Energy Model for Multiprocess Applications

1. Texas Tech University Energy Model for Multiprocess Applications

2. Faster Computers = More Energy Texas Tech University • 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

3. Faster Computers = More Energy Texas Tech University • 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.

4. Energy Aware Motivations Texas Tech University • Energy Costs • Device Battery Life • Green Computing Initiatives

5. Energy Aware Research Texas Tech University • 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

6. CPU Energy Usage Texas Tech University • 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,

7. CPU Energy Usage (continued) Texas Tech University • 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,

8. Sequential Application Energy Texas Tech University • Sequential Applications only use 1 processor, so the other (N-1) processors are idle. • The energy usage is reduced to

9. Amdahl’s Law Texas Tech University • 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

10. Observations Texas Tech University • 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

11. Turning Off Idle Processors Texas Tech University • 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

12. No Idle Power States Texas Tech University • If , then = • Should only happen if power management settings set incorrectly or poorly • Optimization only way to increase energy efficiency