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The factor factor, part 3

In part 1 and part 2 of this series, I claimed that there is apparently a secret rule in the microprocessor industry that determines the success--or failure--of new chip designs.

The failures included RISC processors, media processors, and intelligent RAM chips, which all sank in spite of clearly demonstrable advantages over alternative solutions. The great success is the programmable graphics processing unit (GPU), which has succeeded in spite of the sometimes wrenching shifts in programming methods and PC system architecture that have been required to support it.

So what's the secret? Simply this: a factor-of-two advantage, even if it'… Read more

The factor factor, part 2

In the first part of this series, I claimed that a great secret in the microprocessor industry largely determines whether new products succeed or fail.

I noted that this secret shouldn't be a secret at all because many people (including myself) have talked about it over the years, but clearly a lot of people are in the dark because they continually disregard it and develop products that are doomed.

I gave several examples of products that failed because their creators didn't know the great secret. Those products included RISC processors, media processors, and intelligent RAM chips, in which processor cores were integrated with memory to eliminate one of the great bottlenecks in computer performance.

During my eight years at Microprocessor Report, I covered the markets for media processors, 3D-graphics chips, network processors, and what I coined extreme processors--chips with large numbers of simple cores running in parallel. Many of these chips were cheaper, easier to design, and twice as fast as competing products--and still failed.

However, some did succeed. The critical factor that made the difference in most of these cases is the essence of the so-called secret.

One of those successes is the graphics processing unit, or GPU.

I was reminded again of the secret at Nvidia's recent GPU Technology Conference, where many of the talks dealt with GPU computing.

(Disclosure: I recently wrote a technical white paper for Nvidia.)

Although the GPU field dates back only five or six years, GPUs have already earned a place alongside CPUs. Each is clearly superior for certain kinds of applications.

This is true in spite of the fact that GPUs aren't nearly as easy to program as CPUs. Like other forms of parallel programming, GPU programming requires new hardware (the GPU itself), significant new extensions for programming languages, and a different mindset for programmers--one that simply wasn't part of standard computer-science curriculum for most of the last 50 years.

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The factor factor, part 1

Listen carefully. I am about to reveal one of the great apparent secrets of the microprocessor industry. This secret largely determines whether new products succeed or fail.

I don't know why it seems to be a secret. It's simple enough. I figured it out early, in my first job in the industry, and I've seen it demonstrated over and over since then. I'm hardly the only one who knows this secret; I've seen dozens of talks that allude to it, and a few that mentioned it specifically. I've talked about it myself in articles I wrote for Microprocessor Report and other publications.

Unfortunately, I've also seen hundreds of products brought to market in apparent ignorance of this simple rule, and they've all failed, wasting the billions of dollars invested in their development. Assuming the developers weren't throwing away their money on purpose, I conclude they must not have known the one basic fact that doomed their projects, which means it must be a secret.

The secret is...… Read more