Power Issues in On-chip Interconnection Networks
Mojtaba AmiriNov. 5, 2009
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Why Interconnection Networks?
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Interconnection Networks Issues
– Performance, Reliability– Power Consumption
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Papers
• PowerHerd: A distributed scheme for dynamic satisfying peak power constraints in interconnection networks
• Dynamic voltage scaling with links for power optimization of interconnection networks
By L. Shang, L.-S. Peh, and N. K. Jha
ECE, University of Princeton
PowerHerd: A Distributed Scheme for Dynamically Satisfying Peak-Power
Constraints in Interconnection Networks
By
L. Shang, L.-S. Peh, and N. K. JhaDepartment of Electrical Engineering
Princeton University
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Introduction (1)
• Problem • Peak-power constrains
• Solution• PowerHerd
– Distributed and run-time– Modified router
•
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Introduction (2)– An Example
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PoweHerd Router Architecture
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PoweHerd Router MechanismPLPB =PGPB/# Routers
Estimate PLPB Predict PLPB
Calculate Shared power
Negotiation with neighbors and share power
Update PLPB
Throttle switch
allocator
Update routing decision
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Dynamic Power Estimation
• Power dominators:– Input Buffer– Crossbar Switch– Link
Based on Switching activity,
Number,Coefficients from linear
regression
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Estimation Error
• Orion error 2-3% Total 10%
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Leakage Power Estimation
• Leakage Power is about 10%. (Critique)
Based on• Switching activity,• Number,• Coefficients from linear regression
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Dynamic Power Prediction
W around 4 3 Hardware Simplification
By shift and add
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Dynamic Power Sharing (Protocol)
TGPB/N
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Dynamic Power Sharing (2)
1/2
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Dynamic Power ThrottlingNear the local power budget Simple gating (Critique)
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Power-aware Routing
• Previous routing algorithms– Performance– Fault-tolerance
• This routing algorithm considers power consumption of neighbors– Low overhead
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Result Comparison-IdealMaxPower
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Result Comparison-StaticAllocPower
Global
Power
budget
136.3 W
27.3 W
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Effect of Power-Sharing Interval
Global
Power
budget
136.3 W
53.3W
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Effect of Local Power Constraints
PGPB = 136.3 W
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Different Topologies
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Summary
• PowerHerd– Distributed Scalable– Online (Dynamic) Efficient– Guarantee Peak-Power Constrain The Issue– Help other techniques
Dynamic Voltage Scaling with Links for Power Optimization of Interconnection
Networks
By
L. Shang, L.-S. Peh, and N. K. JhaDepartment of Electrical Engineering
Princeton University
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Introduction
• Power saving technique– Employs DVFS Links (the first attempt)
• How? Based on history of previous actions• Performance penalty– 2.5 throughput– 15.2 average latency
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DVFS Link
C= 5usn = .9
• Characteristics of a DVFS link– Transition time (100 link clock cycles)– Transition energy– Transition status– Transition step
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Communication Traffic Charc.
Link Utilization (LU)
Congestion
What is the Problem with this model?
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CTC- Input Buffer Utilization
Congestion
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Input Buffer Age
Congestion
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Prediction Policy
• LU & BU together is enough• DVFS based on two steps
• First Link Utilization• Second congestion
• Simple Implementation
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Hardware Implementation
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Effect of DVS on power-performance
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Effect of thresholds on power-performance
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Effect of DVFS links with varying Char.
Task
Duration
1ms
0.1 us
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Summary
• Appling DVFS to Interconnection networks• History-based DVFS (LU, BU)• Power saving HUGH!• First study
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Critiques to PoweHerd
• Consider static power 10% now is much more!
• Gate-level design for traffic throttling is not realistic.
• Completely Distributed; suggestion hybrid!
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Critiques to DVFS Link
• There is no 100% guarantee to find the optimum for History-Based Policy
• This method works because the link is supposed to be power dominator! Inconsistent with first paper.
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Comparisons of the Two Papers
PowerHerd DVFS Link
Target Peak Power Constrain Power Consumption
Performance Penalty Yes Yes
Power Technique Power –aware routing, Dynamic power throttling
DVFS
Improvement 100% guarantee 6 times saving
Inconsistent Assumptions(most power dominator)
Input Buffers Links