dsp online algorithms for the atlas tilecal read out drivers
DESCRIPTION
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 PresentationTRANSCRIPT
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