Performance per watt

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Performance per watt includes various measures of computing energy efficiency. Examples include: FLOPS per watt, MIPS per watt, or the score for other performance benchmark, divided by the power used. Often the power is the average power used while running the benchmark, but sometimes other measures of power usage may be employed (e.g. peak power, average power, idle power.)

For example, UNIVAC I performed approximately 0.015 operations/watt-second (performing 1,905 operations/second, while consuming 125 kW).

Most of the power a computer uses is converted into heat, so a system that takes fewer watts to do a job will require less cooling to maintain a given operating temperature. If installed where there is limited climate control, a lower power computer will operate at a lower temperature, which may make it more reliable. Reducing cooling demands make it easier to make a computer quiet. Reducing energy consumption can also make it less costly to run, and reduce the environmental impact from powering the computer (see green computing).

Computing energy efficiency is sometimes also measured by reporting the energy required to run a particular benchmark, for instance EEMBC EnergyBench.

Performance (in operations/second) per watt can also be written as operations/watt-second, or operations/joule, since 1 watt = 1 joule/second.

Contents 1 FLOPS per watt 1.1 Examples 2 Green500 List 3 GPU efficiency 4 Challenges 5 Other energy efficiency measures 6 See also 7 References

[edit] FLOPS per watt

Compter Performance
Name	FLOP/s
megaflops	106
gigaflops	109
teraflops	1012
petaflops	1015
exaflops	1018
zettaflops	1021
yottaflops	1024

FLOPS per watt is a measure of efficiency of computation, where FLOPS is a measure of computation speed in FLoating POint Operations Per Second. Usually applied to scientific computing and simulations involving lots of floating point calculations.

[edit] Examples

Microwulf, a low cost desktop Beowulf cluster of 4 dual core Athlon 64 x2 3800+ computers, runs at 58 MFLOPS/Watt.^[1]

As of 2007, the Green500 list rates Blue Gene/P as the most efficient supercomputer on the TOP500 in terms of FLOPS per Watt, running at 350 MFLOPS/Watt.^[2]

On June 9th, 2008 CNN reported that IBM's Roadrunner supercomputer achieves 376 MFLOPS/Watt. ^[3]

As part of Intel's TeraScale research project, they produced an 80 core CPU that can achieve over 16 GFLOPS/Watt.^[4][5]

[edit] Green500 List

The Green500 list ranks computers from the TOP500 list of supercomputers in terms of energy efficiency. Typically measured as LINPACK FLOPS per watt.^{[6] [7]}

[edit] GPU efficiency

Graphics processing units (GPU) have continued to increase in energy usage, while CPUs designers have recently focused on improving performance per watt. High performance GPUs may now be the largest power consumer in a system. Measures like 3DMark2006 score per watt can help identify more efficient GPUs.^[8] However that may not adequately incorporate efficiency in typical use, where much time is spent doing less demanding tasks.^[9]

Since GPUs may also be used for some general purpose computation, sometimes their performance is measured in terms also applied to CPUs, such as FLOPS per watt.

[edit] Challenges

While performance per watt is useful, absolute power requirements are also important. Claims of improved performance per watt may be used to mask increasing power demands. For instance, GPUs have gotten to such large power requirements that though newer generation architectures may provide better performance per watt, they still consume unreasonable amounts of power.^[10]

Benchmarks that measure power under heavy load may not adequately reflect typical efficiency. For instance, 3DMark stresses the 3D performance of a GPU, but many computers spend most of their time doing less intense display tasks (idle, 2D tasks, displaying video). So the 2D or idle efficiency of the graphics system may be at least as significant for overall energy efficiency. Likewise, systems that spend much of their time in standby or soft off are not adequately characterized by just efficiency under load. To help address this some benchmarks, like SPECpower, include measurements at a series of load levels.^[11]

The efficiency of some electrical components, such as voltage regulators, decreases with increasing temperature, so the power used may increase with temperature. Power supplies, motherboards, and some video cards are some of the subsystems affected by this. So their power draw may depend on temperature, and the temperature or temperature dependence should be noted when measuring.^[12][13]

Performance per watt also typically does not include full life-cycle costs. Since computer manufacturing is energy intensive, and computers often have a relatively short lifespan, energy and materials involved in production, distribution, disposal and recycling often make up significant portions of their cost, energy use, and environmental impact.^[14][15]

Energy required for climate control of the computer's surroundings is often not counted in the wattage calculation, but can be significant.^[16]

[edit] Other energy efficiency measures

SWaP (space, wattage and performance). SUN Microsystems metric for data centers, incorporating energy and space.

SWaP = Performance/(Space x Power)

Where performance is measured by any appropriate benchmark, and space is size of the computer. ^[17]

[edit] See also

Energy efficiency benchmarks:

• Average CPU Power Measures power used running several standard benchmarks.
• SPECpower Benchmark for web servers running Java. (Server Side Java Operations per Joule)
• EEMBC EnergyBench.

Other:

• GeForce 8 Series GPU list, has energy use and theoretical FLOPS.

[edit] References

• Wu-Chun Feng (October 2003). "Making a case for Efficient Supercomputing". ACM Queue 1.