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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

- 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

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

- 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

- 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

- 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 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

- 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

- 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

- 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

- 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

- If
- Energy efficient to run at higher freq.
- Pentium
- If
- Energy efficient to run at lower freq.
- PowerPC

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

- 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

- 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

- 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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