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 Some more variations on the idea. How small could we make the nanoprobes so that we would not need to use a ground based laser at all? Again I'm assuming we have a method to have the nanoprobes link up after launch to form a macro-scale spacecraft through self-assembly.

 We could use either the ionized solar wind or solar light to provide the propulsion. Since graphene has already been produced at centimeter scales we can assume the "sail" is made of graphene. This would provide a very lightweight yet strong sail, especially important for the ultra-small nanoprobes needed for this scenario.

  We want the nanoprobes to reach relativistic speeds as with the Hawking proposal. How much mass could they have when the only propulsion is the solar wind or solar light?

 

  Bob Clark

 

 

 

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2 hours ago, Bill Phil said:

Moore's law has been observed to be slowing... Computers, lasers, experiments, and the like May not be as small as hoped.

Computers are not getting faster, they are laterizing into tasking. If you need a single fast processor, its all but stopped. 

 

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32 minutes ago, PB666 said:

Computers are not getting faster, they are laterizing into tasking. If you need a single fast processor, its all but stopped. 

 

Moore's law isn't really about speed, but all capabilities in general.

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On 5/7/2016 at 4:01 PM, PB666 said:

Computers are not getting faster, they are laterizing into tasking. If you need a single fast processor, its all but stopped. 

 

And if I need to compile code, render CGI, or compress audio, I honestly don't give a crap if computer got faster, or if my tasks are now parsed between a thousand of them. If I can compile in minutes instead of days, that's good enough for me.

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2 hours ago, K^2 said:

And if I need to compile code, render CGI, or compress audio, I honestly don't give a crap if computer got faster, or if my tasks are now parsed between a thousand of them. If I can compile in minutes instead of days, that's good enough for me.

But the software needs to be specifically programmed in many cases to take advantage of that,mwhich means you get really big operating systems for the various levels of tasking and really big programs. 

 

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More like programming paradigms and compilers must be different. Which, in certain circles, they already are. :) 

The programs are larger, yes. But that hasn't been the bottleneck since 8bit days. And the operating systems, compilers, and libraries are written by "someone else", which has always been the case. The responsibility is then on the programmer to know how to use their tools, which, again, is nothing new.

Whether you are a GPU programmer or a cloud compute programmer, it really comes down to learning techniques for efficient computation by thousands of machines, as well as limitations of your particular hardware. And yet again, that's the same thing as learning to program efficiently on any hardware that came before. And this is the direction everything is going. To utilize a typical off-the-shelf CPU efficiently, you need to keep 8 logical cores (typically 4 physical cores with hyperthreading) busy, which means running at least 8 threads concurrently. Ditto consoles, but 6 threads is the magic number there. So even if you aren't programming for GPU or clouds/clusters, you still have to know how to do things in parallel, and we're simply going to see more of that. My prediction is home operating systems and C++ standard supporting massive parallel computation by early 2020s.

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