27
An Integrated Thermal Estimation Framework for Industrial Embedded Platforms Andrea Calimera Andrea Acquaviva Alberto Macii Enrico Macii Massimo Poncino Politecnico di Torino STMicroelectronics Matteo Giaconia Claudio Parrella

An Integrated Thermal Estimation Framework for Industrial

  • Upload
    others

  • View
    3

  • Download
    0

Embed Size (px)

Citation preview

Page 1: An Integrated Thermal Estimation Framework for Industrial

An Integrated Thermal Estimation Framework for Industrial Embedded Platforms

Andrea Calimera

Andrea Acquaviva

Alberto Macii

Enrico Macii

Massimo Poncino

Politecnico di Torino STMicroelectronics

Matteo Giaconia

Claudio Parrella

Page 2: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 2

Thermal Issues

DIFFICULTIES IN DISSIPATING HEAT

DIFFICULTIES IN

DISSIPATING HEAT

POWER

CONSUMPTION

POWER

CONSUMPTION

THERMAL ISSUES• High Operating Temperature• Large Temperature Gradient

CIRCUIT

PERFORMANCE

CIRCUIT

PERFORMANCERELIABILITY and

AGING

RELIABILITY and

AGING

Technology scaling

MORE GENERATED HEAT

MORE GENERATED

HEAT

Efficient application of these techniques requires fast thermal estimations at each stage of the design flow

Intrusive thermal-aware design techniques are required at each level of abstraction

Page 3: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 3

� Intrusive thermal-aware design techniques have become a

must in modern SoCs, at each level of abstraction

� application level (e.g., thermal aware task migration)

� system level (e.g., 3D ICs, packaging, heat spreading)

� architectural level (e.g., Measure & Control techniques - DVFS)

� temperature monitors

� knobs which implement control strategies

� Efficient application of these strategies requires fast estimation of thermal effects in the earlier stages of the SoC

design flows

� spatial&temporal gradients

� peak operating temperature and hotspotsA thermal estimation framework which integrates heterogeneous info - at design time - is missing in today’s flow

Thermal Aware Design

Page 4: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 4

� An ideal thermal estimator... just alchemy?

� Why it is so hard... an industrial test case

� Power/thermal estimation flow

� What you can do

� Single component analysis

� Component interaction analysis

� Conclusions

Outline

Page 5: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 5

THERMAL ESTIMATOR

THERMAL ESTIMATOR

PO

WE

R

ES

TIM

AT

OR

PO

WE

R

ES

TIM

AT

OR

fast & accurate

dynamic + leakage

Heterogeneous Thermal Estimator

SYSTEM CONFIGURATION

SYSTEM CONFIGURATION

SYSTEMSYSTEM

RTLRTL

GATEGATE

APPLICATIONAPPLICATION SoC

PHYSICALPHYSICAL

THERMAL MODELS

THERMAL

MODELS

WORKLOADWORKLOAD

thermal profile

thermal-aware

design

sensors&knobs

power domains

packaging&heat sinks

battery sizing

feedback

Page 6: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 6

ST Spear 1300 MPU: Mean Features

� Designed for cost-sensitive applications requiring significant

processing and connectivity capabilities at low power

consumption

� networking/home gateways (eth and WiFi interface)

� embedded media and imaging (camera interface, LCD/touch screen

controller, audio codecs)

� Architecture

� ARM A9 Cortex dual-core power-optimized 800MHz

� 512KB L2 Cache

� Serial Management Interface (SMI - IP)

� One-time programmable logic (anti-fuse)

� 300KB SRAM Memory

Page 7: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 7

300KB

High Speed

AC

P

UHC (2)

UOC

GMAC

MultiLayer Interconnect MatrixMultiLayer Interconnect Matrix

EX

PA

NS

ION

INT

ER

FA

CE

SPEAr1300

Low Speed

10

70

Basic

50

Application

C A B D

10/10020/50 35/80 30

10 20 35 5575 80

10 20 50 80

10/2050/5570/75

30/354060

KBD

I

81

100

I2S(2)

I2C

SSP

FSMC

UART

RAM

JPGC

1.3 Mgates1.3 Mgates

100

80

F

G

61

72

RAS

LCD

10/10020/7540/80

70

6060

ADC

80 10 20 30 35 40 55 50 60 70

75

Misc

GPIO(2)

RTC

GPT(4)

20

SMI

ROM

40

SATA/PCIe0

MCIF

C3

55

L2CC

FPU PTM i/f

Cortex A9

I-cache

32KB

D-cache

32KB

FPU PTM i/f

I-cache

32KB

D-cache

32KB

ABI

SCU GIC

A9SM

WD

/T

IME

R Cortex A9

WD

/T

IME

R

10100

60

50/55/80

70/75

30/35/40

20/110

16/32 (ECC)

SDRAM

Controller

DDR 2/3

H

L

K

J

M

N

CFG

30

7535

R

DMAC

L2 cache (512KB)

