AMD does reverse GPGPU, announces OpenCL SDK for x86

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08-16-2009, 04:14 AM
trinibwoy

Quote:

Originally Posted by Chumbucket843

hey im in high school and i take that as an offense but i do see how easy that would be to parallelize and then paste into a forum. it looks like you can do this with a lot of sequences.

Haha, sorry. Wasn't meant as an insult, just pointing out how smart people in high school are ;)

Quote:

Originally Posted by Drwho?

Knowing that you have to deal with numbers that are way behond what the CPU or GPU registers can deal with

Yes, we've already covered that earlier. You would need to implement z=f(x,y) where f is a multiplication function of arbitrarily large numbers. It doesn't change the algorithm, you're still doing a prefix sum on an associative operation. You should already know how to implement f(x,y) since you coded a factorial function on the CPU right? ;)

Quote:

Originally Posted by xVeinx

That being said, the factorials calculation can be computed in parallel, but you'd have to break up the problem and be able to keep track of what has/hasn't been calculated, which would be more effectively done on the CPU.

For non-deterministic problem sets maybe but this is a simplification of an already simple prefix scan. I'm sure Drwho didn't take the time to look it up when I suggested he do so, so I'll help him out.

http://developer.download.nvidia.com...n/doc/scan.pdf

This problem is even simpler because you don't need to store an array of operands since you know that for n! you generate a sequence where i=1..n and for every element a[i], a[i+1]=a+1. So it's just simple math to partition that sequence into M thread blocks each taking M*2 elements from the sequence. Once all blocks are done with their sub-sequences you do a final reduction of all block results and voila.
08-16-2009, 04:19 AM
trinibwoy

Quote:

Originally Posted by Chumbucket843

hey im in high school and i take that as an offense but i do see how easy that would be to parallelize and then paste into a forum. it looks like you can do this with a lot of sequences.

Haha, sorry. Wasn't meant as an insult, just pointing out how smart people in high school are ;)

Quote:

Originally Posted by Drwho?

Knowing that you have to deal with numbers that are way behond what the CPU or GPU registers can deal with

Yes, we've already covered that earlier. You would need to implement z=f(x,y) where f is a multiplication function of arbitrarily large numbers. It doesn't change the algorithm, you're still doing a prefix sum on an associative operation. You should already know how to implement f(x,y) since you coded a factorial function on the CPU right? ;)

Quote:

Originally Posted by xVeinx

That being said, the factorials calculation can be computed in parallel, but you'd have to break up the problem and be able to keep track of what has/hasn't been calculated, which would be more effectively done on the CPU.

For non-deterministic problem sets maybe but this is a simplification of an already simple prefix scan. I'm sure Drwho didn't take the time to look it up when I suggested he do so, so I'll help him out.

http://developer.download.nvidia.com...n/doc/scan.pdf

This problem is even simpler because you don't need to store an array of operands since you know that for n! you generate a sequence where i=1..n and for every element a[i], a[i+1]=a+1. So it's just simple math to partition that sequence into M thread blocks, each block taking n/M elements from the sequence. Once all blocks are done with their sub-sequences you do a final reduction of all block results and voila.
08-16-2009, 04:43 AM
W1zzard

Quote:

Originally Posted by trinibwoy

So it's just simple math to partition that sequence into M thread blocks each taking M*2 elements from the sequence. Once all blocks are done with their sub-sequences you do a final reduction of all block results and voila.

do it please. i genuinely wonder how long it takes to implement and how fast it will run
08-16-2009, 04:47 AM
trinibwoy

Quote:

Originally Posted by W1zzard

do it please. i genuinely wonder how long it takes to implement and how fast it will run

I'm no CUDA programmer but it's trivial to do in Java on multiple CPU threads using BigDecimal. To get this to run in CUDA you would need to build a similiar data structure to represent unbounded integer values on the GPU. That isn't trivial!
08-16-2009, 04:49 AM
W1zzard

Quote:

Originally Posted by trinibwoy

I'm no CUDA programmer but it's trivial to do in Java on multiple CPU threads using BigDecimal.

to me that sounds like an argument _for_ x86 "normal programming" and against gpgpu? ;)
08-16-2009, 04:50 AM
nn_step

Quote:

Originally Posted by W1zzard

i dont think it is possible to make a general statement like "x86 will outperform opencl".

from what i understand, the unique feature of opencl is that it can run threads on the cpu and the gpu. so run iterative/branching/recursive stuff on the cpu and use the gpu for stuff like matrix multiplications.

of course in a commercial environment it is also important how quickly you can get things working. your factorial is a great example for that. 1 hour to write cpu code, weeks to write gpu code. coders cost money, time you often don't have, hardware is cheap, just get a few dozen boxes running the cpu implementation

