1. The University of Adelaide, School of Computer Science
9 April 2019
1.5 Power and Energy
Introduction
Problem: Get power in, get power out
Power and Energy: A systems Perspective
How we should think about Performance, Power, and Energy:
From the viewpoint of a system designer, there are three primary concerns:
What is the maximum power.
What is the sustained power consumption, widely called the thermal design power (TDP)  Determines the cooling requirement.
The third factor for both (Designers and Users) is Energy and Energy efficiency.
Power: is simply Energy per Unit time.
1 watt = 1 Joule/second
Energy is the capacity to do work.
Energy is power integrated over time.
Power is the rate at which work is done, or energy is transmitted.
Chapter 2 — Instructions: Language of the Computer

2. 1.5 Power and Energy (continue)
Example: I left a 60W light bulb on for 30 days, which raised my electric bill by 43.2 kWh (kilowatt-hours).
Example: My car's battery can provide 500 amps at 12 volts, which equals 6kW of power.
We use Energy to compare the efficiency of two Processors (not Power).
Example: Processor A may have a 20% higher average power consumption than Processor B, but A executes the task in only 70% of the time needed by B,
Thus, its Energy consumption =1.2 × 0.7 = 0.84 which is clearly better.

3. 1.5 Power and Energy (continue)

4. 1.5 Power and Energy (continue)
Example: Some microprocessors today are designed to have adjustable voltage, so a 15% reduction in voltage may result in a 15% reduction in frequency. What would be the impact on dynamic energy and on dynamic power?

5. 1.5 Power and Energy (continue)
The University of Adelaide, School of Computer Science
9 April 2019
1.5 Power and Energy (continue)
Intel consumed ~ 2 W
3.3 GHz Intel Core i7 consumes 130 W
Heat must be dissipated from 1.5 x 1.5 cm chip
This is the limit of what can be cooled by air
Trends in Power and Energy
Chapter 2 — Instructions: Language of the Computer

6. 1.5 Power and Energy (continue)
The University of Adelaide, School of Computer Science
9 April 2019
1.5 Power and Energy (continue)
Techniques for reducing power:
Do nothing well
Dynamic Voltage-Frequency Scaling
Low power state for DRAM, disks
Overclocking, turning off cores
Trends in Power and Energy
Chapter 2 — Instructions: Language of the Computer

7. 1.5 Power and Energy (continue)
The University of Adelaide, School of Computer Science
9 April 2019
1.5 Power and Energy (continue)
Static power consumption
Currentstatic x Voltage
Scales with number of transistors
To reduce: power gating
Trends in Power and Energy
Chapter 2 — Instructions: Language of the Computer

8. The University of Adelaide, School of Computer Science
9 April 2019
1.6 Trends in Cost
Trends in Cost
The Impact of Time, Volume, and Commoditization
Cost decreases over time
Cost driven down by learning curve
Learning curve improves Yield
Designs that have twice the yield will have half the cost.
DRAM: price closely tracks cost
Microprocessors: Prices also drop over time, but, because they are less standardized than DRAMs, the relationship between price and cost is more complex.
Volume
As a rule of thumb, some designers have estimated that cost decreases about 10% for each doubling of volume.
Commoditization
Many vendors ship virtually identical products  the market is highly competitive.
Learning Curve
Chapter 2 — Instructions: Language of the Computer

9. Integrated Circuit Cost
The University of Adelaide, School of Computer Science
9 April 2019
Integrated Circuit Cost
Trends in Cost
Chapter 2 — Instructions: Language of the Computer

10. Examples:

11. The University of Adelaide, School of Computer Science
9 April 2019
1.7 Dependability
Dependability
Chapter 2 — Instructions: Language of the Computer

14. 1.8 Measuring Performance
The University of Adelaide, School of Computer Science
9 April 2019
1.8 Measuring Performance
Typical performance metrics:
Response time
Throughput
Speedup of X relative to Y
Execution timeY / Execution timeX
Execution time
Wall clock time: includes all system overheads
CPU time: only computation time
Benchmarks
Kernels (e.g. matrix multiply)
Toy programs (e.g. sorting)
Synthetic benchmarks (e.g. Dhrystone)
Benchmark suites (e.g. SPEC06fp, TPC-C)
Measuring Performance
Chapter 2 — Instructions: Language of the Computer

15. 1.9 Principles of Computer Design
The University of Adelaide, School of Computer Science
9 April 2019
1.9 Principles of Computer Design
Principles
Take Advantage of Parallelism
e.g. multiple processors, disks, memory banks, pipelining, multiple functional units
Principle of Locality
Reuse of data and instructions
Focus on the Common Case
Amdahl’s Law
Chapter 2 — Instructions: Language of the Computer

16. Principles of Computer Design
The University of Adelaide, School of Computer Science
9 April 2019
Principles of Computer Design
Principles
The Processor Performance Equation
Chapter 2 — Instructions: Language of the Computer

17. Principles of Computer Design
The University of Adelaide, School of Computer Science
9 April 2019
Principles of Computer Design
Principles
Different instruction types having different CPIs
Chapter 2 — Instructions: Language of the Computer