overview of the atlas fast tracker...
TRANSCRIPT
July 24, 2008 M. Shochet 1
Overview of the ATLAS Fast Tracker (FTK)(daughter of the very successful CDF SVT)
July 24, 2008 M. Shochet 2
What is it for?• At the LHC design accelerator intensity:
– New phenomena: ∼ 0.05 Hz– Total interaction rate: ∼ 1 GHz (40 MHz beam crossings)
• Many possible new phenomena produce heavy b quarkswhich can only be distinguished from the bulk of the background by reconstructing the individual tracks.
• We are proposing to significantly enhance the ability of ATLAS to rapidly identify b quarks in the trigger.– Currently done in commodity PC’s. This is slow and becomes
slower as the accelerator intensity and thus track density increase.
The problem!
beam pipe few mm
July 24, 2008 M. Shochet 3
ATLAS
July 24, 2008 M. Shochet 4
Inner Tracking Detectors
Pixels barrel SCT barrel Pixels disks
3 pixel layers (space point)
8 strip layers (1 coordinate)
⇒ 11 layers, 14 coordinates
July 24, 2008 M. Shochet 5
Getting data into FTKRODs
SCT →
Pixels →
ROBs
ROBs
FTKon L1 accept
silicon hits silicon tracks
Level 2
ask for ROI’s
dual-output HOLA designed by Tang
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Number of input fibers• Pixels: 120• Strips: 92
Number of crates• ∼ 12
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How does it work?
• First do pattern recognition, then fit possible candidates.
•Prestore patterns (roads) in large content-addressable memory.
The Pattern Bank (4-layer)
coarse resolution hits full resolution hits(superbins)
July 24, 2008 M. Shochet 8
Massively parallel pattern recognition
AM = BINGO PLAYERS
HIT # 1447
PATTERN NPATTERN 1PATTERN 2
PATTERN 3
PATTERN 5
PATTERN 4
track fitter
1 superbin per silicon layer
Majority logic allows up to 1 missed layer.
July 24, 2008 M. Shochet 9
Functional layout
Track dataROBIN
Track dataROBIN
Raw dataROBINs
~Offline quality Track parameters
SUPER BINSDATA
ORGANIZER ROADS
ROADS + HITS
EVENT # N
PIPELINED AM
HITS(LVDS links)
DO-board
EVENT # 1
AM
-boardPixels & SCT
DataFormatter
(DF)
50~100 KHzevent rate
RODsRODs
cluster findingsplit by layer
overlap regions
S-links
Track Fitter
July 24, 2008 M. Shochet 10
Possible layout for a core crate (after DFs)
AM
-B7
AM
-B8
AM
-B1
AM
-B0
DO
5D
O4
DO
3D
O2
DO
1D
O0
Trac
k Fi
tter
AM
-B2
AM
-B3
AM
-B4
AM
-B5
AM
-B6
AM
-B9
AM
-B10
AM
-B11
AM
-B12
July 24, 2008 M. Shochet 11
Data Formatter
• Receives raw hits from the detector (RODs)• Finds hit clusters
pixels silicon strips
• Store cluster centroids• Separates clusters by silicon layer & sends to Data
Organizers on 6 LVDS data busses (22 bits each)
July 24, 2008 M. Shochet 12
Data Organizer• Receives hits from Data Formatters.• Stores hits at full resolution in a way that is rapidly
accessible by pattern number.• Sends hits at coarser resolution (superbin) to pattern
recognition unit (Associative Memory).• Receives patterns from AM, retrieves full resolution hits,
and sends road number and hits to the Track Fitter.
July 24, 2008 M. Shochet 13
Track Fitter• Receives road # and associated hits from Data Organizers.• Computes all hit combinations
• Calculate the track parameters curvature, azimuthal angle, polar angle, z0, impact parameter
and the goodness of fit (χ2) using a linear correction to the mean for that sector (excellent precision over a sector).
sector: a physical silicon module in each layerpixels: 1" x 2.5 " strips: 2.5" x 5 "
July 24, 2008 M. Shochet 14
14 measurements, 5 parameters ⇒ 9 constraints (→χ2)
Pi: 5 track parameters & 9 constraints (χ2 is sum of squares)xj: the hit coordinate in layer jaij, bi: the stored constants for each sector, calculated in
advance from a large sample of training tracks (simulation or data)
• Cut on goodness of fit; among the combinations in a road, select the track with the best χ2.
• Output good tracks to ROBIN.
14
1i ij j i
jp a x b
=
= +∑
July 24, 2008 M. Shochet 15
Readout Buffer (ROBIN)• Stores tracks for access by the level-2 trigger PCs.
