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Moore's Law describes an important trend in the that can be inexpensively placed on an Integrated Circuit is increasing Exponentially , doubling approximately every two years. The observation was first made by Intel co-founder Gordon E. Moore in a 1965 paper.1 2 The trend has continued for more than half a century and is not expected to stop for a decade at least and perhaps much longer. 3 Almost every measure of the capabilities of digital electronic devices is linked to Moore's Law: processing speed, memory capacity, even the resolution of LCD screens and digital cameras. All of these are improving at (roughly) Exponential rates as well. This has changed dramatically the ''usefulness'' of digital electronics in nearly every segment of the world economy. Moore's Law is a driving force of technological and social change in the late 20th and early 21st centuries. HISTORY Moore's original statement can be found in his publication "Cramming more components onto Integrated Circuits ", '' Electronics Magazine '' 19 April , 1965 : The term Moore's Law was coined around 1970 by the Caltech professor, VLSI pioneer, and Entrepreneur Carver Mead . 5 Moore may have heard , 2005 In April 2005, Intel offered $10,000 to purchase a copy of the original ''Electronics Magazine.''6 David Clark, an engineer living in the UK, was the first to find a copy and offer it to Intel.7 In 1975, Moore projected a doubling only every two years. He is adamant that he himself never said "every 18 months", but that is how it has been quoted.Although it is sometimes quoted as every 18 months, Intel's official Moore's Law page , as well as an interview with Gordon Moore himself, states that it is every two years. The SEMATECH roadmap follows a 24 month cycle. FORMULATIONS OF MOORE'S LAW hard disk capacity (in GB ). The plot is Logarithmic , so the fit line corresponds to Exponential Growth .]] Several measures of digital technology are improving exponentially. Transistors per integrated circuit. The most popular formulation is of the doubling of the number of Transistor s on Integrated Circuit s every two years. At the end of the 1970s, Moore's Law became known as the limit for the number of transistors on the most complex chips. Recent trends show that this rate has been maintained into 2007. Cost per transistor. An extremely clear formulation. Density at minimum cost per transistor. This is the formulation given in Moore's 1965 paper. It is not about just the density of transistors that can be achieved, but about the density of transistors at which the cost per transistor is the lowest. Understanding Moore's Law As more transistors are made on a chip the cost to make each transistor reduces but the chance that the chip will not work due to a defect rises. If the rising cost of discarded non working chips is balanced against the reducing cost per transistor of larger chips, then as Moore observed in 1965 there is a number of transistors or complexity at which "a minimum cost" is achieved. He further observed that as transistors were made smaller through advances in Photolithography this number would increase "a rate of roughly a factor of two per year". Computing power per unit cost. It is also common to cite Moore's Law to refer to the rapidly continuing advance in computing power per Unit Cost , because increase in transistor count is also a rough measure of computer processing power. On this basis, the power of computers per unit cost - or more colloquially, "bangs per buck" - doubles every 24 months (or, equivalently, increases 32-fold in 10 years). The rate of progression in Disk Storage over the past decades has actually sped up more than once, corresponding to the utilization of Error Correcting Code s, the Magnetoresistive Effect and the Giant Magnetoresistive Effect . The current rate of increase in Hard Drive capacity is roughly similar to the rate of increase in transistor count. Recent trends show that this rate has been maintained into 2007. RAM storage capacity. Another version states that RAM storage capacity increases at the same rate as processing power. Data per optical fiber. According to Gerry/Gerald Butters, Forbes.com - Profile - Gerald Butters is a communications industry veteran LAMBDA OpticalSystems - Board of Directors - Gerry Butters the former head of Lucent's Optical Networking Group at (sometimes called "WDM") increased the capacity that could be placed on a single fiber by as much as a factor of 100. Optical networking and DWDM is rapidly bringing down the cost of networking, further progress seems assured. As a result, the wholesale price of data traffic collapsed in the Dot-com Bubble . Dark Fiber overcapacity and the optical network Bandwidth oversupply greatly exceeding demand of even the most optimistic forecasts by a factor of up to 30 in many