It is entirely possible to make that statement in cases in which the code is massively Serial.
08-16-2009, 04:52 AM
trinibwoy

Quote:

Originally Posted by W1zzard

to me that sounds like an argument _for_ x86 "normal programming" and against gpgpu? ;)

Nope it just means that people have written billions of lines of code for CPUs over time that other people can reuse. If you had to go reinvent the wheel everytime you wrote a program on a CPU you would have the same problem. Just because there's a lot of code already out there for CPUs doesn't make it "normal programming". Eventually there will be similiar reusable data structures and libraries for GPUs, but right now we're in the inventing the wheel phase :)
08-16-2009, 08:35 AM
Solus Corvus

Quote:

Originally Posted by trinibwoy

Nope it just means that people have written billions of lines of code for CPUs over time that other people can reuse. If you had to go reinvent the wheel everytime you wrote a program on a CPU you would have the same problem. Just because there's a lot of code already out there for CPUs doesn't make it "normal programming". Eventually there will be similiar reusable data structures and libraries for GPUs, but right now we're in the inventing the wheel phase :)

Not only are the programming tools for GPGPU still evolving, the hardware itself is still evolving too. Will future GPUs have more capabilities and fewer limitations then current GPUs? Definitely.

It's the same story with x86. It definitely wasn't pretty in its early days.
08-16-2009, 08:47 AM
W1zzard

Quote:

Originally Posted by Solus Corvus

Not only are the programming tools for GPGPU still evolving, the hardware itself is still evolving too. Will future GPUs have more capabilities and fewer limitations then current GPUs? Definitely.

It's the same story with x86. It definitely wasn't pretty in its early days.

true, but back then there wasnt a competing technology available that was more mature in every regard except that it came with 1 potential order of magnitude execution time reduction promise.

does gpgpu offer anything else other than the promise of being faster?
08-16-2009, 08:56 AM
Solus Corvus

Being faster is the only thing that comes to mind at the moment.

But x86 at its start wasn't faster, easier to develop for, or more mature then some of the other ISAs of the time. IMO it was low cost and ubiquity that lead to its early success.
08-16-2009, 09:52 AM
Drwho?

here is the few 1st digit of 1000000!

82639316883312400623766461031726662911353479789638 73045167775885563379611035645084446530511311463973 35160680421087858854146474695064783618230121097542 32995901156417462491737988838926919341417654578323 93198728024721989396436544455216153392058351993879 89417742062408415939877018188072231692520577371284 36859815222389311521255279546829742282164292748493 88778471244357228595093436211764525449305226584119 76299056190121202414190025341283194330650762070040 51595915117186613844750900755834037427137686877042 09375102350263340124834131491021768454943127363639 90669719529613457333185577827926166902990562020543 69409707066647851950401003675381978549679950259346 66642561397857355976414208350625445088433370019103 46467387684551438607977529149091464312409535521184 54755321622415039686972337454998330671728809536246 48077818320285426377421697236875196416847586471082 42100299778180917677898375179885052302287080350414 43033114386531070330335994687223907101785184740297 83087941364846376812855960498131717659293531630665 17480609772403756072910751424791692204603165502971 69354047663716190369381921896827532213492684751953 50100400335255754749084696578284256885422102069005 13532770029669416657845610334030651805753128367466 39302736238230285383667241957608614717411328876198 68511924639222394549034184071704524191278560391738 18065632292055980341496433939625002178497725812661 13824842989268461523442361118297456949837880338146 87469951709983634639027320349411064589427249057923 05860181434890526382963177342611731621379255430545 09844614644539199499300410119112360492794946012951 30659278247356204716530093403421148592953866359624 47461097303253380618748369952010062827823753289857 99694238906888529567715949209225149583806856514505 96670904555697317271773014004432808102825390252086 48000898390663154978466569004207120665481602926839 38943423565931192630890840193101695234971107709046 97787866113905135675939369298998926409043243894492 10869093844596609832775820823588351223893611134646 66406618178718704409169235099804650072819161636524 13939761918325607097915533516559818774178302468101 91055845341174334013771594704523382014837248934927 36225371480136546463360019692746427132960171671652 65441110722837953835858565183287750920925286592401 94965758088678759206907055438624460369055092476355 26054794986896702217286822255591086864614968403942 96022938804319833255001743711629597524893489578370 95360081696384427809037703763228572556032284560089 99845469405610984854146135108704412702067643651153 44979482463513313444153430254463924329415057983134 38164811961057658077860119374565557615301684268901 39677170011676284699970487161367602640539814056150 76174991110145759325069317658157472438057937126633 21062938475659697058245825083806111628613740584206 59508856753326967758289024053017037388329261183392 62073903655201325025196211382457528966196071713373 73341415000488973314367305436350799224765380907032 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62351886512754025568040309237521504554309701174368 08652424523560028228164422202943923402629217818654 52690700649198013197638563371008688348707330107224 72250649159997013857510699068604406509366375038175 57914864054286848836042284536873941367218188389716 54753213466662227163911429345359079653372969098519 14846664193968882121700414718204757584484078048781 14257929120817684171224838060353311367511135615527 70449707301662433106895624383530559736019003112110 72020866021426553821633353923648307962410874958002 67720169938502515632718842424940224358886194979390 72475406126376873006931187184791894427432074521337 59816597924544429589765412718696937356893948346780 05719364538544515294747200727654260333498197915843 65365013852685543053805849197374826376294917478528 30927822199571032113729437223319867479721169647135 23319712049279923901215349954492374715372117145743 78628554826134753344458214096739964519670156700440 90950849772085174459494029999425599705281308573001 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00831409048755120184963446220571445326684183824083 259252131
.....
.....
.....
For Those who are crazy enough and what to see for your eyes ...
The world document with 1000000! inside ... 2.55MB

