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Critical Power Slope Understanding the Runtime Effects of Frequency Scaling Akihiko Miyoshi, Charles Lefurgy, Eric Van Hensbergen Ram Rajamony Raj Rajkumar. Motivation. Power management algorithms implicitly assume that lower performance points are more energy efficient that higher points

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Critical Power Slope Understanding the Runtime Effects of Frequency ScalingAkihiko Miyoshi, Charles Lefurgy, Eric Van Hensbergen Ram Rajamony Raj Rajkumar


Motivation
Motivation

  • Power management algorithms implicitly assume that lower performance points are more energy efficient that higher points

  • This paper shows that this assumption is not always valid

  • Also helps decide which operating points of a processor should be considered by an power management algorithm


Outline

Watts

Watts

Outline

  • Motivation

    • <: not always true

    • How do we choose which operating points to use?

  • Evaluation of frequency scaling, clock throttling and dynamic voltage scaling on three existing processors

  • Analytical model: Critical Power Slope

  • Analysis on voltage scaling systems

  • Conclusion


Techniques of power management
Techniques of Power Management

  • Frequency scaling

    • Processor clock is reduced

    • Processor consumes less energy at the expense of reduced performance

  • Clock throttling

    • Clock runs at original frequency

    • Clock signal is gated/disabled for some cycles at regular intervals

  • Dynamic voltage scaling

    • Reduces power consumed by lowering the operating voltage

    • Advantageous because E ∝ V2


Linux on pentium
Linux on Pentium

  • Dell Inspiron 8000 laptop with 850 MHz PIII processor with 512Mb of RAM running Linux 2.4.6

  • Processor runs at 8 different performance states

    • 100% 87.5% 75% 62.5% 50% 37.5% 25% 12.5%

  • Effect is evaluated by throttling the clock

  • The following micro benchmarks were considered

    • Access to register

    • L1 cache (read)

    • L1 cache (write)

    • Access to memory (read)

    • Access to memory (write)

    • Disk Read



Power usage in idle mode pentium
Power usage in idle mode - Pentium

  • Linux scheduler puts the processor into C1 or C2 sleep state

  • Idle state power is considered to be a constant


Power measurements at different performance states pentium
Power measurements at different performance states - Pentium

  • Simple benchmark which exercises the CPU while changing the performance state from 100% - 12.5%

  • As performance is lowered system power usage decreases linearly


Energy consumption
Energy consumption

  • Energy required to complete the benchmark – Eactive + Eidle

  • Compare energy used to execute same load at the same time interval at different operating points

    • The time interval does not end at Eactive since the system is kept on until next request arrives

  • Idle time = Time to run the benchmark at a particular operating point – Time to run the benchmark at lowest performance states

  • Idle power is known, hence Eidle can be calculated


  • Eactive + Eidle decreases slightly as performance state increases

  • The benchmarks suggest we should run this system at the highest performance state possible


Linux on powerpc
Linux on PowerPC

  • PowerPC 405GP microprocessor, 8KB of D cache 16KB of I cache, 32MB RAM with Linux 2.4.0

  • Frequency of the processor and processor local bus (PLB) can be changed directly affecting memory speed



Powerpc energy consumption
PowerPC: Energy consumption

  • Total energy = Eactive + Eidle

    • Eactive = Ecpu + ESDRAM +Eother

  • By lowering frequency, total energy used by the system descreases

  • Results contrary to the Pentium based system


Characterization of the two systems
Characterization of the two systems

  • Bimodal behavior – system will either be in active or idle mode

  • Performance ∝ frequency

  • Pidle will be considered constant for all frequencies

  • Consider CPU intensive workload W, lowest frequency fmin

    • At fmin utilization of the system is 1 and W takes Tfmin units of time to complete

    • (-eq. 1)

    • At frequency f (f> fmin)

      (Ef = Eactive + Eidle)

      (-eq. 2)


Critical power slope
Critical Power Slope

  • As power ∝ frequency and constant at idle state (from the graph)

  • Substituting Pf in eq. 2

    • (-eq. 3)

  • There should be a slope m where energy

  • usage at all frequencies is equal

  • - critical power slope mcritical

  • Equating eq. 1 and eq.3 we get


Implications of cps
Implications of CPS

  • If

    • Energy efficient to run at higher freq.

    • Pentium

  • If

    • Energy efficient to run at lower freq.

    • PowerPC


Cps for voltage scaling system
CPS for voltage scaling system

  • Non linear power savings : P ∝ V2

  • Look at every operating point at frequency

  • If

    • Energy efficient at higher frequency than

  • If

    • Energy efficient at lower frequency than


Analysis on sa 1100
Analysis on SA-1100

  • A StrongARM processor (SA-1100) is considered

  • Above 74MHz

  • At 74MHz

  • Below 74MHz

  • Energy Inefficient below 74MHz!

  • No incentive to operative between 74MHz and 59 MHz using voltage scaling


Critical power slope in realistic workload
Critical Power slope in Realistic workload

  • Static page requests on a web server

    • Apache 1.3, Pentium based laptop

  • At 100% performance – 1500 requests/sec

  • At 62.5% performance – 700 requests/sec

  • Energy increases linearly as request rate increases

  • More energy efficient to run at higher performance

  • Consistent with previous Pentium system analysis


Conclusion
Conclusion

  • This paper shows the assumption that lower performance points are more energy efficient that higher performance points is not valid

  • This paper helps decide which operating point to choose in a power management scheme



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