areas. Pixels per dollar. Similarly, Barry Hendy of Kodak Australia has plotted the "pixels per dollar" as a basic measure of value for a digital camera, demonstrating the historical linearity (on a log scale) of this market and the opportunity to predict the future trend of digital camera price and resolution. A SELF-FULFILLING PROPHECY: INDUSTRY STRUGGLES TO KEEP UP WITH MOORE'S LAW Although Moore's Law was initially made in the form of an Observation and Forecast , the more widely it became accepted, the more it served as a goal for an entire industry. This drove both Marketing and Engineering departments of Semiconductor manufacturers to focus enormous energy aiming for the specified increase in processing power that it was presumed one or more of their competitors would soon actually attain. In this regard, it can be viewed as a Self-fulfilling Prophecy . The implications of Moore's Law for Computer Component suppliers are very significant. A typical major design project (such as an all-new CPU or hard drive) takes between two and five years to reach production-ready status. In consequence, component manufacturers face enormous timescale pressures—just a few weeks of delay in a major project can spell the difference between great success and massive losses, even Bankruptcy . Expressed as "a doubling every 18 months", Moore's Law would suggests phenomenal progress for Technology over the span of a few years. Expressed on a shorter Timescale , however, this would equate to an average performance improvement in the industry as a whole of close to 1% ''per week''. Thus, for a manufacturer in the competitive CPU market, a new product that is expected to take three years to develop and turns out just three or four months late is 10 to 15% slower, bulkier, or lower in capacity than the directly competing products, and is close to unsellable. If instead we accept that performance will double every 24 months, rather than every 18 months, a 3 to 4 month delay would translate to 8-11% lower performance. As the cost of computer power to the a chip at 180 nm was roughly US$300,000. The cost to tape-out a chip at 90 nm exceeds US$750,000, and is expected to exceed US$1,000,000 for 65 nm.) In recent years, analysts have observed a decline in the number of "design starts" at advanced process nodes (130 nm and below for 2007). While these observations were made in the period after the 2000 economic downturn, the decline may be evidence that traditional manufacturers in the long-term Global Market cannot economically sustain Moore's Law. FUTURE TRENDS Computer industry technology "road maps' predict (as of 2001) that Moore's Law will continue for several chip generations. Depending on the doubling time used in the calculations, this could mean up to a hundredfold increase in transistor count per chip within a decade. The semiconductor industry technology roadmap uses a three-year doubling time for chips with good economics can continue during the next decade.9 Some of the new directions in research that may allow Moore's law to continue are:
12 A decade ago, chips were built using a 500 nm process.
While this time horizon for Moore's Law scaling is possible, it does not come without underlying engineering challenges. One of the major challenges in integrated circuits that use Nanoscale transistors is increase in Parameter Variation and Leakage Current s. As a result of variation and leakage, the Design margins available to do predictive design are becoming harder. Such systems also dissipate considerable power even when not switching. Adaptive and Statistical design along with leakage power reduction is critical to sustain scaling of CMOS . A good treatment of these topics is covered in Leakage in Nanometer CMOS Technologies . Other scaling challenges include: # The ability to control Parasitic Resistance and Capacitance in transistors, # The ability to reduce Resistance and Capacitance in electrical Interconnect s, # The ability to maintain proper transistor Electrostatics to allow the Gate Terminal to control the ON/OFF behavior, # Increasing effect of line edge roughness, # Dopant Fluctuations , # System level power delivery, # Thermal design to effectively handle the dissipation of delivered power, and # Solving all these challenges at an ever-reducing manufacturing cost of the overall system. ULTIMATE LIMITS OF THE LAW On April 13, 2005, Gordon Moore himself stated in an interview that the law cannot be sustained indefinitely: "It can't continue forever. The nature of exponentials is that you push them out and eventually disaster happens." and noted that Transistors would eventually reach the limits of miniaturization at Atomic levels: Krauss and Starkman announced an ultimate limit of around 600 years in their paper "Universal Limits of Computation" , based on rigorous estimation of total information-processing capacity of any system in the Universe . Then again, the law has often met obstacles that appeared insurmountable, before soon surmounting them. In that sense, Moore says he now sees his law as more beautiful than he had realised: "Moore's Law is a violation of Murphy's Law . Everything gets better and better." 