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[Giz] Intel + MS to Reinvent Computing - Page 2

post #11 of 18
Quote:
Originally Posted by joemaniaci View Post
You know it always comes up that to get my four cores used, it would be very difficult, wouldn't it be easier to just make a chip near the cpu that automatically divies up the workload for all four cores. Don't know anything about the inner workings of processors, but it seems like the easiest for me.
Hard to explain without writing alot, but it really isn't that easy.

If you are doing a sequence of things that each depend upon the result of the previous item, you have a problem.

For example, if you do this, 2 + (5 * 6) + 8 = 40

You have one core do the multiplication inside the parenthesis, and the other, do the outside addition. In this case, you're ok.

But what about (5 * 6) * 5 + 2 = 152

One core does the multiplication inside the parenthesis, and that other does the outside math. Due to order of operations you must wait for the 5 * 6 to resolve to 30 before continuing. So the second core is waiting for the first. At this point you might as well just have let one core do the entire problem.

This is probably the simplist reason why multithreading doesn't always work or help.

What about things like physics? Core 1 takes care of one entities movement, core 2 takes care of the other. Core 1 realizes that its entity just collided with another, so it does calculations for that collision. But wait, just as core 1 was doing that calculation, core 2 moved its entity, and now the two entities aren't even touching. So one thinks there is a collision, and the other things they're not touching! That is a problem. And if you have them communicate information to each other about the state of the entities you'd get reliable physics, but each core would be waiting on information from the other, at which point you lose most the benefit of having multiple threads for your physics.
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post #12 of 18
Quote:
Originally Posted by DuckieHo View Post
That's freaking rediciously hard to do. The thread manager would have to understand all the code that will be going through it, predict which threads can be separated, schedule them, and make sure there is no locking. If anyone could figure out how to produce such a chip, they would get a few hundred million for the technology.
Current generation graphcis cards use Stream processors which rely on parallel processing.
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post #13 of 18
Quote:
Originally Posted by Lelouch View Post
Current generation graphcis cards use Stream processors which rely on parallel processing.
This is because the information being processed by GPUs is extremely linear and consistant.
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post #14 of 18
Awesome! Time for someone to give multi-core processing the software it needs.
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post #15 of 18
Quote:
Originally Posted by Lelouch View Post
Current generation graphcis cards use Stream processors which rely on parallel processing.
They rely on parallel processing since they process very parallel large data sets. Try to ask a video card to do path prediction or out of order operation. Two very different needs.

Analogy:
Quad CPU = 4 Nobel mathematicians
128 Stream Processors = 128 high schoolers.

Ask the 4 Nobel laureates to do 100,000 arthimetic problems = Doable, but would take some time.
Ask the 128 high schooler to solve differential equations = Doable but would take months/years.

Ask the 128 high schooler to do 100,000 arthimetic problems = Doable 32 times faster than just 4 people.
Ask the 4 Nobel laureates to solve differential equations = Doable in a few hours.
Once again...
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post #16 of 18
Quote:
Originally Posted by DuckieHo View Post
They rely on parallel processing since they process very parallel large data sets. Try to ask a video card to do path prediction or out of order operation. Two very different needs.

Analogy:
Quad CPU = 4 Nobel mathematicians
128 Stream Processors = 128 high schoolers.

Ask the 4 Nobel laureates to do 100,000 arthimetic problems = Doable, but would take some time.
Ask the 128 high schooler to solve differential equations = Doable but would take months/years.

Ask the 128 high schooler to do 100,000 arthimetic problems = Doable 32 times faster than just 4 people.
Ask the 4 Nobel laureates to solve differential equations = Doable in a few hours.
Right, its basically the difference between quality and quantity; different situations favor one or the other.
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post #17 of 18
Quote:
Originally Posted by DuckieHo View Post
They rely on parallel processing since they process very parallel large data sets. Try to ask a video card to do path prediction or out of order operation. Two very different needs.

Analogy:
Quad CPU = 4 Nobel mathematicians
128 Stream Processors = 128 high schoolers.

Ask the 4 Nobel laureates to do 100,000 arthimetic problems = Doable, but would take some time.
Ask the 128 high schooler to solve differential equations = Doable but would take months/years.

Ask the 128 high schooler to do 100,000 arthimetic problems = Doable 32 times faster than just 4 people.
Ask the 4 Nobel laureates to solve differential equations = Doable in a few hours.
Superb analogy =)
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post #18 of 18
Quote:
Originally Posted by DuckieHo View Post
They rely on parallel processing since they process very parallel large data sets. Try to ask a video card to do path prediction or out of order operation. Two very different needs.

Analogy:
Quad CPU = 4 Nobel mathematicians
128 Stream Processors = 128 high schoolers.

Ask the 4 Nobel laureates to do 100,000 arthimetic problems = Doable, but would take some time.
Ask the 128 high schooler to solve differential equations = Doable but would take months/years.

Ask the 128 high schooler to do 100,000 arthimetic problems = Doable 32 times faster than just 4 people.
Ask the 4 Nobel laureates to solve differential equations = Doable in a few hours.
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