1
FirmLeak: A framework for efficient and accurate runtime estimation of leakage power by firmware Abstract Run-time Leakage Power Estimation Experimental Results FirmLeak Introduction References PVT Independent Leakage abstracts for Power Gating Domains Arun Joseph, Anand Haridass, Charles Lefurgy + , Spandana Rachamalla, Sreekanth Pai, Diyanesh Chinnakkonda, Vidushi Goyal * IBM Systems & Technology Group, IBM Research + , IIT Kharagpur * Separating the dynamic and leakage power can enable new optimizations for cloud computing. We introduce FirmLeak, a new framework that enables accurate, real- time estimation of microprocessor leakage power by system software. FirmLeak accounts for power-gating regions, per-core voltage domains, and manufacturing variations. Normalized VDD Total Power Under Varying Temperature 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 50.00 55.00 60.00 65.00 70.00 75.00 80.00 Temperature (C) Normalized VDD Total Power HW 3 ES 3 Normalized VDD Total Power Under Varying Temperature 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 50.00 55.00 60.00 65.00 70.00 75.00 80.00 Temperature (C) Normalized VDD Total Power HW 1 ES 1 Normalized VDD Total Power Under Varying Temperature 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 50.00 55.00 60.00 65.00 70.00 75.00 80.00 Temperature (C) Normalized VDD Total Power HW 2 ES 2 Normalized VDD Total Power Under Varying Temperature 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 50.00 55.00 60.00 65.00 70.00 75.00 80.00 Temperature (C) Normalized VDD Total Power HW 3 ES 3 Normalized VDD Total Power Under Varying Temperature 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 50.00 55.00 60.00 65.00 70.00 75.00 80.00 Temperature (C) Normalized VDD Total Power HW 1 ES 1 Normalized VDD Total Power Under Varying Temperature 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 50.00 55.00 60.00 65.00 70.00 75.00 80.00 Temperature (C) Normalized VDD Total Power HW 2 ES 2 Normalized VDD Total Power Under Varying Frequency 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 -10% 0% 10% 20% 30% Frequency as % of Nominal Normalized VDD Total Power HW 3 ES 3 Normalized VDD Total Power Under Varying Frequency 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 -10% 0% 10% 20% 30% Frequency as % of Nominal Normalized VDD Total Power HW 1 ES 1 Normalized VDD Total Power Under Varying Frequency 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 -10% 0% 10% 20% 30% Frequency as % of Nominal Normalized VDD Total Power HW 2 ES 2 Normalized VDD Total Power Under Varying Frequency 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 -10% 0% 10% 20% 30% Frequency as % of Nominal Normalized VDD Total Power HW 3 ES 3 Normalized VDD Total Power Under Varying Frequency 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 -10% 0% 10% 20% 30% Frequency as % of Nominal Normalized VDD Total Power HW 1 ES 1 Normalized VDD Total Power Under Varying Frequency 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 -10% 0% 10% 20% 30% Frequency as % of Nominal Normalized VDD Total Power HW 2 ES 2 NormalizedTotal VDDPower Under Varying Voltage 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.040 1.060 1.080 1.100 1.120 1.140 1.160 VDDVoltage (V) Normalized VDD Total Power HW3 ES3 Normalized Total VDD Power Under Varying Voltage 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.040 1.060 1.080 1.100 1.120 1.140 1.160 VDD Voltage (V) Normalized VDD Total Power HW 1 ES 1 Normalized Total VDD Power Under Varying Voltage 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.040 1.060 1.080 1.100 1.120 1.140 1.160 VDD Voltage (V) Normalized VDD Total Power HW 2 ES 2 NormalizedTotal VDDPower Under Varying Voltage 