dro). The quality of the driver is also critical: hard to imagine NVidia working overnight to fix "some" driver bugs due to requests from gamers. Game cards are notoriously bad in dual monitor configurations.
3. A zillion of cores (triumph of marketing VS common sense) divided by the given clock rate ... gives you just ONE poor old core (Rhino/gh are single-threaded apps) that tries to do the job.
4. Single Xeon E5 2xxx V3 (the higher the clock the LESS the cores = better) would be my recommendation. ECC fast memory is also a must.
PS: Find a friend who operates a "loaded" H/P Z840 and test your defs.
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of lines, etc) but I can't see a way to add the text I need where I need it. If I could get each line for the print run to generate automatically, I can put the rest in manually, so just need something like:
... ; I would do the previous to this manuallyG1 X10 Y5 Z3
G1 X5 Y5 E5
G1 X5 Y15 E10
... ; I would do the rest manually
for a 5 mm line from [10, 5, 3] to [5, 5, 3], followed by a 10mm line from there to [5, 15, 3]. Any pointers greatly appreciated.
Ewan…
Hi Rasmus,
This looks like Tapeworm to me, but you might be interested in testing my Phasma definition.
I'll releasse v0.9.9b with mesh relaxation tomorow I hope.
Fred.
hreads where Thread I solves object A1 and Thread II solves object A2. As soon as A1 is completed, Thread I can move on to object B1 and as soon as A2 completes, Thread II can move on to object B3 (whichever comes first). When both A1 and A2 are complete, we can spawn a new thread (III) to take care of object B2.
If B2 completes before B3, then Thread III will terminate. If B3 completes before B2, then Thread II terminates. Whichever thread is last will pick up execution of object C3. And so on and so forth.
This sort of threading is actually not guaranteed to help much though, as it is likely that the bottleneck components in the network will still need to be handled by a single thread.
A more efficient solution would be to divvy up the execution per component to multiple threads. If you're trying to compute the Curve Closest Point for 10,000 points and your machine contains 4 cores, then we can assign 2,500 points to the first core, 2,500 points to the second core etc.
This approach will actually work when there's only a few bottleneck components and it also means the order in which components are solved is no longer important.
An even more fine-grained approach to threading would be to make the Curve Closest Point function in the Rhino SDK threaded. There's a lot of looping going on in any given Curve CP computation so the curve could be broken up into loose spans where each span is solved by a different core. Then the partial results get consolidated once all threads finish.
The benefit here is that it would be multi-core for everyone, not just Grasshopper components.
The bad news: Some functions in Rhino are not thread-safe. Meaning that data structures such as NurbsCurves cannot be modified from multiple threads at once as it will compromise their validity. You might well end up with invalid curves and quite possible weird crashes. In very bad cases it might even be that a specific function in our SDK can only be running once, so even if you were to duplicate the curve it would still not work.
Until our SDK is thread-safe there can be no global threading in Grasshopper. I don't know where we're headed with this, but I do know that we've started using some threaded algorithms in the display as of Rhino5, so it seems we're at least getting our feet wet.
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David Rutten
david@mcneel.com
Seattle, WA…
Added by David Rutten at 5:47pm on November 17, 2010
the original curve has area A1 and it is scaled by a factor b, then the resulting curve has area A1*b^2. The difference between these areas is your target A2, so we need to solve for the factor b. This is sqrt(1-(A2/A1)) and will be different for each curve. Then we can loft the external and internal curves, cap, and subtract to get the final solid. It's then verified by slicing with normal planes and calculating the areas of the cross sections.
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