l i a b l eh k C o m p u t i n gL a b o r a t o r y

AgeSim: A Simulation Framework AgeSim: A Simulation Framework for Evaluating the Lifetime Reliabifor Evaluating the Lifetime Reliabi

lity of Processor-Based SoCslity of Processor-Based SoCs

Presenter: Lin HuangPresenter: Lin Huang

Lin Huang and Qiang Xu

CUhk REliable computing laboratory (CURE)

The Chinese University of Hong Kong

Lifetime Reliability Becomes A Serious Lifetime Reliability Becomes A Serious ConcernConcern

Useful life

Fai

lure

rat

e

Infantmortality

180nm130nm90nm

~ 7 year[T. M. Mak]

< 7 year ~ 10 year

Time

WearoutFailure mechanisms

Electromigration

NBTI

TDDB

Reliability-related factors

Temperature

Supply voltage

Frequency

Design-Stage Decisions Affect Lifetime Design-Stage Decisions Affect Lifetime ReliabilityReliability

Functionality Power consumption Area constraint Thermal issue Expected service life …

SPECIFICATION

IC

DPM / DTMDVFS

Timeout

Thermal throttling

Power gating

…

RedundancyLevel

Quantity

…

Task AllocationRound-robin

Optimized

…

Without an efficient yet accurate lifetime reliability simulation framework,making the good decisions is extremely difficult if not impossible !

The Challenges in Simulation-Based The Challenges in Simulation-Based Lifetime Reliability AnalysisLifetime Reliability Analysis

Increasing failure rate

Exponential distribution assumption in previous work

Time

Fai

lure

rat

e

Useful lifeInfant

mortality Wearout

The Challenges in Simulation-Based The Challenges in Simulation-Based Lifetime Reliability AnalysisLifetime Reliability Analysis

Operational temperature varies significantly and rapidly

Obtained with HotSpot 4.0 [Huang-ieeetc08]

How to achieve efficient yet accurate lifetime reliability simulation with such limited information, when failure mechanisms follow arbitrary failure distributions?

Key IdeaKey Idea

General failure distribution with general scale parameter by which time is divided Example: Weibull failure distribution

Suppose we can express the reliability function as

and can be computed according to limited tracing information Example: reliability function

Key IdeaKey Idea

Aging rate Capture the impact of certain usage strategy

Reliability-related usage strategy A combination of …

Dynamic power/thermal managementTrigger mechanismLoad-sharing strategy

… given the application flow with certain characteristic

Key IdeaKey Idea

Temperature

Supply voltage

Frequency

USAGESTRATEGY

FuturePast

Representative workload

Aging rate

Key IdeaKey Idea

FuturePast

Representative workload

Proposed Simulation Framework: AgeSimProposed Simulation Framework: AgeSim– Step One: Simulation and Tracing– Step One: Simulation and Tracing

ExecutionMode

Power(Data)

Temperature(Data)Power /

ThermalManager

TemperatureSimulator

PowerSimulator

Power StateMachine

TriggerMechanism

ApplicationFlow

Load-sharingStrategy

RedundancyScheme

time step

Proposed Simulation Framework: AgeSimProposed Simulation Framework: AgeSim– Step One: Simulation and Tracing– Step One: Simulation and Tracing

Power StateMachine

TriggerMechanism

ApplicationFlow

Load-sharingStrategy

RedundancyScheme

Power /ThermalManager

TemperatureSimulator

PowerSimulator

ExecutionMode

Power(Data)

Temperature(Data)

Reliability-Related Factors

Trace File

Proposed Simulation Framework: AgeSimProposed Simulation Framework: AgeSim– Step Two: Aging Rate Calculation– Step Two: Aging Rate Calculation

&

&

Reliability-Related Factors

Trace File

Aging rate

Model ValidationModel Validation

By average temperature28.3% error in MTTF

By AgeSimalmost identical results

Case Study ICase Study IDynamic Voltage and Frequency ScalingDynamic Voltage and Frequency Scaling

DVFS1 Low voltage: 90%Vdd

DVFS2 Low voltage: 80%Vdd

No DVFS

HVIdle

HVRun

Task departure

Task arrival

LVIdle

LVRun

Task departure

Task arrival

T>TH T<TL

Case Study ICase Study IDynamic Voltage and Frequency ScalingDynamic Voltage and Frequency Scaling

System load The ratio between task arrival rate and service rate

Case Study ICase Study IDynamic Voltage and Frequency ScalingDynamic Voltage and Frequency Scaling

System load The ratio between task arrival rate and service rate

Case Study IICase Study IITask Allocation on Multi-Core ProcessorsTask Allocation on Multi-Core Processors

Random allocation

Performance-aware allocation Always choose the

available core with highest frequency

[Sarangi-ieeetsm08]

Example Chip Frequency Map

Case Study IICase Study IITask Allocation on Multi-Core ProcessorsTask Allocation on Multi-Core Processors

System load The ratio between task arrival rate and service rate

Discussion on the Flexibility of Discussion on the Flexibility of AgeSimAgeSim

Task allocation and scheduling for MPSoC under lifetime reliability constraint

Multiprocessor with different redundancy schemes Example: gracefully degrading redundancy, standby redundancy

ConclusionConclusion

Lifetime reliability has become a serious concern for high-performance ICs

Design stage decisions significantly affect system reliability

We propose an efficient yet accurate simulation framework to evaluate the system reliability under various usage strategy Arbitrary failure distribution Fine-grained tracing for representative workloads

AgeSim is effective and flexible

AgeSim: A Simulation Framework for EvaluatiAgeSim: A Simulation Framework for Evaluating the Lifetime Reliability of Processor-Based ng the Lifetime Reliability of Processor-Based

SoCsSoCs

Thank you for your attention !Thank you for your attention !

Backup SlidesBackup Slides

Multiple representative workload Aging rate Accuracy Key idea

Multiple Representative WorkloadsMultiple Representative Workloads

The proposed method could be easily extended to analyze the system with multiple representative workloads

We can organize the workloads into a hyper-workload with their occurrence probabilities

We can extract the aging rate and occurrence probability for each workload and then compute the unified aging rate by

Aging RateAging Rate

Time

Fai

lure

rat

e Aging rate is independent of time

AccuracyAccuracy

Key IdeaKey Idea

Power StateMachine

TriggerMechanism

ApplicationFlow

Load-sharingStrategy

RedundancyScheme

Processorusage strategy

Power StateMachine

TriggerMechanism

ApplicationFlow

Load-sharingStrategy

RedundancyScheme

Agingrate

Reliabilityfunction