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.040 1.060 1.080 1.100 1.120 1.140 1.160 VDDVoltage (V) Normalized VDD Total Power HW3 ES3 Normalized Total VDD Power Under Varying Voltage 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.040 1.060 1.080 1.100 1.120 1.140 1.160 VDD Voltage (V) Normalized VDD Total Power HW 1 ES 1 Normalized Total VDD Power Under Varying Voltage 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.040 1.060 1.080 1.100 1.120 1.140 1.160 VDD Voltage (V) Normalized VDD Total Power HW 2 ES 2 Fig. 9. VDD total power under varying conditions of temperature Fig. 10. VDD total power under varying conditions of frequency Fig. 11. VDD total power under varying conditions of voltage 1. Wei Huang et al. "TAPO: Thermal-aware power optimization techniques for servers and data centers," Green Computing Conference and Workshops (IGCC), 2011. 2. S. Borkar et al. ‘‘Parameter variations and impact on circuits and microarchitecture,’’ in Proc. Design Autom. Conf., Jun. 2003. 3. US Patent 8,527,794: “Realtime power management of integrated circuits,” Ibrahim, A. and Dwarakanath, A. and Shimizu, D.P . 4. Dhanwada, N. et al. "Efficient PVT independent abstraction of large IP blocks for hierarchical power analysis," Computer-Aided Design (ICCAD), 2013 IEEE/ACM International Conference on, pp.458,465, 18-21 Nov. 2013. 5. IBM Redbooks: “IBM Power 710 and 730 Technical Overview and Introduction,” May 2013. The information for each device type in the domain, along with process corner from test, temperature and voltage conditions from hardware sensors, is passed into a device level leakage model. Fig. 6. Leakage power estimation via firmware Leakage power estimation in modern high-performance microprocessors, must account for significant manufacturing variation [2] as well as workload-induced temperature variation. Since firmware power management may operate on a longer time intervals than power-gating, the ability to derate the estimate for the actual power-on time becomes important. Accurate runtime estimation of leakage power from [1, 3] requires intensive post-silicon power characterization and data collection. Process, Voltage, Temperature (PVT) independent Leakage Abstract Generation PVT independent Power Gating Domain Leakage Abstract Table Process Corner from Manufacturing Test EPROM Hardware SoC Microcontroller FirmTech Leakage Power API Firmware Other FW Silicon Voltage & Temperature Measurements Processor Process, Voltage, Temperature (PVT) independent Leakage Abstract Generation PVT independent Power Gating Domain Leakage Abstract Table Process Corner from Manufacturing Test EPROM Hardware SoC Microcontroller FirmTech Leakage Power API Firmware Other FW Silicon Voltage & Temperature Measurements Processor Motivating Scenarios Introduces the use of Process, Voltage and Temperature (PVT) independent pre-silicon Power Gating domain Leakage Abstracts (PGLA) in firmware to accurately estimate per-device type contributions and total runtime leakage power. Enables significant reduction in post-silicon power characterization. Enables power-gating aware estimation by adding accompanying circuitry to track the time spent in power-gating states. Cloud-based billing Chip Core Core Core Core Per-core dynamic power estimate Per-core leakage power estimate (FirmLeak) Read counters, VPD, temperature per-core voltage Hypervisor VM 1 VM 2 Schedule VM on cores Map core to VM (provided by hypervisor) Dynamic energy Leakage energy Chargeback accounting Chip Core Core Core Core Chip Core Core Core Core Per-core dynamic power estimate Per-core leakage power estimate (FirmLeak) Read counters, VPD, temperature per-core voltage Hypervisor VM 1 VM 2 Hypervisor VM 1 VM 2 Schedule VM on cores