The screen shot:
http://v12extreme.com/ipost/amillion_facto.png
Without ANY optimization, it toke 43735260 milliseconds, about 728 minutes ... around 12 hours ...
With some threading, I think I can get it down dramatically, I ll just do it for the fun of it ...
The 8MB of my Nehalem will be really useful between the combining of splited multiplications ...

Basically: Done!
08-16-2009, 09:56 AM
Final8ty

I can do it faster in my head, its just that copy & paste to the forum from my head is problematic.
08-16-2009, 10:04 AM
nn_step

Quote:

Originally Posted by Final8ty

I can do it faster in my head, its just that copy & paste to the forum from my head is problematic.

Then drop to scientific notation and give us the first 13 digits [which is more than enough for any engineering project]
08-16-2009, 10:29 AM
Drwho?

Quote:

Originally Posted by W1zzard

i dont think it is possible to make a general statement like "x86 will outperform opencl".

from what i understand, the unique feature of opencl is that it can run threads on the cpu and the gpu. so run iterative/branching/recursive stuff on the cpu and use the gpu for stuff like matrix multiplications.

of course in a commercial environment it is also important how quickly you can get things working. your factorial is a great example for that. 1 hour to write cpu code, weeks to write gpu code. coders cost money, time you often don't have, hardware is cheap, just get a few dozen boxes running the cpu implementation

OpenCL is to Java what Larrabee new instruction is the Assemby code ... See the point?

Francois
08-16-2009, 11:00 AM
W1zzard

Quote:

Originally Posted by Drwho?

OpenCL is to Java what Larrabee new instruction is the Assemby code ... See the point?

Francois

no :)
08-16-2009, 11:38 AM
Drwho?

Quote:

Originally Posted by W1zzard

no :)

OpenCL is a softare layer ... with drivers ... it has concequences ... and overhead .. Assemble code is known to be the fastest code on any architecture.
A Simple layer between LrB new instruction and the programmer will do. we all know that as soon as a desktop application need performance, it does down to ASM.

The massive number of Java Desktop is gone, no more need of those ... almost every computer runs x86 from AMD, intel or VIA.

Last word ... Drivers seems to be a problem, there are a lot of empirical about this ... an healthy PC uses less driver in the long run.
Before people make fun of the intel drivers, some should clean up on the front of their doors ... ;-)

http://media.arstechnica.com/news.me...stacrash-1.jpg
08-16-2009, 11:43 AM
W1zzard

Quote:

Originally Posted by Drwho?

OpenCL is a softare layer ... with drivers ... it has concequences ... and overhead .. Assemble code is known to be the fastest code on any architecture.
A Simple layer between LrB new instruction and the programmer will do. we all know that as soon as a desktop application need performance, it does down to ASM.

Last word ... Drivers seems to be a problem, there are a lot of empirical about this ... an healthy PC uses less driver in the long run.
Before people make fun of the intel drivers, some should clean up on the front of their doors ... ;-)

http://media.arstechnica.com/news.me...stacrash-1.jpg

i haven't seen anyone write assembler code on x86 in many years. even drivers are coded in a high level language. compilers are fairly smart, they produce good code, better than 90% of asm coders. asm code is a nightmare to maintain.
what do you code in asm at intel?
08-16-2009, 11:43 AM
Talonman

Quote:

Originally Posted by Drwho?

OpenCL is a softare layer ... with drivers ... it has concequences ... and overhead .. Assemble code is known to be the fastest code on any architecture.

I believe you...

I posted once that I thought OpenCL would probably be slower than CUDA and got my head bit off! ;)

The thread was locked in the end.
08-16-2009, 11:52 AM
W1zzard

Quote:

Originally Posted by Talonman

I posted once that I thought OpenCL would probably be slower than CUDA and got my head bit off! ;)

i doubt a significant difference will exist, even if nv implements opencl on top of cuda. got the link to the thread?
08-16-2009, 11:58 AM
Drwho?

