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The Law that Keeps on Giving
March 22, 2020
Moore's law is the observation that the number of transistors in a dense integrated circuit doubles about every two years. The observation is named after Gordon Moore, who together with Bob Noyce ( the inventor of the integrated circuit) founded Fairchild Semiconductor and Intel , In 1965 the paper described a doubling every year in the number of components per integrated circuit and projected this rate of growth would continue for at least another decade.[3] In 1975,[4] looking forward to the next decade,[5] he revised the forecast to doubling every two years, a compound annual growth rate (CAGR) of 40%.[6][7][8] growth in raw computational power achieved with each new generation of ICs. Fifty-five years later, IC Insights’ 2020 edition of The McClean Report (released in January) shows how over the past five decades, DRAMs, flash memories, microprocessors, and graphics processors have tracked the Moore’s curve. Factors such as power consumption and challenges associated with scaling limitations have cut into the transistor growth rates of some IC products during the last 10-15 years. For example, DRAM transistor counts were increasing at the average rate of about 45% per year through the early 2000s but slowed to about 20% through the 16Gb generation that appeared in 2016. Samsung began volume production with single-chip 16Gb DRAM devices near the end of 2016. One year earlier Samsung initiated volume production of 12Gb DRAM chips, and 8Gb devices one year before that. The DDR5 standard still being finalized by JEDEC includes monolithic 24Gb, 32Gb, and 64Gb devices.
Figure 1: Transistor Count Trends
March 22, 2020
Moore's law is the observation that the number of transistors in a dense integrated circuit doubles about every two years. The observation is named after Gordon Moore, who together with Bob Noyce ( the inventor of the integrated circuit) founded Fairchild Semiconductor and Intel , In 1965 the paper described a doubling every year in the number of components per integrated circuit and projected this rate of growth would continue for at least another decade.[3] In 1975,[4] looking forward to the next decade,[5] he revised the forecast to doubling every two years, a compound annual growth rate (CAGR) of 40%.[6][7][8] growth in raw computational power achieved with each new generation of ICs. Fifty-five years later, IC Insights’ 2020 edition of The McClean Report (released in January) shows how over the past five decades, DRAMs, flash memories, microprocessors, and graphics processors have tracked the Moore’s curve. Factors such as power consumption and challenges associated with scaling limitations have cut into the transistor growth rates of some IC products during the last 10-15 years. For example, DRAM transistor counts were increasing at the average rate of about 45% per year through the early 2000s but slowed to about 20% through the 16Gb generation that appeared in 2016. Samsung began volume production with single-chip 16Gb DRAM devices near the end of 2016. One year earlier Samsung initiated volume production of 12Gb DRAM chips, and 8Gb devices one year before that. The DDR5 standard still being finalized by JEDEC includes monolithic 24Gb, 32Gb, and 64Gb devices.
Figure 1: Transistor Count Trends
Transistor counts in Intel’s PC microprocessors grew approximately 40% per year through 2010, but the rate dropped to half that in the years following. Transistor count increases for the company’s server MPUs paused in the mid- to late-2000s but then started growing again at the rate of about 25% per year. Intel stopped revealing details of transistor counts in 2017. Transistor counts for Apple’s A series application processors used in its iPhones and iPads have increased at the annual rate of 43% since 2013. That rate includes as the most recent endpoint the A13 processor, with its 8.5 billion transistors. In the first half of 2020, Apple is expected to unveil an iPad Pro based on a new A13X processor. High-end GPUs from Nvidia have incredibly high transistor counts. Unlike microprocessors, GPUs and their highly parallel structure do not contain a significant amount of cache memory. Some of the latest GPUs from Nvidia are neural network processing units (NPUs) designed specifically for AI and machine learning. The powerful drive of the IC industry to innovate its way over and around technology barriers can never be underestimated, but there are some very dramatic shifts underway regarding how ICs are designed and manufactured. Though some roadblocks standing in the way of progress toward future generations look more like high walls than hurdles, Moore’s Law continues to hold for the total IC industry.