Map core to VM (provided by hypervisor) Dynamic energy Leakage energy Chargeback accounting Fig. 2. Per core energy for VM energy chargeback Fan-based power optimization Fan-based Power Optimization Increasing Microprocessor Temperature (Decreasing fan speed) Increasing Power Consumption Microprocessor leakage power Fan power Total power Fig. 3. Optimizing the sum of fan power and leakage power For each design unit that makes up the hardware block (example: microprocessor), we generate a leakage abstracts, using techniques described in [4]. Power- Gating Domain Rail Device type svt n svt p hvt n hvt p mvt n mvt p 1 Vdd w 1 ,l 1 ,c 1 w 2 ,l 2 ,c 2 w 3 ,l 3 ,c 3 w 4 ,l 4 ,c 4 w 5 ,l 5 ,c 5 w 6 ,l 6 ,c 6 1 Vcs w 7 ,l 7 ,c 7 w 8 ,l 8 ,c 8 w 9 ,l 9 ,c 9 w 10 ,l 10 ,c 10 w 11 ,l 11 ,c 11 w 12 ,l 12 ,c 12 2 Vdd w 13 ,l 13 ,c 13 w 14 ,l 14 ,c 14 w 15 ,l 15 ,c 15 w 16 ,l 16 ,c 16 w 17 ,l 17 ,c 17 w 18 ,l 18 ,c 18 2 Vcs w 19 ,l 19 ,c 19 w 20 ,l 20 ,c 20 w 21 ,l 21 ,c 21 w 22 ,l 22 ,c 22 w 23 ,l 23 ,c 23 w 24 ,l 24 ,c 24 Power- Gating Domain Rail Device type svt n svt p hvt n hvt p mvt n mvt p 1 Vdd w 1 ,l 1 ,c 1 w 2 ,l 2 ,c 2 w 3 ,l 3 ,c 3 w 4 ,l 4 ,c 4 w 5 ,l 5 ,c 5 w 6 ,l 6 ,c 6 1 Vcs w 7 ,l 7 ,c 7 w 8 ,l 8 ,c 8 w 9 ,l 9 ,c 9 w 10 ,l 10 ,c 10 w 11 ,l 11 ,c 11 w 12 ,l 12 ,c 12 2 Vdd w 13 ,l 13 ,c 13 w 14 ,l 14 ,c 14 w 15 ,l 15 ,c 15 w 16 ,l 16 ,c 16 w 17 ,l 17 ,c 17 w 18 ,l 18 ,c 18 2 Vcs w 19 ,l 19 ,c 19 w 20 ,l 20 ,c 20 w 21 ,l 21 ,c 21 w 22 ,l 22 ,c 22 w 23 ,l 23 ,c 23 w 24 ,l 24 ,c 24 Fig. 5. Power gating domain leakage abstract (PGLA) table The derating factor is the ratio of the incremented count in the power- on counter to the incremented count of the cycle counter during the interval. Derating = (poweron2 – poweron1) / (cycles2 – cycles1) Derated Leakage Power = Leakage Power * Derating Microcontroller Processor Cycle counter Power-on counter Power Domain Derating = (poweron2 – poweron1) / (cycles2 – cycles1) Derated Leakage Power = Leakage Power * Derating Microcontroller Processor Cycle counter Power-on counter Power Domain Fig. 7. Derated leakage power estimation Fig. 1. FirmLeak Overview Leakage Power vs Temperature @ Voltage V 1 volts, Process Corner S 1 0 1 2 3 4 5 6 7 8 9 10 45 50 55 60 65 70 75 80 85 90 95 100 105 110 Temperature (C) Norm alized Leakage Power D1 D2 D3 D4 Leakage Power vs Temperature @ Voltage V 1 volts, Process Corner S 2 0 1 2 3 4 5 6 7 8 9 10 45 50 55 60 65 70 75 80 85 90 95 100 105 110 Temperature (C) Norm alized Leakage Power D1 D2 D3 D4 Leakage Power vs Temperature @ Voltage V 1 volts, Process Corner S 3 0 1 2 3 4 5 6 7 8 9 10 45 50 55 60 65 70 75 80 85 90 95 100 105 110 Temperature (C) Norm alized Leakage Power D1 D2 D3 D4 Leakage Power vs Temperature @ Voltage V 1 volts, Process Corner S 1 0 1 2 3 4 5 6 7 8 9 10 45 50 55 60 65 70 75 80 85 90 95 100 105 110 Temperature (C) Norm alized Leakage Power D1 D2 D3 D4 Leakage Power vs Temperature @ Voltage V 1 volts, Process Corner S 2 0 1 2 3 4 5 6 7 8 9 10 45 50 55 60 65 70 75 80 85 90 95 100 105 110 Temperature (C) Norm alized Leakage Power D1 D2 D3 D4 Leakage Power vs Temperature @ Voltage V 1 volts, Process Corner S 3 0 1 2 3 4 5 6 7 8 9 10 45 50 55 60 65 70 75 80 85 90 95 100 105 110 Temperature (C) Norm alized Leakage Power D1 D2 D3 D4 Fig. 4. Motivation for using per device type power gating abstracts in the runtime estimation of leakage power in firmware. Derated Leakage Power Estimation Experimental Setup Power 730/740 class server [5] used for experimental evaluation. Uses 32nm POWER7+ processors. 2 socket entry-level SMP server with up to 16 processor cores. The system planar supports two POWER 7+ modules. Fig. 8. POWER7+ server Average Error of ~5%. Average error of ~3.8 %. Average error of ~2 %.

