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WebGL is already secured to be a success; only IE-users will not have the 3D-web without plugin. But once sites like Wikipedia starts to offer 3D-imagery of the human body and buildings (as we know in Google Earth’s KML-format), things can go really fast in favour of the WebGL-supported browsers. This is important, because the balance between the computers/smartphones and the servers (you know: internet) just got somewhat more connected. I was first somewhat critical, because I want the web to have content (text and images) and not be “an ultimate experience” – luckily it turned out to be good for the content. I’m looking forward to Wikipedia and hardware accelerated services like Streetview!
A possible next step would be WebCL. But is it technically possible? And what would the internet-landscape be to be ready for such thing? Khronos did mention to be working on such technique, according to this article. But not much attention was given to it. So I was happy to see a GSOC11 proposal WebCL-plugin for Firefox by Adrien Plagnol. They even have some code. But it was already finished for Firefox 4 (Windows and Linux), I learnt about a week ago.
It is very simple: it is a Javascript-version of the host-specific OpenCL code. Kernels are just kernels as we know them.
Nokia has put together a very nice WebCL homepage, which contains tutorials. And at lesson one we see how it looks like:
function detectCL() {
// First check if the WebCL extension is installed at all
if (window.WebCL == undefined) {
alert("Unfortunately your system does not support WebCL. " +
"Make sure that you have both the OpenCL driver " +
"and the WebCL browser extension installed.");
return false;
}
// Get a list of available CL platforms, and another list of the
// available devices on each platform. If there are no platforms,
// or no available devices on any platform, then we can conclude
// that WebCL is not available.
try {
var platforms = WebCL.getPlatformIDs();
var devices = [];
for (var i in platforms) {
var plat = platforms[i];
devices[i] = plat.getDeviceIDs(WebCL.CL_DEVICE_TYPE_ALL);
}
alert("Excellent! Your system does support WebCL.");
} catch (e) {
alert("Unfortunately platform or device inquiry failed.");
}
}
As you can see this is very understandable code, if you know the basics of OpenCL and JavaScript. It is built for stability, so it seems to crash less easily than I expected.
I’ve written/tweeted a lot about OpenCL wrappers and how I think the OpenCL-ecosphere advances mainly by the growing up of the wrappers. Complaints about the far too long initialisation of OpenCL-software can easily be put in just a few lines of code. We now start from scratch again, but I will not be wonder-struck if there will be a jQuery-plugin released soon.
In the first place, think real-time encryption which can be adapted per user without the browser knowing. There are many more reasons all going back to the demand to have a browser-based computer (like Google is trying with its ChromeOS). All OS-APIs need to be available in a HTML5-like language and this is exactly that.
What are you still doing here? Install the Opencl-plugin for Firefox 4 and try Nokia’s online OpenCL-sandbox now! +1 for crashing it, +2 for sending in a bug-report.
After IBM-compatible clones took over from Apple, Atari and ZX Spectrum, we just got used to that a PC is an X86 with MS Windows and Office on it. Around a decade ago Apple fought back with OSX on which Windows 7 (launched in 2009) was the first real answer. Meanwhile Apple switched to Intel, since IBM was not fast enough with the development of the POWER-processor – a huge operation, which seemed a one-time-only step for Apple at the time. SemiAccurate now speaks of Intel being replaced by ARM on Apple’s laptops.
A few weeks ago I asked Computer Science students if they knew ARM. Not even 1% had heard of it, but lots more knew there was a Samsung-chip in their smartphone. So what’s going on without us knowing it?
I’ll try to describe the market for a few key-years and then try to put the big names in it. There is a lot going on between i.e. Nvidia, Samsung, Texas Instruments and Imagination Technologies in the ARM-market, but I’ll leave that out of the story. Also not mentioned are the game-consoles and servers, but they did have big influences on the home-PC market.
In the picture at the right you see an idea of how fast the markets would have grown from a 2006 perspective. (Click on it for the full report). You see that the explosive growth of smartphones was not expected; the other detail is that the cloud also was not foreseen here.
After reading you understand why Nvidia focuses so much on HPC and mobile.
