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GPGPU Programming

Name: Anonymous 2013-08-18 19:29

I want to get into GPGPU programming out of curiosity.

CUDA or OpenCL? How do I choose which GPU to buy?

Name: Anonymous 2013-08-18 19:34

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Name: Anonymous 2013-08-18 19:39

CUDA a shit

Name: Anonymous 2013-08-18 19:57

>>2
That's what happens when you forget your [code] tags.

Name: Anonymous 2013-08-18 20:00


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Name: Anonymous 2013-08-18 20:20

heterogenous computing a shit

Name: Anonymous 2013-08-18 20:30

>>4
What? It worked exactly as planned.

Name: Anonymous 2013-08-18 21:14

>>7
He probably doesn't have proper proportional fonts install. He probably uses the default proportional fonts.

Name: Anonymous 2013-08-18 22:07

    ._
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    ||. ∧_∧ 
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    ヽ( つと)    ゴロゴロ…
    || (ヽ ) ) ( ̄◎
      )し'し'  |~~~|
     ⊆=⊇   ̄゛

Name: Anonymous 2013-08-18 22:23

>>1
both are shit but CUDA is more shit

use OpenCL 2 or 1.2 but remember! it's shit

Name: Anonymous 2013-08-18 22:26

>>1
Check chapter 2.3 of SICP™ Satori edition.

Name: Anonymous 2013-08-18 23:18

>>11
All the compound data objects we have used so far were constructed ultimately from numbers. In this section we extend the representational capability of our language by introducing the ability to work with arbitrary symbols as data.

Name: Anonymous 2013-08-18 23:24

>>12
Fool, this is from SICP™ [standard] edition.

Name: Anonymous 2013-08-18 23:29

Use OpenCL, and write your own GPU Scheme and compile it to OpenCL SPIR.

Name: Anonymous 2013-08-19 0:50

>>13
OpenCL: usage: -i -a -h -t -b -p

Name: Anonymous 2013-08-19 1:37

How to enjoy OpenCL in 14 steps.
1.buy tons of expensive books about GPGPU programming. They're all outdated but they'll work.
2.buy 1000$ graphics card.
3.Overclock it.
4.Copy algorithms from the internet, slightly modify them.
5.design your own algorithms.
6.create your own OpenCL library of algorithms. Open Source it.
7.Write a project using your library. Open Source it.
8.Wait so alot of people use your OpenCL library.
9....5 years...
10.Graphics cards advance to support newer standards, newer hardware, making your library obsolete.
11.Your 1000$ graphics card is now worth 10$ at best.
12.Your algorithms now rely on legacy features and half of them are deprecated.
13.You cry yourself to sleep and swear off GPGPU programming for good.
14.People write really awesome GPGPU code and you get jealous. Proceed to step 1.

Name: Anonymous 2013-08-19 1:44

>>16
14.

What's so awesome and useful about it?

Name: Anonymous 2013-08-19 2:09

>>17
Its orders of magnitude(x10-x10000) faster if your code is parallelizable and you have a recent video card.

Name: Anonymous 2013-08-19 2:27

>>18
parallel
Buzzword

Name: Anonymous 2013-08-19 2:38

>>19
Buzzword
Buzzword

Name: Anonymous 2013-08-19 2:41

>>19
If parallel is a buzzword for you, perhaps you should return back to 1960's

Name: Anonymous 2013-08-20 11:09

Name: Anonymous 2013-08-20 13:35

>>22
nice dubs

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