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Forty Years of Moore's Law
kjh1 writes "CNET is running a great article on how the past 40 years of integrated chip design and growth has followed [Gordon] Moore's law. The article also discusses how long Moore's law may remain pertinent, as well as new technologies like carbon nanotube transistors, silicon nanowire transistors, molecular crossbars, phase change materials and spintronics. My favorite data point has to be this: in 1965, chips contained about 60 distinct devices; Intel's latest Itanium chip has 1.7 billion transistors!"
It's not a law, it's an observation. Did you know the term 'law' for a scientific theory was coined by Isaac Newton, who felt that his 'Laws of Motion' were so right and pervaded the universe so deeply that they had to be a law? He wanted to convey they had a deeper significance than a mere theory. In time of course, even these 'laws' came to be shown to be incomplete or only true for slow moving objects. Ever since, every theory both worthy and crackpot has been called a 'law'. It's about time we returned to the humbler 'theory', 'theorem' or 'observation'. In the case of Moore's 'Law', it's not even a very good theory, since it only describes a very general trend, it cannot predict with any accuracy exactly how fast/how many transistors or elements a chip will have at any time in the future.
By the way, if the Itanium has 1.7 billion transistors, (I'll take the poster's word for it) then one has to ask - are they all pulling their weight? It seems a hell of a lot for what it does. Surely one way to squeeze more out of Moore's Observation is to come up with more efficient architectures and use fewer devices, working more efficiently/smarter/harder. Just a thought.
...the moment. It depends on your application of course. But for number crunching it's hard to beat the GPU on recent graphics cards. For non-graphics applications you can expect speedups from 5-15 times (not %) for things like linear algebra, option pricing and singnal processing. This has been increasing faster than Moore's Law and will likely increase faster. Code written for GPUs is inherently streaming code, and hence easily parallelisable, so many of the complex dependencies that make CPUs tricky to speed up go away. These are exciting times and a big shift in programming paradigm is taking place.
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