data

Output

Only the input, DCS- and calibration data is available for processing


Status Detector Algorithms (general remark)

HL

T c

hain

HLT Processors/

Detector Algorithms

offline source

interface

Completely identical HLT processing can run both in the online and offline framework

dedicated data structures shipped between components, can be ROOT Tobjects

DA's must work entirely on incoming data

dedicated publisher components for special data are possible

HLT produces ESD files, filled with the data it can reconstruct/provide

offline sink

interface

RORC publishers

HLT out

Online Offlinedata from DAQ AliHLTReconstructor

data to DAQ AliHLTReconstructor


Status Detector Algorithms(general remark)

1) no access to (global) AliRoot data structures

(a) DA's have no AliRunLoader instance

(b) DA's run as separated processes, no data exchange via global variables

(c) DA's can only work on incoming data and OCDB data

2) proper data transport hierarchy deployed by DA, i.e. access to whatever data through

global methods/objects from lower hierarchies is penalty code

3) structures/objects for data exchange have to be optimized

4) TObjects for data transport must declare pointer-type members as transient members

(//!), initialization properly handled by the constructor

5) in principle all offline code using the AliReconstructor plugin scheme can run on HLT,

if a proper data transport hierarchy is deployed


Status Detector Algorithms(TPC status)

Status:

• full TPC reconstruction running in HLT

• output in ESD format

• TPC calibration tasks defined by the TPC group

• TPC group decided to extensively use HLT's computing capabilities for calibration task

• several prototype DA's developed

• Commissioning of calibration algorithms starts soon


Status Detector Algorithms(TPC task list)

• HLT On-line monitoring for TPC – Calibration :

• 1-d histograms for pedestal runs and noise calibration

• 1-d histograms for pad by pad calibration (time offset, gain and width of the time response function) for the pulser run and during the normal data taking

• 1-d histograms for the gain calibration during the Krypton run, cosmic, laser and data taking

• TPC drift velocity

• Data Quality Monitoring (DQM)

– Online monitoring:• 3d reconstructed track view optionally together with the 3d detector geometry inside

• Drift velocity monitoring

• Pad by pad signal

• Charge per reconstructed track monitoring


Status Detector Algorithms(TRD status)

• Clusterization algorithm– Ready and working

– Uses directly Offline clusterizer

• Stand alone tracker– Almost ready (ready within next 1-2 weeks)

• HLT Component implemented

• Still few fixes within the AliRoot TRD offline code to be done – HLT will run 100% Offline code here too

• PID component– Pending – offline code under finalization stage – again, no change of the Offline

algorithms within HLT

• Triggering scenarios under consideration



• Calibration– Native AliRoot OCDB calibration data access (provided via HLT TAXI)

– Production of reference data for calibration algorithms• Ready and working

• Uses directly offline code

• Monitoring– Prototype ready

– Integration into AliEve will follow

TRD Clusters reconstructed on HLT



• Calibration:– Histogram production ready&working (mcm tracklet based)

– Each HLT component has an OCDB access (just like in Offline) via local (HLT node) storage – TRD chain is using OCDB data (1:1 Offline AliRoot code)

– TRD preprocessor handles calibration of calibration parameter from the input histograms collected on the HLT

• TRD local reconstruction on HLT almost complete (local tracking still on the way...)

• Calibration histograms are produced

• First HLT monitoring code emerging soon (also AliEve support)


Status Detector Algorithms(TRD task list)

• Short term to do:– PID

– Track merging with TPC (and ITS eventually)

• Long term to do:– Physics trigger scenarios


Status Detector Algorithms(PHOS status)

• Current status– running full PHOS HLT chain (5 modules) with raw data simulated in aliroot

– successful test on simulated HLT ”cluster” consisting of 3 laptops

– fast and accurate online evaluation of cell energies

– calibration data: Continious accumulation of per channel energy distribution:• Calibration data written to root files at end of run.

• Histograms has been evaluated visually and looks reasonable.

– raw data can be written to files untouched by the HLT (HLT mode A)

– calibration data can be accumulated over several runs.

– event display: Display of events & calibration data for 5 modules using HOMER

– collection of data from several nodes to be vizualized in a single event display.

– PHOS HLT Analysis chain has run successfully distributed over 21 nodes at the HLT cluster at P2


Status Detector Algorithms(PHOS task list)

• Currenly ongoing work:– Implementation of DQM

– Integration of end of run calibration procedures, DA

– Implementation of fast Phi0 invariant mas algorithm

– Testing and benchmarking of the processing cain on the HLT cluster.

– Preparations for PDC07

• Near future plans:– Integration ECS, DCS , shuttle etc..

– Testing of the HLT processing chain on beamtest data

– Making of ESDs to be send to DAQ with HLT-out

– Running of the PHOS HLT processing chain on data files and root files

– Minor improvment on the online display

– Finalization and documentation of internal PHOS HLT data format.


Status Detector Algorithms(DiMuon status and task list)

• Present Status:– Standalone hit reconstruction is ready and implemented in HLT environment of

CERN PC farm

– First results of resolution test with the rawdata generated using AliRoot of dHLT chain at CERN

– Processing time for multiple event is large compared to standalone mode

– Full dHLT Chain is working and up in UCT cluster

• Future to do list:– Improvement of the processing timing

– Integration of the tracker algorithm in CERN HLT.

– Implementation of the full chain along with debugging and benchmarking.

– Preparing the output in ESD format.

– Efficiency checking of the dHLT chain using beamtest data


Information on the web

http://wiki.kip.uni-heidelberg.de/ti/HLT/index.php/ECS-interface

http://wiki.kip.uni-heidelberg.de/ti/HLT/index.php/Specification-HLT2OFFLINE-interface

http://wiki.kip.uni-heidelberg.de/ti/HLT/index.php/UseCase-Calibration-HLT

http://wiki.kip.uni-heidelberg.de/ti/HLT/index.php/Data_path_from_DCS_to_the_HLT

and talks of HLT session on the last Alice week


Backup slides


Status Detector Algorithms(TRD DA overview)


Resolution of dHLT hitreconstruction

Note : Resolution in the Y direction is far better than the X directionis due to the detector geometry, the minimum padsize in beding planeis ~0.5 cm, whereas in non-bending direction is ~0.71 cm.


HLT ECS interface• State transition commands from ECS

– INITIALIZE, CONFIGURE(+PARAMS), ENAGE,START,…

– Mapping to TaskManager states

• CONFIGURE parameters:– HLT_MODE: the mode, in which the HLT shall run (A, B or C)

– BEAM_TYPE: (pp (proton-proton) or AA (heavy ion))

– RUN_NUMBER: the run number for the current run

– DATA_FORMAT_VERSION: the expected output data format version

– HLT_TRIGGER_CODE: ID defining the current HLT Trigger classes

– CTP_TRIGGER_CLASS: the trigger classes in the Central Trigger Processor

– HLT_IN_DDL_LIST: list of DDL cables on which the HLT can expect event data in the coming run. The structure will look like the following: <CableName>:<DetectorPart>,<CableName>:<DetectorPart>,...

– HLT_OUT_DDL_LIST: list of DDLs, on which the HLT can send data to DAQ

m. richter, d. r ö rich, s. bablok (ift, university of bergen) p.t. hille (university of oslo)

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