After IBM-compatible clones took over from Apple, Atari and ZX Spectrum, we just got used to that a PC is an X86 with MS Windows and Office on it. Around a decade ago Apple fought back with OSX on which Windows 7 (launched in 2009) was the first real answer. Meanwhile Apple switched to Intel, since IBM was not fast enough with the development of the POWER-processor – a huge operation, which seemed a one-time-only step for Apple at the time. SemiAccurate now speaks of Intel being replaced by ARM on Apple’s laptops.
A few weeks ago I asked Computer Science students if they knew ARM. Not even 1% had heard of it, but lots more knew there was a Samsung-chip in their smartphone. So what’s going on without us knowing it?
I’ll try to describe the market for a few key-years and then try to put the big names in it. There is a lot going on between i.e. Nvidia, Samsung, Texas Instruments and Imagination Technologies in the ARM-market, but I’ll leave that out of the story. Also not mentioned are the game-consoles and servers, but they did have big influences on the home-PC market.
In the picture at the right you see an idea of how fast the markets would have grown from a 2006 perspective. (Click on it for the full report). You see that the explosive growth of smartphones was not expected; the other detail is that the cloud also was not foreseen here.
After reading you understand why Nvidia focuses so much on HPC and mobile.
You might have read about Molybdenite a few months ago. It is more efficient than Graphene which is in turn more efficient than good old Silicon, most notable energy-wise. Magazine ‘Nature’ had an article on it, which is summarised by Psychorg, so check it out. The claim it is 100 000 times more efficient than Silicon (and more efficient than the already very promising Graphene). This fan-free Silicon-replacer would be a major disaster for the cooling-industry!
But what would change for us? We are now on the edge to move to ARM (started by the smartphone- and tablet-industry), but is al this needed if the energy-costs drop to prices comparable to the costs to keep ice-cream cold on the North-Pole (20 years ago). This technique would give huge potential to Fusion-chips which now have a long way to go, to solve the heat-problem. But since it would take several years (and thus decades in hi-tech years) to get these chips on the market, no assumptions for market-share can be made based on what will happen in a few years.
So this is European ARM (and licensees around the world) vs US Intel and AMD. The sarcastic joke among me and a few friends make, is that the fight of the past 20, 30 years between the economic US and EU is actually about who has the money to hire the most Asians, to develop the revolutionising devices. But as long as the US and EU have the feeling we are actually the equation of the competition as we are a massive 12% of the world-population, I won’t be behind the facts too much.
Since batteries don’t evolve as fast as processors, the power-problem needed to get slashed differently. A mayor reason for choosing ARM is that it uses less energy than X86, just like LCD/TFT is replaced by e-ink and organic LEDs and memory is non-volatile in portable devices.
In case we get a big reduction for CPU and memory, then the efficiency of the architecture is less of a problem. So then Intel and AMD can re-enter the market again, but then with much more powerful devices. Until then ARM-licensees like NVIDIA and ImTec have a better market if it comes to near-future devices. As I expected more tablet-manufacturers come up with docking-stations to replace the PC with a tablet. AMD and Intel have to keep surprising (and probably protect their market) the coming years to avoid losing from ARM. In other words: the coming years will be exciting how the consumer-market looks like and which companies deal in it. When thinking about these years, keep in mind what Windows XP has thought us: computers are fast enough for what average Joe wants to do with it. Hey, I use my laptop for OpenCL and the big screen, for the rest I use my mobile phone.
While I did not see it as a serious problem last year, the heat-problem for a GPU+CPU on one chip is quite a challenge. Waiting for the Molybdrenite or Graphene chips to mature will be like digging your own grave. Each step forward will result in two new products: one which is more power and/or heat efficient, and one which is more powerful. Since the competition from ARM-companies is heavy, the chances that the focus will be on more powerful Hybrid CPUs is bigger. As I stated above the losses are in the low-power area. Intel and AMD are very aware of this challenge.
Have you checked the differences between DirectX 10 and 11 games? Just check the discussions on the growing side of not needing to support DirectX 11, because 10 is good enough. Also here, the demand is higher to have the same graphics-quality for less money on more portable devices. Hybrid CPUs will eat the GPU-market for sure.
ARM-processors are hybrid processors. That’s all I tell, so you can -in combination with all stated above- formulate your own conclusions. I was very surprised NVIDIA started targeting ARM with their high-end GPUs, but was this a real bad idea?
