Post on 25-Feb-2016
description
Energy Model for Multiprocess Applications
Texas Tech University
Faster Computers = More Energy• Moore’s law predicted 2 fold yearly increase
in transistor count for inexpensive devices• Transistor size has decreased to the point
where size can longer be major factor in speed• Multicore processors now fairly common• Increased performance from larger transistor
counts and multiple cores has increased energy usage
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Faster Computers = More Energy• An hour of usage on a super computer today
uses the same amount of energy that a moderate home will during the most extreme months of the year
• Google estimates their data centers use the same amount of power as 200,000 homes each year.
Texas Tech University
Energy Aware Motivations• Energy Costs• Device Battery Life• Green Computing Initiatives
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Energy Aware Research
• Most work being done in hardware design• CPUs now have multiple operating states to save
energy when not in use• Advanced Control Power Interface(ACPI) was
developed to give Operating Systems the ability to reduce power consumption of computers
• Most models & scheduling techniques rely on altering CPU operating frequency, which user applications cannot directly access
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CPU Energy Usage
• Energy is the amount of power used for a specified amount of time,
• If the power varies with time then, • With N processors, the total energy is the sum
of each processor’s usage,
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CPU Energy Usage (continued)
• The electrical power of a CPU is estimated as , is a physical constant and F is the operating frequency.
• As the frequency of a processor can vary with time, the energy usage of a multicore processor is
• CPUs only operate at S number of frequencies, • Developers cannot select the frequency of the CPU,
only if it is idle or not, so there are only 2 frequencies we consider, ON & OFF,
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Sequential Application Energy
• Sequential Applications only use 1 processor, so the other (N-1) processors are idle.
• The energy usage is reduced to
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Amdahl’s Law• Can be used to give a comparison between
sequential & parallel application performance• For this model, it gives us , the ratio of the
sequential energy usage to the parallel energy usage on an N processor system.
• is constant, so
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Observations
• Increasing CPU utilization increases Energy Efficiency
• “Racing to idle” means that the CPU will return to an idle state sooner
• Less time executing also means other components will be using less energy too
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Turning Off Idle Processors
• If is zero, then a parallel application uses the same power as its sequential version
• If runtime is fixed, additional processors are unnecessary
• Idle CPUs are not turned off and only waste energy
• Newer devices have too many CPUs, i.e. Smart Cell Phones
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No Idle Power States
• If , then = • Should only happen if power management
settings set incorrectly or poorly• Optimization only way to increase energy
efficiency
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