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FirmLeak: A framework for efficient and accurate runtime estimation of leakage power by firmware

Abstract Run-time Leakage Power Estimation Experimental Results

FirmLeak

Introduction

References

PVT Independent Leakage abstracts for Power

Gating Domains

Arun Joseph, Anand Haridass, Charles Lefurgy+, Spandana Rachamalla, Sreekanth Pai, Diyanesh Chinnakkonda, Vidushi Goyal* IBM Systems & Technology Group, IBM Research+, IIT Kharagpur*

� Separating the dynamic and leakage power can enable new

optimizations for cloud computing.

� We introduce FirmLeak, a new framework that enables accurate, real-

time estimation of microprocessor leakage power by system software.

� FirmLeak accounts for power-gating regions, per-core voltage

domains, and manufacturing variations.

Normalized VDD Total Power Under Varying

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Fig. 9. VDD total power under varying conditions of temperature

Fig. 10. VDD total power under varying conditions of frequency

Fig. 11. VDD total power under varying conditions of voltage

1. Wei Huang et al. "TAPO: Thermal-aware power optimization

techniques for servers and data centers," Green Computing

Conference and Workshops (IGCC), 2011.

2. S. Borkar et al. ‘‘Parameter variations and impact on circuits and

microarchitecture,’’ in Proc. Design Autom. Conf., Jun. 2003.

3. US Patent 8,527,794: “Realtime power management of integrated

circuits,” Ibrahim, A. and Dwarakanath, A. and Shimizu, D.P .

4. Dhanwada, N. et al. "Efficient PVT independent abstraction of large

IP blocks for hierarchical power analysis," Computer-Aided Design

(ICCAD), 2013 IEEE/ACM International Conference on, pp.458,465,

18-21 Nov. 2013.

5. IBM Redbooks: “IBM Power 710 and 730 Technical Overview and

Introduction,” May 2013.

� The information for each device type in the domain, along with

process corner from test, temperature and voltage conditions from

hardware sensors, is passed into a device level leakage model.

Fig. 6. Leakage power estimation via firmware

� Leakage power estimation in modern high-performance

microprocessors, must account for significant manufacturing variation

[2] as well as workload-induced temperature variation.

� Since firmware power management may operate on a longer time

intervals than power-gating, the ability to derate the estimate for the

actual power-on time becomes important.

� Accurate runtime estimation of leakage power from [1, 3] requires

intensive post-silicon power characterization and data collection.

Process, Voltage, Temperature (PVT) independent Leakage Abstract Generation

PVT independent Power Gating Domain Leakage

Abstract Table

Process Corner from Manufacturing Test

EPROMHardware

SoC

Microcontroller

FirmTechLeakagePower

API

Firmware

Other FW Silicon Voltage &

Temperature

Measurements

Processor

Process, Voltage, Temperature (PVT) independent Leakage Abstract Generation

PVT independent Power Gating Domain Leakage

Abstract Table

Process Corner from Manufacturing Test

EPROMHardware

SoC

Microcontroller

FirmTechLeakagePower

API

Firmware

Other FW Silicon Voltage &

Temperature

Measurements

Processor

Motivating Scenarios

� Introduces the use of Process, Voltage and Temperature (PVT)

independent pre-silicon Power Gating domain Leakage Abstracts

(PGLA) in firmware to accurately estimate per-device type

contributions and total runtime leakage power.

� Enables significant reduction in post-silicon power characterization.

� Enables power-gating aware estimation by adding accompanying

circuitry to track the time spent in power-gating states.

