Implications of Moore’s Law
Technological change is a combination of more and of better technology. A recent study in the journal Science shows that the peak of the rate of change of the world's capacity to compute information was in the year 1998, when the world's technological capacity to compute information on general-purpose computers grew at 88% per year.[68]
[edit] Transistor count versus computing performance
The exponential processor transistor growth predicted by Moore does not always translate into exponentially greater practical CPU performance. Let us consider the case of a single-threaded system. According to Moore's law, transistor dimensions are scaled by 30% (0.7x) every technology generation, thus reducing their area by 50%. This reduces the delay (0.7x) and therefore increases operating frequency by about 40% (1.4x). Finally, to keep electric field constant, voltage is reduced by 30%, reducing energy by 65% and power (at 1.4x frequency) by 50%, since active power = CV2f. Therefore, in every technology generation transistor density doubles, circuit becomes 40% faster, while power consumption (with twice the number of transistors) stays the same.[69]
Another source of improved performance is due to microarchitecture techniques exploiting the growth of available transistor count. These increases are empirically described by Pollack's rule which states that performance increases due to microarchitecture techniques are square root of the number of transistors or the area of a processor.
In multi-core CPUs, the higher transistor density does not greatly increase speed on many consumer applications that are not parallelized. There are cases where a roughly 45% increase in processor transistors have translated to roughly 10–20% increase in processing power.[70] Viewed even more broadly, the speed of a system is often limited by factors other than processor speed, such as internal bandwidth and storage speed, and one can judge a system's overall performance based on factors other
[edit] Transistor count versus computing performance
The exponential processor transistor growth predicted by Moore does not always translate into exponentially greater practical CPU performance. Let us consider the case of a single-threaded system. According to Moore's law, transistor dimensions are scaled by 30% (0.7x) every technology generation, thus reducing their area by 50%. This reduces the delay (0.7x) and therefore increases operating frequency by about 40% (1.4x). Finally, to keep electric field constant, voltage is reduced by 30%, reducing energy by 65% and power (at 1.4x frequency) by 50%, since active power = CV2f. Therefore, in every technology generation transistor density doubles, circuit becomes 40% faster, while power consumption (with twice the number of transistors) stays the same.[69]
Another source of improved performance is due to microarchitecture techniques exploiting the growth of available transistor count. These increases are empirically described by Pollack's rule which states that performance increases due to microarchitecture techniques are square root of the number of transistors or the area of a processor.
In multi-core CPUs, the higher transistor density does not greatly increase speed on many consumer applications that are not parallelized. There are cases where a roughly 45% increase in processor transistors have translated to roughly 10–20% increase in processing power.[70] Viewed even more broadly, the speed of a system is often limited by factors other than processor speed, such as internal bandwidth and storage speed, and one can judge a system's overall performance based on factors other