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Online Triggers and  DAQ Online Triggers and  DAQ

Online Triggers and DAQ - PowerPoint Presentation

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Online Triggers and DAQ - PPT Presentation

openlab V Niko Neufeld CERNPH CERN openlab major review Oct 2014 Data acquisition and online challenges recap Online data filtering and processing quasi realtime data reduction for highrate detectors ID: 782365

data daq openlab lightning daq data lightning openlab neufeld online 100 level trigger detector processing rate high compute gbit

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Slide1

Online Triggers and DAQopenlab V

Niko Neufeld, CERN/PH

CERN

openlab

major review Oct. 2014

Slide2

Data acquisition and online challenges - recap

Online data filtering and processing(quasi-)

realtime data reduction for high-rate detectorsHigh bandwidth networking for data acquisitionTerabit/s networks

Data-transfer and storage

openlab V lightning DAQ N. Neufeld

2

Slide3

Evolution of the LHCb trigger-DAQopenlab V lightning DAQ N. Neufeld

LHCb Run

2

LHCb Run 3

Max. inst. luminosity

4 x 10^32

2 x 10^33

Event-size (mean –

zero-suppressed) [

kB

]~ 60 (L0 accepted) ~ 100 Event-building rate [MHz]1 40# read-out boards~ 330400 - 500link speed from detector [Gbit/s]1.64.5output data-rate / read-out board [Gbit/s]4 100 # detector-links / readout-boardup to 24up to 48# farm-nodes~ 16001000 - 4000# links 100 Gbit/s (from event-builder PCs)n/a400 - 500final output rate to tape [kHz]1220 - 100

3

Slide4

Detector front-end electronics

Eventbuilder network

Eventbuilder PCs + software LLT

Eventfilter Farm

~ 80 subfarms

UX85B

Point 8 surface

subfarm

switch

TFC

500

6 x 100 Gbit/s

subfarm

switch

Online storage

Clock & fast commands

8800

Versatile Link

throttle from PCIe40

Clock & fast commands

6 x 100 Gbit/s

Online Architecture

ECS

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Slide5

Event-size [kB]

Rate [kHz]

Bandwidth [Gb/s]

Year [CE]

ALICE

20000

50

8000

2019

ATLAS

400020064002023CMS40001000320002023LHCb

100

40000

32000

2019

Future data rates @ LHC (trigger stage 2)

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40000 kHz == collision rate

LHCb abandons Level 1 for an all-software trigger

O(100)

Tbit

/s networks required

Slide6

Project HTCC (High Throughput Computing Collaboration)

Partners: CERN,

intel

Goal apply

intel

technologies to Online computing challenges

Work-packages

Interconnect

for DAQ

(

Stormlake)Knights Landing for software triggers (HLT and L1.5)Reconfigurable Logic (Xeon/FPGA)Use LHCb use-case as concrete example problems, but try to keep solutions and reports as widely applicable as possibleopenlab V lightning DAQ N. Neufeld6

Slide7

Original “Use-cases” in Online (from openlab V white paper)

“Level-1” using (more/all) COTS hardware

Data Acquisition

“High Level Trigger

“Controls”“Online data processing” ✔“Exporting data”openlab V lightning DAQ N. Neufeld7✔ == covered in HTCC

Slide8

Additional material

Slide9

Use-case #1 The first level trigger

Slide10

Calorimeter data

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Slide11

Finding Muons (2d view)

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Slide12

Level 1 Trigger today

The Level 1 Trigger is implemented in hardware: FPGAs and

ASICs  difficult / expensive to upgrade or change, maintenance by experts only

Decision time:

~ a small number of microseconds

It uses simple, hardware-friendly signatures

 looses interesting collisions

Each sub-detector has its own solution, only the uplink is

standardized

openlab V lightning DAQ N. Neufeld12

Slide13

Level 1 challenge

Can we do this in software? Using GPGPUs / XeonPhis?

We need low and near– deterministic latency Need an efficient interface to detector-hardware: CPU/FPGA hybrid?

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Slide14

Use-case #2 and #6Data Acquisition and Export  fast data transport

Slide15

Data Acquisition (generic example)

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custom radiation- hard link from the detector

DAQ (“event-building”) links – some LAN (10/40/100

GbE

/

InfiniBand

)

Links into compute-units: typically 1/10 Gbit/s Detector

DAQ network

100 m rock

Readout Units

Compute Units

Every Readout Unit has a piece of the collision data

All pieces must be brought together into a single compute unit

The Compute Unit runs the software filtering (High Level Trigger – HLT)

10000 x

~ 1000 x

~ 3000 x

Slide16

Data acquisition challenge

Transport large amount of data (multiple Terabit/s @ LHC) reliably and cost-effectivelyIntegrate the network closely and efficiently with compute resources (be they classical CPU or “many-core”)

Multiple network technologies should seamlessly co-exist in the same integrated fabric (“the right link for the right task”), end-to-end solution from online processing to scientist laptop (e.g. light-sources)

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Slide17

Use-case #3 and #5Online Data processing

Slide18

Pattern finding - tracks

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Slide19

Same in 2 dimensions

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Can be much more complicated: lots of tracks / rings, curved / spiral trajectories, spurious measurements and various other imperfections

Slide20

LHC High Level Trigger: Key Figures

Existing code base: 5 MLOC of mostly C++

Almost all algorithms are

single-threaded

(only few exceptions)

Currently processing time on a X5650 per event: several 10

ms

/ process (hyper-thread)

Currently between 100k and 1 million events per second are filtered online in each of the 4 LHC experiments

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Slide21

Online Data processing challenge

Make the code-base ready for multi/many-core (this is not Online specific!)Optimize the online processing compute in terms of cost, power, cooling

Find the best architecture integrating “standard servers”, many-core systems and a high-bandwidth network

openlab V lightning DAQ N. Neufeld

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