� Cloud-based billing

Chip

Core Core

CoreCore

Per-coredynamic powerestimate

Per-coreleakage power

estimate(FirmLeak)

Read counters,VPD, temperature per-core voltage

Hypervisor

VM 1

VM 2

ScheduleVM on cores

Map core to VM(provided by hypervisor)

Dynamicenergy

Leakage energy

Chargeback

accounting

Chip

Core Core

CoreCore

Chip

Core Core

CoreCore

Per-coredynamic powerestimate

Per-coreleakage power

estimate(FirmLeak)

Read counters,VPD, temperature per-core voltage

Hypervisor

VM 1

VM 2

Hypervisor

VM 1

VM 2

ScheduleVM on cores

Map core to VM(provided by hypervisor)

Dynamicenergy

Leakage energy

Chargeback

accounting

Fig. 2. Per core energy for VM energy chargeback

� Fan-based power optimization

Fan-based Power Optimization

Increasing Microprocessor Temperature (Decreasing fan speed)

Incre

asin

g P

ow

er C

onsum

ption

Microprocessor leakage power

Fan power

Total power

Fig. 3. Optimizing the sum of fan power and leakage power

� For each design unit that makes up the hardware block (example:

microprocessor), we generate a leakage abstracts, using techniques

described in [4].

Power-

Gating

Domain

Rail Device type

svt n svt p hvt n hvt p mvt n mvt p

1 Vdd w1,l1,c1 w2,l2,c2 w3,l3,c3 w4,l4,c4 w5,l5,c5 w6,l6,c6

1 Vcs w7,l7,c7 w8,l8,c8 w9,l9,c9 w10,l10,c10 w11,l11,c11 w12,l12,c12

2 Vdd w13,l13,c13 w14,l14,c14 w15,l15,c15 w16,l16,c16 w17,l17,c17 w18,l18,c18

2 Vcs w19,l19,c19 w20,l20,c20 w21,l21,c21 w22,l22,c22 w23,l23,c23 w24,l24,c24

Power-

Gating

Domain

Rail Device type

svt n svt p hvt n hvt p mvt n mvt p

1 Vdd w1,l1,c1 w2,l2,c2 w3,l3,c3 w4,l4,c4 w5,l5,c5 w6,l6,c6

1 Vcs w7,l7,c7 w8,l8,c8 w9,l9,c9 w10,l10,c10 w11,l11,c11 w12,l12,c12

2 Vdd w13,l13,c13 w14,l14,c14 w15,l15,c15 w16,l16,c16 w17,l17,c17 w18,l18,c18

2 Vcs w19,l19,c19 w20,l20,c20 w21,l21,c21 w22,l22,c22 w23,l23,c23 w24,l24,c24

Fig. 5. Power gating domain leakage abstract (PGLA) table

� The derating factor is the ratio of the incremented count in the power-

on counter to the incremented count of the cycle counter during the

interval.

Derating = (poweron2 – poweron1) / (cycles2 – cycles1)

Derated Leakage Power = Leakage Power * Derating

Microcontroller Processor

Cycle counter

Power-on counter

Power DomainDerating = (poweron2 – poweron1) / (cycles2 – cycles1)

Derated Leakage Power = Leakage Power * Derating

Microcontroller Processor

Cycle counter

Power-on counter

Power Domain

Fig. 7. Derated leakage power estimation

Fig. 1. FirmLeak Overview

Leakage Power vs Temperature @ Voltage V1 volts, Process Corner S1

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7

8

9

10

45 50 55 60 65 70 75 80 85 90 95 100 105 110

Temperature (C)

No

rma

lize

d L

ea

ka

ge

Po

we

r

D1 D2

D3 D4

Leakage Power vs Temperature @ Voltage V1 volts, Process Corner S3

0

1

2

3

4

5

6

7

8

9

10

45 50 55 60 65 70 75 80 85 90 95 100 105 110

Temperature (C)

No

rma

lize

d L

ea

ka

ge

Po

we

r

D1 D2

D3 D4

Fig. 4. Motivation for using per device type power gating abstracts in the runtime

estimation of leakage power in firmware.

Derated Leakage Power Estimation

Experimental Setup

� Power 730/740 class server [5] used for experimental evaluation.

� Uses 32nm POWER7+ processors.

� 2 socket entry-level SMP server with up to 16 processor cores.

� The system planar supports two POWER 7+ modules.

Fig. 8. POWER7+ server

� Average Error of ~5%.

� Average error of ~3.8 %.

� Average error of ~2 %.