DSP online algorithms for the ATLAS TileCal Read Out Drivers

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DSP online algorithms for the ATLAS TileCal Read Out Drivers. Cristobal Cuenca Almenar IFIC (University of Valencia-CSIC). Outline. System overview Code structure Processing tasks Optimal Filtering Muon tagging Missing Et. ATLAS detector. . Hadronic Tile Calorimeter. 12 m. EBA. LBA. - PowerPoint PPT Presentation

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DSP online algorithms for the ATLAS TileCal

Read Out Drivers

Cristobal Cuenca AlmenarIFIC (University of Valencia-CSIC)

Outline System overview Code structure Processing tasks

Optimal Filtering Muon tagging Missing Et

ATLAS detector

Hadronic Tile Calorimeter

4 m

12 mEBA

LBALBC

EBC

Hadronic Tile Calorimeter

Read Out Chain

PMT

SHAPER

DIGITIZER

TILECAL MODULE

READ OUT DRIVER SYSTEM

Optical Fibers

Read Out Driver boardG-links

Read Out Driver boardStaging FPGAs

Read Out Driver boardProcessing Units

Read Out Driver board

Output ControllerFPGAs

Read Out Driver board

Serializers

Read Out Driver boardVME and TTC

FPGA

Read Out Driver boardStaging FPGAsG-links Processing Units

Optical Fibers

TransitionModule

Output ControllerFPGAs

Serializers

VME and TTCFPGA

Processing Units: DSP Eight functional units:

2 multipliers 6 arithmetic and logical units

8/16/32-bit data support 40-bit arithmetic options Clock cycle of 720 MHz Memory: 1056 Kbytes

32 Kbytes cache 1024 Kbytes RAM

Real time fixed-point processor

TMS360C6414xTM Texas Instruments

Trigger signal distribution

ATLAS three trigger levels.

Read-Out Drivers (ROD).

Processing Units

TTC Information

Outline System overview Code structure Processing tasks

Optimal Filtering Muon tagging Missing Et

Code structure

Circular buffers Two input buffers / one output Circular buffers: pointers defined at configuration time.

Commands and Internal Registers

Commands: configure the DSP processing variables:

• event size• processing task• TTC synchronization• Missing Et & Muons tag• Histogramming• Staging / Full operation modes

Internal Registers: Online information of the

detector read-out performance.

Information available from the ATLAS TDAQ official software.

Synchronization task BCID checking : Front-End data vs. TTC information

TTC events always processed. Resynchronization tasks to restore single errors.

Timer interruptions to avoid stopping the system when a module fails.

Outline System overview Code structure Processing tasks

Optimal Filtering Muon tagging Missing Et

Reconstruction Algorithms

Requirements: Send reconstructed information to the 2nd level trigger

Work in real-time at 1st level trigger rate• LHC rate: 100 kHz • First years rate: ~50 kHz• Commissioning rate (during July-August 2006): ~1Hz

Proposed algorithms: Optimal Filtering:

Reconstruction of the energy and arrival time of the particles

Transverse Energy:Calculation of the transverse energy deposited on each module

Muon Tag: Identification of low transverse momentum muons

Optimal Filtering (I)

OF: amplitude, phase and Quality Factor.

Digital Samples ATLAS Physics run : 7 samples

Pedestal: Baseline of the signal.

Weights obtained from the pulse shape and noise autocorrelation matrix.

∑=

−=n

iii pSaA

1

)( ∑=

−=n

iii pSb

A 1

)(1τ

∑=

−−=n

iii AgpS

A 1

))((1χ

Optimal Filtering (II) Input data: 16 DMU blocks

with 3 channels each. Individual channel gain

transmitted in the DMU block header.

7 samples per channel. Pedestal assignment. Weights downloaded from a

database by the TDAQ software at configuration time.

Energy Time QF Roundup, scaling and

packing adaptation for the output data format.

Muon tagging

Input data: Energy from OF algorithm.

Upper and lower thresholds:

Low threshold cuts the electronic noise

Upper threshold eliminates hadronic showers and tails

Output: number of muons found and Pseudorapidities of these muons

3,2,1=≤≤ ithrEthr highii

lowi

Missing Et algorithm

Input data: energy from OF algorithm

DSP fast computation of: Total transverse energy per module

X and Y projections Output packed in event sub-fragment toguether with Muon tagging algorithm output.

Conclusions An Optimal Filter has been implemented in the TileCal Read Out Driver for online data reconstruction

Two trigger oriented algorithms have also been implemented: Muon tagging Transverse energy calculation

These algorithms have been tested successfully during TileCal commissioning phase last summer.

Working now on improving timing and performance