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CPU Speed Remaining Flat - Intro to Parallel Programming

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    To understand why the GPU is such an interesting processor today, we'll start
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    with technology trends. Why the world has gone parallel. And first, we'll start
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    with some good news. Modern processors are made from transistors. And each year,
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    those transistors get smaller and smaller. This graph is from Stanford CPUDB
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    project, thanks guys.
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    What it shows is, the feature size of processors over time, or the feature size
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    is the minimum size of a transistor or wire on a chip. So, what we're seeing is,
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    this is time going in this direction. So, that's a long time ago and that's
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    today. And this is the feature size, so how big transistors are. And notice that
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    it's getting smaller and smaller every generation. So, when you hear talk about
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    45 nanometer process, or a 22 nanometer that's what we're referring to, the
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    feature size. So, we see that it's consistently going down over time. As the
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    feature size decreases, transistors get smaller, run faster, use less power, and
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    we can put more of them on a chip. And the consequence is that we have more and
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    more resources for computation every single year. However, we've also got some
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    bad news. Historically, as transistors improved, processor designers would then
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    increase the clock rates of processors, running them faster and faster every
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    year. Let's take a look at this diagram of clock speeds over the years. So
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    again, we have time going on this axis, okay? So, a long time ago, today. And
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    here, we have clock frequency. How fast we're clocking these transistors.
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    Historically, one of the primary drivers of clock performance has been clock
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    speed increases. So, we see over many years, we see clock speeds continue to go
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    up. However, over the last decade, we see that clock speeds have essentially
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    remained constant.
タイトル:
CPU Speed Remaining Flat - Intro to Parallel Programming
概説:

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Video Language:
English
Team:
Udacity
プロジェクト:
CS344 - Intro to Parallel Programming
Duration:
01:37

English subtitles

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