110

DMAC

110 30 35 40

55 50 70 75 80 110

SATA/PCIe

1

SATA/PCIe

2

I

Page 8: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 8

ST Spear 1300 MPU: Low-Power

� Advanced power savings features

� Multiple power mode: Normal,

Slow, Sleep mode

� CPU clock with software programmable frequency

� Multiple power domains

� Dual-core CPU

� configurable logic

� PCI controllers

� Memories

� I/O peripheral

� 2 levels of coarse-grain clock-

gating structures for each power

domain

� Power-aware physical synthesis using low-power libraries with dual

threshold voltage cell usage

Page 9: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 9

� A smart power estimator should be able to integrate mixed

information obtained using different techniques at different

steps of the design flow

physical infofloorplan

process

physical info

floorplanprocess

SRAM

info form data-sheet

�Area, Access time

�Leakage, Dynamic per cycle

SRAM

info form data-sheet

�Area, Access time

�Leakage, Dynamic per cycle

ARM-LP + Cache-L1

info form data-sheet

�Area, Frequency

�Leakage, Dynamic VS Power-Mode

ARM-LP + Cache-L1

info form data-sheet

�Area, Frequency

�Leakage, Dynamic VS Power-Mode

Heterogeneous Power Information

Synthesizable IP

gate-level power estimation

based on STD timing/power

library

Synthesizable IP

gate-level power estimation

based on STD timing/power

library

Cache-L2

info form data-sheet

�Area, Access time, Latency

�Leakage VS PowerMode

�Dynamic power per cycle

Cache-L2

info form data-sheet

�Area, Access time, Latency

�Leakage VS PowerMode

�Dynamic power per cycle

Page 10: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 10

Example of Power Information

� Global figures

� Per process (fast, nominal)

� Per temperature (75°C, 125°C)

� Leakage & dynamic power

Page 11: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 11

Power Information: Per Component

� Per component

information

� Hard macros (red)

� Synthesizable logic (yellow)

Page 12: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 12

Power/Thermal Estimation Flow

� An unique environment based on Matlab Simulink® which

integrates different power estimation techniques and interfaces with a thermal library

1. Activity Modulation Blocks (AMBs)

2. Power Management Blocks (PMBs)

3. Power Computation Blocks (PCBs)

4. Temperature Computation Blocks (TCBs)

ACTIVITY

MODULATION

ACTIVITY

MODULATIONPOWER

COMPUTATION

POWER COMPUTATION

1

3

FLOORPLAN-LIKE INFORMATION

FLOORPLAN-LIKE INFORMATION

THERMAL

LIBRARY

THERMAL

LIBRARY

THERMPERATURE

SENSORS EMULATION

THERMPERATURE

SENSORS EMULATION

4

4POWER/THERMAL

MANAGER

POWER/THERMAL

MANAGER 2

Page 13: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 13

Activity Modulation Blocks (AMBs)

� AMBs set the utilization profiles (statically or dynamically)

of the system components

� Implemented using Simulink Stateflow®

� design environment for state charts and flow diagram

� can interface with cycle accurate simulators (MPARM-Scope-SIMICS)

� For each component of the SoC

� the functionality is described as a finite state machine

� the activity is defined as states and transitions among theme triggered by self-generated or asynchronous external events

Component AMBs Output

IPs FSM Switching activity over time

Hard Macro Power-State Machine Power-state currently in use

Memory Memory access emulation of a trace # read/write operation cycles

Page 14: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 14

Power Management Blocks (PMBs)

� PMBs simulate the implementation of power and thermal

management policies

� Implemented using Matalb Simulink®

� Interact with AMBs, PCBs and TCBs

� take the activity information from AMBs and the thermal information coming from the thermal feedback

� decide when to enter a certain power state configuration

� the power configuration is used inside PCBs to compute actual power consumption

� e.g., if a component is idle (info from AMBs), it is turned into a power-gating state (by PMBs); this info will be used to calculate the effective power consumption (info to PCBs)

14

Page 15: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 15

Thermal Computation Blocks (TCBs)

� PCBs compute dynamic and leakage power consumption

� Implemented using different techniques depending on the type of components and the power characterizations available

COMPONENT AVAILABLE INFO DESCRIPTION

Core processor + L1 cache

Power state information

� It is the only info available for hard macros� Power consumption quantified for the given tech. and for various corner cases (WC, NOM, BC, temperature)� Static and available for each power mode

Memories (L2 cache, SRAM)

Energy per read/write cycle

� Total leakage and dynamic power per cycle for various corner cases and operating conditions (Voltage, Temp.)

