CS184a: Computer Architecture (Structures and Organization) Day6: October 11, 2000 Instruction Taxonomy VLSI Scaling Caltech CS184a Fall2000 -- DeHon.

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Transcript CS184a: Computer Architecture (Structures and Organization) Day6: October 11, 2000 Instruction Taxonomy VLSI Scaling Caltech CS184a Fall2000 -- DeHon.

CS184a:
Computer Architecture
(Structures and Organization)
Day6: October 11, 2000
Instruction Taxonomy
VLSI Scaling
Caltech CS184a Fall2000 -- DeHon
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Last Time
• Computing requirements
• Instruction requirements
• Structure
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Today
• Instruction Taxonomy
• VLSI Scaling
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Instruction Distribution
• Beyond 64 PE, instruction bandwidth
dictates PE size
PEarea 4N
=N
(648l)
PEarea =16Kl2N
• Build larger arrays
processing elements become less dense
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Instruction Memory
Requirements
• Idea: put instruction memory in array
• Problem: Instruction memory can quickly
dominate area, too
– Memory Area = 641.2Kl2/instruction
– PEarea = 1Ml2 + (Instructions)  80Kl2
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Instruction Pragmatics
• Instruction requirements could dominate
array size.
• Standard architecture trick:
– Look for structure to exploit in “typical
computations”
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Two Extremes
• SIMD Array
(microprocessors)
– Instruction/cycle
– share instruction across
array of PE s
– uniform operation in
space
– operation variance in
time
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• FPGA
– Instruction/PE
– assume temporal
locality of instructions
(same)
– operation variance in
space
– uniform operations in
time
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Hybrids
• VLIW (SuperScalar)
– Few pinsts/cycle
– Share instruction across w bits
• DPGA
– Small instruction store / PE
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Architecture Instruction Taxonomy
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Instruction Message
• Architectures fall out of:
– general model too expensive
– look for structure in common problems
– exploit structure to reduce resource
requirements
• Architectures can be viewed in a unified
design space
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VLSI Scaling
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Why Care?
• In this game, we must be able to predict the
future
• Rapid technology advance
• Reason about changes and trends
• re-evaluate prior solutions given technology
at time X.
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Why Care
• Cannot compare against what competitor
does today
– but what they can do at time you can ship
• Careful not to fall off curve
– lose out to someone who can stay on curve
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Scaling
• Premise: features scale “uniformly”
– everything gets better in a predictable manner
• Parameters:
 l (lambda) -- Mead and Conway (class)
– S -- Bohr
– 1/k -- Dennard
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Feature Size
l is half the minimum
feature size in a VLSI
process
[minimum feature
usually channel width]
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Scaling
•
•
•
•
•
Channel Length (L)
Channel Width (W)
Oxide Thickness (Tox)
Doping (Na)
Voltage (V)
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Scaling
•
•
•
•
•
Channel Length (L)
l
Channel Width (W)
l
Oxide Thickness (Tox) l
Doping (Na)
1/l
Voltage (V)
l
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Effects?
•
•
•
•
•
•
•
•
Area
Capacitance
Resistance
Threshold (Vth)
Current (Id)
Gate Delay (tgd)
Wire Delay (twire)
Power
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Area
 l -> l/k
 A=L*W
 A -> A/k2
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 0.35mm -> 0.25mm
• 50% area
• 2x capacity same area
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Area Perspective
[2000 tech.]
18mm18mm
0.18mm
60G l2
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Capacitance
• Capacitance per unit
area
– Cox= eSiO2/Tox
– Tox-> Tox/k
– Cox -> k Cox
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Capacitance
• Gate Capacitance
–

–
–
Cgate= A*Cox
A -> A/k2
Cox -> k Cox
Cgate -> Cgate /k
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Threshold Voltage
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Threshold Voltage
• VTH-> VTH /k
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Current
• Saturation Current
– Id=(mCOX/2)(W/L)(Vgs-VTH)2
–
–
–
–
Vgs=V-> V /k
VTH-> VTH /k
W-> W/k
Cox -> k Cox
– Id-> Id/k
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Gate Delay
 tgd=Q/I=(CV)/I
• V-> V /k
• Id-> Id/k
• C -> C /k
 tgd -> tgd /k
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Resistance
• R=rL/(W*t)
• W-> W/k
• L, t similar
• R -> k R
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Wire Delay
 twire=RLC
• R -> k R
• C -> C /k
• …assuming (logical)
wire lengths remain
constant...
 twire -> twire
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Power Dissipation (Static)
• Resistive Power
– P=V*I
– V-> V /k
– Id-> Id/k
– P-> P /k2
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Power Dissipation (Dynamic)
• Capacitive
(Dis)charging
• Increase Frequency?
– f -> kf ?
– P=(1/2)CV2f
– V-> V /k
– C -> C /k
– P -> P/k2
– P-> P/k3
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Effects?
•
•
•
•
•
•
•
•
Area
1/k2
Capacitance
1/k
Resistance
k
Threshold (Vth) 1/k
Current (Id)
1/k
Gate Delay (tgd) 1/k
Wire Delay (twire) 1
Power
1/k2-> 1/k3
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Delays?
• If delays in gates/switching?
• If delays in interconnect?
• Logical interconnect lengths?
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Delays?
• If delays in gates/switching?
– Delay reduce with 1/k [l]
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Delays
• Logical capacities growing
• Wirelengths?
– No locallity->k
– Rent’s Rule
• L ->n(p-0.5)
• [p>0.5]
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Capacity
•
•
•
•



Rent: IO=C*Np
p>0.5
A= C*N2p
Logical Area ->k2
k2 A= C*N22p
k2 N2p = N22p
N2 = k(1/p) N
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• Sanity Check
– p=1
– N2 = kN
– p~0.5
– N2 ~ k2 N
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Compute Density
• Density = compute / (Area * Time)
 k3>compute density scaling>k
 k3: gates dominate, p<0.5
 k2: moderate p, good fraction of gate delay
 k : large p (wires dominate area and delay)
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Power Density
• P-> P /k2 (static, or increase frequency)
• P-> P/k3 (dynamic, same freq.)
 A -> A/k2
• P/A -> P/A … or … P/kA
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Physical Limits
• Doping?
• Features?
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Physical Limits
• Depended on
– bulk effects
• doping
• current (many electrons)
• mean free path in conductor
– localized to conductors
• Eventually
– single electrons, atoms
– distances close enough to allow tunneling
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Finishing Up...
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Big Ideas
[MSB Ideas]
• Instruction organization induces a design
space (taxonomy) for programmable
architectures
• Moderately predictable VLSI Scaling
– unprecedented capacities/capability growth for
engineered systems
– change
– be prepared to exploit
– account for in comparing across time
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Big Ideas
[MSB-1 Ideas]
• Uniform scaling reasonably accurate for
past couple of decades
• Area increase k2
– Real capacity maybe a little less?
• Gate delay decreases (1/k)
• Wire delay not decrease, maybe increase
• Overall delay decrease less than (1/k)
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