Electrical Engineering

at Fermilab

The Hidden Agenda Behind

All This Physics Stuff

Jim Hoffand

Farah Fahim

(Jim got too much credit on the poster)

Presented by:

Engi

neer

ing

vers

us

Phys

ics…

what

’s th

e re

al d

iffer

ence

?Engineerin

g

Physics

Engineers build machines.If, along the way, they happen to uncover some phenomena or help other people to do so…oh well, that was fun.

Physicists pursue phenomena.In order to do so, if they have to build some machines, that is just the cost of business

That

bei

ng

said

…

Engineering is

better

Electrical Engineering

is MUCH better.

For t

he re

st o

f th

e ta

lk

There are lots of types of electrical

engineering at Fermilab… Power Engineering RF Engineering Board Design Etc…etc…etc…For the remainder of the talk, we’ll focus

on Front End Electronics and Integrated

Circuit Design Engineering, largely

because it is widely regarded as the best,

most significant and most interesting

type of electrical engineering, but also

because it is what we do.No one said we couldn’t be biased in this

presentation…

Wha

t doe

s a

Phys

icist

see?

Physicists pursue phenomena so they SEE phenomena. They see particles and their interaction.

Wha

t doe

s an

Engi

neer

see?

Engineers see the machines. We see the hundreds and thousands of little detectors.

Wha

t doe

s an

Engi

neer

see?

Engineers see the machines. We see the hundreds and thousands of little detectors.

We see tiny puffs of charge that “magically” appear at the inputs of our electronics. On some level we really don’t care where they come from.

It is also significant that, at least at first, there is NO ORDER to what we find and there can be a LOT of noise. Order must be extracted and noise must be suppressed.

Wha

t doe

s an

Engi

neer

see?

Engineers see the machines. We see the hundreds and thousands of little detectors.

“Tin

y Pu

ffs o

f Ch

arge

”? R

eally

? For example:LAr Detectors like LBNE10000 electrons

Pixel Detectors in CMS1000 electronsCCD Detectors in CDMS A few electrons

Wha

t do

we d

o wi

th

thes

e tin

y pu

ffs o

f ch

arge

?

Limita

tions

GeometrySizeNeighborhoodTime

Power

How do we get this done?

Shut

up

and

let

Fara

h ta

lk…

Rem

embe

r thi

s?

This

is wh

ere

we

star

t…

Every 25ns…Most of these events are meaningless, and the amount of information gathered is staggering, so we have to discard most of it.

Still, when we find something interesting, we have to turn this…

Into

this…

We have to extract the significant particles from the meaningless ones and from the noise.

How?

The desire for high momentum tracks allows us to narrow the scope to a set of towers

Simulations prior to experimentation allow us to predict patterns of hit detectors that indicate a significant track amid all the noise.

Real

Tim

e Tra

ck

Findi

ng

For simplicity, we will look at this in 2 dimensions rather than 3.

Layers correspond to, for example, each set of concentric cylinders within the tracking detector.Imagine simulating all conceivable tracks within this space and then recording those tracks in a Pattern Recognition Associative Memory.

Wha

t is a

Pat

tern

Re

cogn

ition

As

socia

tive

Mem

ory?

Ordinary read-only memories

respond to a new address

presented at its inputs with

the data corresponding to that

address. Someone gives it an

address and the ROM responds with data. Simple.

Associative Memories respond

to data with data.A single piece of data given to

an associative memory could

result in several associations

or it could result in none.

Wha

t is a

Pat

tern

Re

cogn

ition

As

socia

tive

Mem

ory?

Pattern Recognition Associative

Memories take it one step

further.Data is first subdivided into

categories. For example, hair

color, eye color, height and

weight.Data is only matched within

category. For example, hair

color data is only matched

against hair color patterns. Once a match is found in each

category, we have found a

potentially interesting pattern.

Patte

rn

Reco

gniti

on in

HEP

Our categories are detector layers.Our data are detector addresses within each detector layer.Given a pattern recognition associative memory with enough patterns to cover the tower and with the speed necessary to match patterns in the time allowed, we can do the job.

High

-Spe

ed P

atte

rn

Reco

gniti

onLayer 1

Address 4 Mat

chLayer 1Address 4 M

atch

Mat

ch

Layer 3Address 7

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ch

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chLayer 3Address 7

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ch

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ch

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ch

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chLayer 3Address 9

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ch

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ch

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ch

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chLayer 3Address 9

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ch

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ch

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ch

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chM

atch

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ch

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ch

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ch

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ch

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ch

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ch

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ch

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atch

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ch

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ch

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ch

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ch

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ch

Road!

The CAM Cell

• In fact, a direct implementation of the figure on the preceding page proved to be possible and it is shown here. To the left is a floorplan of the layout and to the right is the layout itself.

• This implementation brings out several features of the VIPRAM not immediately obvious. First, unlike the classical 2D PRAM architecture which is in a straight line, the resultant square layout of the 3D VIPRAM permits routing of signals from left, right, top and bottom. Second, the matchline of the CAM cell itself is shortened. In the TIPP paper, we talk about the shortening of the Stored Matchlines (Page 7, below Figure 4) and indicate that this will reduce power. Frankly, we were wrong. The Stored Matchlines do not change state rapidly, so they don’t draw much power. However, the CAM match lines run at 100+ MHz, and reducing their parasitic capacitance dramatically reduces the system power consumption.

• None of this was disclosed publicly at TIPP.

matchLine

The Control Cell (Majority Logic)

• A direct implementation of the Majority Logic as shown on Slide 9 is also possible. To the left is a floorplan of the layout and to the right is the layout itself.

Final

3D

Impl

emen

tatio

n

Conc

lusio

ns

Engineers build machines,

and the accelerators and detectors in HEP are among

the most complex machines

in history.In fact, these machines are

themselves composed of smaller machines that are,

each in their own right, enormously complex.

All joking aside, this place is

an engineer’s playground.