Synthesizable IPs

Gate-level netlist + switching activity analysis + tech.libs

� Accurate power estimation using standard library characterization provided by silicon vendors� Statistical analysis is performed by imposing a probabilistic switching activity on the input ports of the IP

Page 16: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 16

Thermal Computation Blocks (TCBs)

� TCBs provide thermal estimation exploiting information about component area and position

� power consumption data are sampled at predefined time intervals (speed/accuracy)

and converted into power-density

� data are fitted into the thermal library and an

equivalent RC electrical model is generated

� emulated sensors provide temperature

(voltage measurement on the RC model)

sisi

si

si

si

si

si

si

si

Cu cucu cu cu

powe

r

Page 17: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 17

Industrial Thermal Characterization

� Thermal analysis report on fabricated chips:

� Global parameter about heat dissipation

efficiency

� Theta j-a (junction-

ambient)

How many degrees between ambient and spreader to dissipate 1W

Tamb = 300K

Theta=24°C

Tchip = 324K

Page 18: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 18

Single Component Analysis

� A component is selected using the component selection mask,

while the rest of the chip remains at a given initial temperature

� Used for two purposes

� simulate a realistic functional behavior for a specific use case or power management configuration

� evaluate the the self-heating that specific component independently from the surroundings

� Serial Management Interface (SMI)

� Power oriented dual-Vth synthesis

� STMicrolectronics 65nm STM tech.

� Power characterization under different PVT corners

Page 19: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 19

Exploiting the Thermal Feedback

� Dynamic and Leakage power

characterization under

different input activity

� Temperature-aware power characterization are used

in the PCBs

electro-thermal

coupling

electro-thermal

coupling

temperatureinsensitivity

temperatureinsensitivity

Page 20: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 20

Exploiting the Thermal Feedback

� Electro-thermal coupling effect for different heat spreading technologies

� [Θ] = K/W → temperature difference between the environment and the heat

spreader to dissipate 1W (thermal resistance)

� [ct] = um → thickness of the spreader Simulation over time

Maximum temperature analysis

Feedback for the package sizing

Simulation over time

Maximum temperature analysis

Feedback for the package sizing

Θ reducesthickness increases

Page 21: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 21

SMI Leakage increase due to other

components in some configuration

SMI Leakage increase due to other

components in some configuration

Component Interaction Analysis

� Analyze the impact of a component on the others in order to

evaluate system level power/thermal management policies

effect of PGeffect of PG

CL is ON, but

C1/C2 are PG

CL is ON, but

C1/C2 are PG

3 power domains: Cores1/2, Configurable Logic, SMI

Configuration 4 5 6

Leakage increase 36% 23% 12%

Page 22: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 22

Dealing with Lack of Thermal Information

� Ab-Initio Thermal Modelling VS Learning Models

� Ab-initio

� Equations based on parameters (thermal conductivity of silicon and spreader)

� Requires characterization of both silicon and spreader

� Changes if the spreader changes

� Learning Models

� Use boot-time or run-time routines for thermal characterization

� Workload –> Power -> Temperature

� Requires temperature sensors

� Challenges

� Where to place sensors?

� Which identification routines?

� Off-line VS runtime?

Page 23: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 23

Thermal-Aware Resource Management

Resource Manager

RM interface

Boot-time thermal

characterizationThermal

control policy

Thermal model

Temperature

sensors

Performan

ce

counters

� Auto characterization of thermal

behavior exploits stress-test

routines and temperature sensor

readings

� The thermal

characterization is then used to

drive a thermal control policy

� The overall objective is to:

� Override RM decisions to

prevent temperature-induced

shut-down

� Introduce reliability awareness

in RM decisions

Page 24: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 24

Thermal-Aware Resource Management

� GOAL

� proactive management of chip temperature to limit hotspots and

gradients, to avoid performance hit due to temperature-induced

shutdown and increase overall system reliability

� FEATURES

� the thermal behavior auto-characterization capability avoids the need of

detailed thermal characterization

� exploit on-chip temperature sensors

� interface with RM developed by UNIBO

� INPUT OF RM:

� temperature sensors, performance counters (HW), core utilization

information

� OUTPUT OF RM:

� panic temperature alarm, hotspots and thermal gradient information to

drive RM decisions about voltage/frequency scaling and task allocation

Page 25: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 25

Power consumption induced

by the stress-test routineTemperature sensors readings

Example with 4 cores and 2 temperature sensors

These traces are used to perform a thermal model identification

Example of Thermal Identification (I)

Page 26: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 26

Comparison between the real

temperature (black) and the

estimated temperature (blue)

Sensor 1

Example with 4 cores and 2 temperature sensors

Sensor 2

� PREDICTION RESULTS:

Example of Thermal Identification (II)

� The identified model is then used to:

� Make prediction about the temperature behavior for a given workload

characteristic

� Develop the control policy (TBD)T(°K)

Time (sec)

Page 27: An Integrated Thermal Estimation Framework for Industrial

ARTEMISIA Association An Integreated Thermal Estimation.. - 27

Conclusions

� Temperature matters... several figures of merit are affected

(Performance, Power, Reliability)

� Thermal aware design has become a must

� Estimating temperature in the earlier design stages is of

paramount importance

� Integrated power/thermal estimators are now required

� Heterogeneous power information (from system to physical level)

� Link power and physical information to tech dependent thermal libraries

� Thermal feedback to drive thermal-aware design strategies

� Thermal identification is possible to avoid extensive

characterization and flexibility

27