14 FUTURISTS AND MOORE'S LAW to earlier Transistor s, Vacuum Tube s, Relay s and Electromechanical computers.]] Extrapolation partly based on Moore's Law has led Futurists such as Vernor Vinge , Bruce Sterling , and Ray Kurzweil to speculate about a Technological Singularity . Kurzweil projects that a continuation of Moore's Law until 2019 will result in transistor features just a few atoms in width. Although this means that the strategy of ever finer Photolithography will have run its course, he speculates that this does not mean the end of Moore's Law: Thus, Kurzweil conjectures that it is likely that some new type of technology will replace current integrated-circuit technology, and that Moore's Law will hold true long after 2020. He believes that the Exponential Growth of Moore's Law will continue beyond the use of integrated circuits into technologies that will lead to the Technological Singularity . The Law Of Accelerating Returns described by Ray Kurzweil has in many ways altered the public's perception of Moore's Law. It is a common (but mistaken) belief that Moore's Law makes predictions regarding all forms of technology, when it actually only concerns Semiconductor Circuit s. Many Futurists still use the term "Moore's Law" in this broader sense to describe ideas like those put forth by Kurzweil. SOFTWARE: BREAKING THE LAW A sometimes misunderstood point is that exponentially improved Hardware does not necessarily imply exponentially improved Software performance to go with it. The productivity of software developers most assuredly does not increase exponentially with the improvement in hardware, but by most measures has increased only slowly and fitfully over the decades. Software tends to get larger and more complicated over time, and Wirth's Law even states humorously that "Software gets slower faster than hardware gets faster". There are problems where exponential increases in processing power are matched or exceeded by exponential increases in complexity as the problem size increases. (See Computational Complexity Theory and Complexity Classes P And NP for a (somewhat theoretical) discussion of such problems, which occur very commonly in applications such as Scheduling .) Due to the mathematical power of exponential growth (similar to the financial power of compound interest), seemingly minor fluctuations in the relative growth rates of CPU performance, RAM capacity, and disk space per dollar have caused the relative costs of these three fundamental computing resources to shift markedly over the years, which in turn has caused significant changes in programming styles. For many programming problems, the developer has to decide on numerous time-space tradeoffs, and throughout the history of computing these choices have been strongly influenced by the shifting relative costs of CPU cycles versus storage space. OTHER CONSIDERATIONS Not all aspects of Computing Technology develop in capacities and speed according to Moore's Law. Random Access Memory (RAM) speeds and Hard Drive seek times improve at best a few percentage points each year. Since the capacity of RAM and hard drives is increasing much faster than is their access speed, intelligent use of their capacity becomes more and more important. It now makes sense in many cases to trade space for time, such as by precomputing indexes and storing them in ways that facilitate rapid access, at the cost of using more disk and memory space: space is getting cheaper relative to time. Moreover, there is a Popular Misconception that the clock speed of a processor determines its speed, also known as the Megahertz Myth . This actually also depends on the number of instructions per tick which can be executed (as well as the complexity of each instruction, see MIPS , RISC and CISC ), and so the clock speed can only be used for comparison between two identical circuits. Of course, other factors must be taken into consideration such as the Bus width and speed of the Peripheral s. Therefore, most popular evaluations of "computer speed" are inherently biased, without an understanding of the underlying technology. This was especially true during the Pentium era when popular manufacturers played with public perceptions of speed, focusing on advertising the clock rate of new products.16 It is also important to note that Transistor Density in Multi-core CPU s does not necessarily reflect a similar increase in practical computing power, due to the Unparallelised Nature of most applications. SEE ALSO
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