Schedule. 9:00-9:10 Section 1 - Basic intro to power and energy. 9:30-9:45 Section 3 - Component specific measurement techniques

9:00 - 9:10 Section 1 - Basic intro to power and energy

9:10 - 9:30 Section 2 - Devices for measuring power

9:30 - 9:45 Section 3 - Component specific measurement techniques

9:45-10:00 Section 4 - Advanced power measurement concepts

10:00-10:30 Section 5 – Memory and Compute on various platforms

10:30-11:00 Coffee Break (Dinning Hall)

11:00-11:30 Section 6 - Instruction-based power models

11:30-11:50 Section 7 - Open discussion

11:50-12:00 Section 8 - Summary and conclusion

Advanced Concepts

•  Multicore and uncore

•  Sleep states

•  Voltage-frequency scaling

•  Managing temperature variations

•  SKU and manufacturing variability

•  Synchronizing power measurements with

application phases

Advanced Concepts

•  Multicore and uncore

•  Sleep states

•  Voltage-frequency scaling

•  Managing temperature variations

•  SKU and manufacturing variability

•  Synchronizing power measurements with

application phases

Multicore and Uncore

7-10 watts per core

Advanced Concepts

•  Multicore and uncore

•  Sleep states

•  Voltage-frequency scaling

•  Managing temperature variations

•  SKU and manufacturing variability

•  Synchronizing power measurements with

application phases

C-States

C-State Power

(watts)

Description

C0 33.2 Normal execution

C1 10.6 Core halted; Core state and L1 cache still resident C3 7.2 Core, L1, and L2 powered down

i7z

C-States

Advanced Concepts

•  Multicore and uncore

•  Sleep states

•  Voltage-frequency scaling

•  Managing temperature variations

•  SKU and manufacturing variability

•  Synchronizing power measurements with

application phases

Voltage-­‐Frequency  Scaling    

y = 0.11x + 0.63 0 0.2 0.4 0.6 0.8 1 1.2 0.0 1.0 2.0 3.0 4.0 C ore V ol ta ge (V ol ts) Frequency (GHz) Haswell 4770K DVFS Settings P-States Frequency   (GHz)   Voltage  (Volts)   3.5 1.012 3.0 0.958 2.5 0.899 2.0 0.845 1.5 0.791 1.0 0.737

Voltage-­‐Frequency  Scaling  

y = 8.00e0.52x 0 10 20 30 40 50 60 70 0 0.5 1 1.5 2 2.5 3 3.5 4 A ve ra ge Po w er (W at ts) Frequency (GHz) HSW DVFS Power AVX Expon. (AVX) 2.00 2.20 2.40 2.60 2.80 3.00 0.0 1.0 2.0 3.0 4.0 Ef fici en cy (G F LO PS/ W at t) Frequency (GHz) HSW Energy Efficiency AVX

-­‐ -­‐  Most  efficient  at  2.0  GHz  

Voltage Frequency Scaling

Overclocking

[Nick Shih, Sep 2012] http://www.youtube.com/watch?v=968ZQ3a6pBM

Overclocked to 7.136 GHz

Voltage Frequency Scaling

0 20 40 60 80 100 0 1 2 3 Pow e r ( Watts) Frequency (GHz) Frequency Scaling DGEMM 1.2 V 1.1 V 1.0 V Linear (1.2 V) Linear (1.1 V) Linear (1.0 V) Performance 0 20 40 60 80 100 1.7 1.9 2.2 2.7 3.1 3.5 En e rg y (J o u le s) Frequency (GHz) Voltage-Frequency Scaling DGEMM Static Cost Dynamic Cost Efficient Operations Less Overhead

Advanced Concepts

•  Multicore and uncore

•  Sleep states

•  Voltage-frequency scaling

•  Managing temperature variations

•  SKU and manufacturing variability

•  Synchronizing power measurements with

application phases

Temperature Variations

Power (watts) Temperature (C)

Idle – Cold 7.5 40 Idle - Hot 9.2 55 Kernel -- Cold 45 51 Kernel -- Hot 48 72

Advanced Concepts

•  Multicore and uncore

•  Sleep states

•  Voltage-frequency scaling

•  Managing temperature variations

•  SKU and manufacturing variability

•  Synchronizing power measurements with

application phases

SKU and Manufacturing Variability

64 Processors Ordered by Average Watts

A ve ra ge W at ts

NAS MG.C.8 -- Intel Xeon E5-2670

77.7 – 85.4 watts, Range of 10%

Source: Rountree, Barry, et al. "Beyond DVFS: A first look at performance under a

hardware-enforced power bound." Parallel and Distributed Processing Symposium Workshops & PhD Forum (IPDPSW), 2012 IEEE 26th International. IEEE, 2012.

Advanced Concepts

•  Multicore and uncore

•  Sleep states

•  Voltage-frequency scaling

•  Managing temperature variations

•  SKU and manufacturing variability

•  Synchronizing power measurements with

application phases

Advanced Concepts

•  Multicore and uncore

•  Sleep states

•  Voltage-frequency scaling

•  Managing temperature variations

•  SKU and manufacturing variability

•  Synchronizing power measurements with

application phases

Impact of manufacturing process

Kenneth Czechowski, Victor W. Lee, Ed Grochowski, Ronny Ronen, Ronak Singhal, Pradeep Dubey, and Richard Vuduc. Improving the energy efficiency of big cores. In Proc. ACM/IEEE Int’l. Symp. on Computer Architecture (ISCA), Minneapolis, MN, USA, June 2014.

Generations of the Intel Core i7

LONGITUDINAL STUDY: CORE I7 PROCESSOR

Sandy Bridge! (2011) Ivy Bridge
 (2012) Haswell(2013) 
 Nehalem
 (2009) Penryn
 (2007) Westmere
 (2010) 45nm 32nm 22nm

Core Nehalem Sandy Bdg Haswell

Microarchitecture Generation Process Tech nolog y Nod e Tock Tock Tock Tick Tick

Generations of the Intel Core i7

L

ONGITUDINAL

S

TUDY

: C

ORE I

7 P

ROCESSOR

Sandy Bridge! (2011) Ivy Bridge
 (2012) Haswell(2013) 
 Nehalem
 (2009) Penryn
 (2007) Westmere
 (2010) 45nm 32nm 22nm

Core Nehalem Sandy Bdg Haswell

Microarchitecture Generation Process Tech nolog y Nod e Tock Tock Tock Tick Tick

Impact of process technology

_{PROCESS TECHNOLOGY NODES} y = 0.68x - 10.48 R² = 0.87 0.00 10.00 20.00 30.00 40.00 50.00 50.00 55.00 60.00 65.00 70.00 75.00 80.00 IVB Po w er W atts ) SNB Power (Watts)

Impact of 22nm process technology step

y = 0.57x + 7.55 R² = 0.97 0.00 10.00 20.00 30.00 40.00 50.00 60.00 45.00 55.00 65.00 75.00 85.00 95.00 W SM Po w er (W atts ) NHM Power (Watts)

Impact of 32nm process technology step

NHM (45nm) vs WSM (32nm) SNB (32nm) vs IVB (22nm)