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07 October 2004 Hayet KEBBATI -1- Data Flow Reduction and Signal Sparsification in MAPS Hayet KEBBATI (GSI/IReS)

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Presentation on theme: "07 October 2004 Hayet KEBBATI -1- Data Flow Reduction and Signal Sparsification in MAPS Hayet KEBBATI (GSI/IReS)"— Presentation transcript:

1 07 October 2004 Hayet KEBBATI -1- Data Flow Reduction and Signal Sparsification in MAPS Hayet KEBBATI (GSI/IReS)

2 07 October 2004 Hayet KEBBATI -2- Pixel Sensors applied to vertex detector  Hybrid Pixel Detectors  Fast readout and radiation hardness device,  Sizeable pixel pitch due to readout circuitry surface,  High material budget.  Charge Coupled Devices -CCD-  High density due to reduced pitch size,  Poor radiation hardness and long readout time.  Benefits from constant decrease of technology size  higher pitch density,  Can be thinned down to the thickness wanted => less material budget compared to hybrid devices,  Fast readout and radiation tolerant compared to CCD,  But radiation hardness always far behind hybrid devices,  Cost-effective and easily available CMOS Process.  Monolitic Active Pixel Sensors -MAPS-

3 07 October 2004 Hayet KEBBATI -3- System on a Chip (SoC) Signal Processing Part Sensor Digital Part Analog part Interface Part (ADC)  At the first Silicon tracking Station (5cm), particle densities have values up to 2 hits/mm².event,  Fast readout (100ns/event)  Huge data flow 1.6 Tera bits/sec (output size=1 bit),  Hit Extraction and data sparsification  Data flow of 8 Giga bits/sec  Implementation of on-chip processing forming a System on Chip  Parallel readout  40 transmission lines per reticle (20mmx20mm), Freq=200 MHz (output size=1 bits) CMOS Sensor -MAPS- : Data Flow Reduction

4 07 October 2004 Hayet KEBBATI -4- Control and address Electronics Fast signal processing and data sparsification  Signal digitalisation Storage threshold values needed during data sparsification Surface ratio (B 2 /B 1 ) must be as small as possible Matrix of Pixel Control ELN Sparcifi cation Memori- sation Smart Detector Reticle Band Height of non- sensitive part B2B2 Sensitive part Control and processing part ADC Band Height of sensitive part B1B1

5 07 October 2004 Hayet KEBBATI -5- Charge Sensitive Element : CDS with clamping capacitor architecture o nwell/p-epi diode biased by a bias forward diode to convert particle charge to voltage, o Noise sources : shot noise, FPN, flicker noise and thermal => CDS technique o On pixel CDS and amplification => good signal to noise ratio and T readout =100ns. VA Vclamp vdd gnd SF sample read clamp Cac Cclamp Csample Vx 2 diodes’s Self reverse bias charge sensitive element SF Vout

6 07 October 2004 Hayet KEBBATI -6- Signal Sparsification Method Hit 2 3 Steps : 1) Scanning clusters of 3x3 pixels 2) Compare pixels and clusters with seed threshold and cluster threshold value 3) Extract valid clusters seed_thre=7 mv cluster_thre=20 mv

7 07 October 2004 Hayet KEBBATI -7- Hit output = W pix. 5 + W adr (cluster 5) W pix R occ Flow Reduction RatioData Flow/Reticle 3 bits4%67%200 Giga bits/sec 8%33% 10%17% 4 bits4%70%240 Giga bits/sec 8%40% 10%25% Hit output = W pix. 2 + W adr (heavy center, processing part surface>>) W pix R occ Flow Reduction RatioData Flow/Reticle 3 bits4%79%128 Giga bits/sec 8%57% 10%47% 4 bits4%82%144 Giga bits/sec 8%64% 10%55% Data Flow with On-chip Processing R occ is the hit occupancy rate = number of hits / total number of pixels W adr is the binary length of the address of the pixel position W pix is the binary length of the signal corresponding to the pixel voltage

8 07 October 2004 Hayet KEBBATI -8- 100 rows 1000 columns 1000 3bits ADC Seed pixel and cluster Comparisons Cluster Extraction Threshold values Memorisation Sub-bloc Detector Structure Pitch = 20 µm  Pixel Readout time = 100ns => Readout time = 10 µs => occupancy rate up to 8% at station 1 closest to the beam  Column parallel readout,  Digitalization of the output data of each column (3 bits ADC). (2 mm) (20 mm) Sensitive part Control and processing part

9 07 October 2004 Hayet KEBBATI -9- 8 OR Gates Tree 128 + + + + + + + + + + + + + + + + + + + + + + + + FSM FIFO 8 ADC counter OR Gates Tree 128 + + + + + + + + + + + + + + + + + + + + + + + + FSM FIFO 8 ADC 200 MHz 50 MHz 10 MHz  Surface = 20mm 2  Processing surface to sensitive surface ratio=1/2 Data Sparsification Implementation results (0.35 µm)

10 07 October 2004 Hayet KEBBATI -10- row decoder column decoder column mux, write buffers, sense amplifiers, DRAM cell write bit line gnd read bit line 3 T DRAM 3.5 x 5.5  m = 2.5 x 3.92 SDRAM Memory Strucure adr write data pre read adr data valid data Write Cycle Read Cycle

11 07 October 2004 Hayet KEBBATI -11- Memory of 512x26 bits in 0.25µm technology Regular layout with silicon surface saving Test data maintain time in DRAM cells Test of circuit behavior under radiation : number and type of errors  detection and correction bits Surface : 320µmx930µm Access delay : 2.5 ns Power dissipation: 7 mW SDRAM Implementation Results

12 07 October 2004 Hayet KEBBATI -12- Summary  Real-time data processing  Readout time = 10µs => hit occupancy rate up to 8% in worst case  Processing surface to sensitive surface ratio = ½  To improve the ratio : 1.Increase the pitch  hit occupancy rate rise 2.Parallel readout by 2 rows  High power dissipation  SDRAM design in 0.25 µm technology  Surface = 320µmx930µm  Access time = 2.5 ns Options to reduce hit occupancy:  Optimize STS geometry to avoid hot spots ? Use hybrid pixels in the hottest area


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