Where Does Power Go in a Computer System: Experimental Analysis and Implications

Where Does Power Go in a Computer System: Experimental Analysis and Implications Hui Chen, Shinan Wang and Weisong Shi Wayne State University

Outline • Introduction • Power Measurement • Evaluation • Implications • Conclusions

Introduction • The power problem of computer systems • Restrict performance improvement • Frequency limitation • Hard to cool down • Influence user experience • Battery lifetime of mobile devices • Waste a large amount of energy consumption • Energy un-proportional in data centers • Low utilization VS high energy consumption

Introduction (cont.) • Methods to solve this problem • Low-power circuits design • New material (PCM) • Power-aware system design • Hardware supplies different power states • Operating system makes power-aware strategies • Power-aware software & application design • Optimize during code compiling • Decrease application performance requirement when battery level is low

Motivation • Computer system still consumes an ever increasing amount of energy • The idle power does not decrease too much • Idle power is not used for computing • Account for a large amount of the total power dissipation • One of the main reason that cause energy un-proportional Where does power go in a computer system?

Experiment Platform Two desktops of different periods The same producer Single core VS multi-core DDR VS DDR3 Different disk size

Power Measurement • Direct Method • CPU, Disk • Indirect Method (subtract) • Memory, NIC

Indirect Power Measurement • Execute a benchmark application to stress a component • Find out with cables supply power for each device • Which cables’ voltage change.

Indirect Power Measurement (cont.) #define CACHELINE_SIZE 64 #define L2CACHE_SIZE 2048 #define ARRAY_SIZE (L2CACHE_SIZE * 1024/CACHELINE_SIZE * 2) typedefstruct{ intdata[CACHELINE_SIZE/4]; }LINE; LINE array[ARRAY_SIZE]; … unsigned intsize = ARRAY_SIZE; unsigned inti = 0; while(1){ array[i%size].data[0] = i; i++; }

Idle Power • While we trying to decrease the idle power of part components, we increase the idle power of other components. • The total idle power does not drop too much.

Idle power (cont.) • The idle power of CPU and memory dropped a lot. • Similar situation was not shown on disk.

Idle Power (cont.) PC05 PC10 Other components should acquire similar or even more concentration .

The active power of CPU • The active power decreased about 5 – 22Watts. • The active power is significantly different when executing each benchmark, even though all the utilization is 100%.

CPU Utilization • CPU Utilization is not a good indicator of power dissipation. • When CPU utilization is 100%, the difference of power may be more than 10W. Not suitable to be used for power modeling.

Controllable Cache Size • Cache benchmark generates much more power than memory benchmark. • Through control cache size we could control the power dissipation of CPU.

An example High Indicator (battery level) Low Cache

Power Transform Efficiency DC Power AC Power High transform efficiency is required in able to save power. Transform Efficiency = • The transform efficiency of AC to DC is low.

Multi-core Task Allocation • The power of CPU does not decrease too much when idling part of cores. From the energy efficiency point of view, idling part of cores while make the other parts busy does not save power.

Conclusions • We measured the power of several main components. • The total idle power does not decrease too much. • The idle power of other parts and disk should acquire more attention. • From the experiment result, we derive several implications that are important for power-aware system design. • CPU utilization is not a good indicator of power dissipation. • Cache size should be controllable. • Power transform efficiency should be increased. • Idling part of cores does not save power.

Thank you! More question? huichen@wayne.edu

Where Does Power Go in a Computer System: Experimental Analysis and Implications