Quote:

Originally Posted by Talonman

I believe you...

I posted once that I thought OpenCL would probably be slower than CUDA and got my head bit off! ;)

The thread was locked in the end.

Please read totally before replying
hehehhe ... CuDa is like OpenCL ... a thick layer between the programmer and the hardware.

For the next few months, it may be fine, but we can't have a PC fragmented with different APIs ... Don't get me wrong, I was a super lover of GLIDE, but it did not survive the "Standardization" ... I guess Cuda is in the same position. OpenCL and DirectX compute are more into the position to standartize ... but long term, Integration will do its work.
The Network cards, sound cards are use to be separated, they are now in the motherboard, with System on chip very soon in the CPU.
This is the nature of this industry, when the CPU catch up from the bottom, it does start doing custom functions with Generic transistors, the CPU goes through transformation to do this, and we are at the beginning of Generic Purpose cores x86 to get into GFX.

The soft drivers for sound cards were never as good as a Creative lab 48 bits cards, but they catch up the all required feature set. they are now a huge majority shipping.

Let's all share opinions, without beating on each other, I may be right, I may be wrong ... It is just what I think, and you are free to dissagree.

Francois
08-16-2009, 12:08 PM
Drwho?

Quote:

Originally Posted by W1zzard

i haven't seen anyone write assembler code on x86 in many years. even drivers are coded in a high level language. compilers are fairly smart, they produce good code, better than 90% of asm coders. asm code is a nightmare to maintain.
what do you code in asm at intel?

I use mostly compilers for the soft architecture ... but most of the code that need performance on PCs IS using ASM.

* Most of the video codec do. Check x264 code or vTune DivX or windows Media ...
* Most of the 3D Rendering like 3DSMax uses intrinsics, almost a 1:1 translation to ASM.
* Most of audio programs have the MP3 parts using MMX.
* Most of the Drivers, including NV and ATI are using ASM to managed cache pollution properly when sending through PCIexpress ... MOVNT and so on ...

The list is very long, you just don t see it because we don t explain much details ...

as soon as Performance can give you a competitive advantage over your software competitor, people use ASM.

I help a lot of those guys.

Francois
08-16-2009, 02:27 PM
Talonman

Quote:

Originally Posted by Drwho?

Let's all share opinions, without beating on each other, I may be right, I may be wrong ... It is just what I think, and you are free to dissagree.

Francois

I am with you 100%. I was kind of fired up yesterday, and might have gotten out of line toward you. Sorry about that.

I think we can all learn from each other. :)
08-16-2009, 04:21 PM
trinibwoy

Quote:

Originally Posted by W1zzard

true, but back then there wasnt a competing technology available that was more mature in every regard except that it came with 1 potential order of magnitude execution time reduction promise.

I hope you don't believe x86 to be the pinnacle of human innovation in ISA's :)

Quote:

Originally Posted by Solus Corvus

Being faster is the only thing that comes to mind at the moment.

And the only thing that matters. It's not like x86 is any more parallel friendly than other platforms.

Quote:

But x86 at its start wasn't faster, easier to develop for, or more mature then some of the other ISAs of the time. IMO it was low cost and ubiquity that lead to its early success.

Exactly.
08-16-2009, 11:30 PM
Smartidiot89

Quote:

Originally Posted by Drwho?

The Network cards, sound cards are use to be separated, they are now in the motherboard, with System on chip very soon in the CPU.
This is the nature of this industry, when the CPU catch up from the bottom, it does start doing custom functions with Generic transistors, the CPU goes through transformation to do this, and we are at the beginning of Generic Purpose cores x86 to get into GFX.

So going abit off-topic perhaps... How far do you think System on Chip will develop within the coming years? I'd like your personal opinion on this

It is obvious that the 3 major PC vendors Intel, AMD and Nvidia have a large interest in this and all have a solution/is working on one that will be released very soon. Looking 10 years ahead will something have changed with out tradition computers with a motherboard, CPU and the option for a stronger GPU would we want to, or have we in 10 years started the transition whereas the difference between a CPU and the GPU has become minimal if not none-existant anymore, and all PCs will consist of a single-chip on a PCB instead of the classical motherboard, CPU, GPU etc. etc.

We have seen SoC taking it's way into Phones and Smaller hand-carried products and soon Qualcomm will release their smartbooks, not performance monsters, but it's SoC in a small package which I can carry around and use as a PC together with a OS (not Windows ofc.).

So my question really is, will this pattern follow into the PC market?
08-17-2009, 12:03 AM
W1zzard

Quote:

Originally Posted by trinibwoy

I hope you don't believe x86 to be the pinnacle of human innovation in ISA's :)

so which isa is more successful?

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