July 24, 2008 M. Shochet 16
Track Fitter details• GigaFitter – a simplified version built for the CDF SVT
– 2D reconstruction (transverse to the beamline)– 6 detector layers– 3 track parameters (curvature, azimuthal angle, impact parameter)– 3 constraints → χ2
July 24, 2008 M. Shochet 17
GigaFitter scheme
• DO roads & hits → input FIFO → RAMs according to detector layer• Combinations (one hit/layer) calculated sequentially & stored in Comb-FIFO• Each combination & the constants are sent to DSP for fitting & selection
Lay0-Ram
Lay1-Ram
Lay2-Ram
Lay3-Ram
...
Com
b -FiFo
INPUT FiFo
Constants RAM
DSP:Fit Tracks
Choose best χ2 track
Lay10-Ram
July 24, 2008 M. Shochet 18
DSP algorithm for SVT
• Comb-FIFO data serialized: 1 hit and its constants sent to parallel DSP slices each computing a track parameter or constraint.
• An additional DSP computes total χ2 from individual constraints• Total of 7 DSP slices in parallel each working at 200 MHz
C4
C3
18
18
18
18
C2
ACC 39
FIFO156
ACC 39
ACC 39
ACC 39
CTRLEVRST
RSTREADY
C1
DSP48E
39
39
39
39
18
constants
Hit
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DSP Slice
• One DSP slice computes a track parameter in 14 clock cycles, plus 4 for the first one.
18
18
39
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Xilinx XC5VSX95T• 14720 V5 slices (4 LUT + 2 FF)
– ∼1% used for each fitter
• 1520 kbit of distributed RAM– ∼1% used for each fitter
• 640 DSPs– ∼2.5% used for each fitter in the FTK version
5 parameters, 9 constraints, 1 to calculate overall χ2
– ⇒ ∼ 40 fitters/chip (remember: many combinations per road)
• 1 Mbyte of block RAM– plenty for the SVT prototype– not even close for the FTK!!
July 24, 2008 M. Shochet 21
Missing hit problem• To obtain high reconstruction efficiency, we must allow one
physical detector layer to miss a hit.• The constants in the parameter and constraint equations are
different when there is a missing hit.• Store 12 sets of constants (all hits, a miss in one of 11 layers).
– A lot of memory that has to be accessed very quickly. Can one look ahead for the constant set that will be needed next?
• Alternative is to estimate the hit location in the missing layer.– How long does it take?
July 24, 2008 M. Shochet 22
Size of the constant memory• 210 words/constant set (14×14 + 14)• If we need 2-byte precision ⇒ 420 bytes/constant set• One constant set/sector. Currently estimate 100k sectors
in an FTK crate.⇒ 42 Mbytes of fast memory⇒ 0.5 Gbyte if solve missing hit problem with more memory
• We have heard that with the latest FPGAs, there is very fast access to external computer-like memory. Is that true?
July 24, 2008 M. Shochet 23
How many fitters are needed?• The number of cycles from the time the data from a road is
in the input FIFO until the track parameters are in the output FIFO is approximately:
NfitCycl = Ncomb × Nhits (all 14 calculations done in parallel)
• A road packet takes Nhits + 1 Data Organizer clock cycles to be sent to the Track Fitter. Thus if we are to have 0 deadtime from track fitting, we need the number of parallel fitters (there are 40 in a chip), Nfitters, satisfying:
• This translates into a maximum average Ncomb of Nfitters × ClockRatio × (Nhits + 1)/Nhits
where ClockRatio is the ratio of the fitter to DO clock speeds.• We will have to satisfy this: road width, # of FPGAs.
Nhits 1 NfitCycl 1DO freq fitter freq Nfitters
+= ×
July 24, 2008 M. Shochet 24
Hit Warrior function• One can easily get many tracks (ghosts) from a single real
particle due to presence of extra random silicon hits.
• Compare a new track with those already found. If new one has 8 or more hits in common with a stored track, keep only the best χ2 track.
• If space permits, add this function to the Track Fitter.
July 24, 2008 M. Shochet 25
Spy Buffer• Data flows very quickly through this system. By the time
any PC using its output detects a problem, the data would already be long gone from the FTK. That makes diagnosing a problem that is occurring internally in the FTK extremely difficult.
• We found it very useful in the SVT to have deep buffers at the input and output of every board in the system. Then, when a problem is detected, these spy buffers can be frozen in the entire system and read out. The buffer is deep enough so the event with the error is still inside it.
• This allows diagnosing and fixing subtle problems.