Reduction of energy-costs for processors will reduce the head-less servers in the data-centre enormously. Internet costs loads of energy, both the transport and the servers – this will reduce the server-part of energy-consumption-sum with quite some factors. All positive news.
But if it all this becomes true, that chips don’t use much energy anymore and actually mobile internet and other radios take the most, what will happen to the cloud? Will you upload your video to get it processed or put your mobile in the sun to charge it while waiting a shorter period?
We need arithmetic, media-processing and input/output; we all have that. We need long battery-life, a good screen and a fast way to input our data and commands; we get more of that each day. But heat-production is Silicon limits a lot, so we get the perfect electronic device the moment we can replace Silicon. Getting rid of the heat could give us square chips, with challenges like reinventing the socket and multi-multi-layerness.
So the question to you: is in The Last Nimzy sequel (you know, the movie with the molybdenite rabbit) a logo of Intel, AMD, ARM or another company found?
My todo-list gets too large, because there seem so many things going on in GPGPU-world. Therefore the following article is not really complete, but I hope it gives you an idea of the product.
ENZO was presented as the alternative to CUDA and OpenCL. In that light I compared them to Intel Array Building Blocks a few weeks ago, not that their technique is comparable in a technical way. PathScale’s CTO mailed me and tried to explain what ENZO really is. This article consists mainly of what he (Mr. C. Bergström) told me. Any questions you have, I will make sure he receives them.
ENZO is a complete GPGPU solution and ecosystem of tools that provide full support for NVIDIA Tesla (kernel driver, runtime, assembler, code generation, front-end programming model and various other things to make a developer’s life easier).
Right now it supports the HMPP C/Fortran programming model. HMPP is an open standard jointly developed by CAPS and PathScale. I’ve mentioned HMPP before, as it can translate Fortran and C-code to OpenCL, CUDA and other languages. ENZO’s implementation differs from HMPP by using native front-ends and does hardware optimised code generation.
You can learn ENZO in 5 minutes if you’ve done any OpenMP-like programming in the past. For example the Fortran-code (sorry for the missing indenting):
!$hmpp simple codelet, target=TESLA1
subroutine add(n, a, b, c)
implicit none
integer, intent(in) :: n
real, intent(in) :: a(n), b(n)
real, intent(out) :: c(n)
integer :: ido i=1, n
if (a(i) > 5) then
c(i) = 1
else
c(i) = 2
endif
enddoend subroutine add
subroutine test
integer, parameter :: n=10
real :: a(n), b(n), c(n)
integer :: ido i=1, n
a(i) = i
b(i) = i
enddo!$hmpp simple callsite
call add(n, a, b, c)
end subroutine test
This is somewhat different we know from OpenCL, mostly because we don’t need a specific kernel. This is because with just a few hints, the compiler does a lot for you. Like in OpenMP you tell the compiler with directives/pragmas which parts you want to be parallelised. More explanation can be found in the user manual [PDF]. You can try it out yourself for free if you have a Tesla-card; future versions of ENZO will support more architectures.
There was some guy at Microsoft who understood IT very well while being a businessman: “Developers, developers, developers, developers!”. You saw it again in the mobile market and now with OpenCL. Normally I watch his yearly speech to see which product they have brought to their own ecosphere, but the developers-speech is one to watch over and over because he is so right about this! (I don’t recommend the house-remixes, because those stick in your head for weeks.)
Since OpenCL needs to be optimised for each platform, it is important for the companies that developers start developing for their platform first. StreamComputer is developing a few different Eclipse-plugins for OpenCL-development, so we were curious what was already there. Why not share all findings with you? I will keep this article updated – know this article does not cover which features are supported by each SDK.
The empty boxes tell IBM and ARM have a lot of influence. With NVIDIA’s current pace with introducing new products (hardware and CUDA), they could also take on ARM.
The matrix is restricted to current better-known compute technologies OpenCL, CUDA, Intel ArrBB, Pathscale ENZO, MS DirectCompute and AccelerEyes JacketLib.
X = All OSes, including MAC
D = Developer (private alpha or private beta)
P = Planned (as i.e. stated in Intel’s Q&A)
U = Unofficial (IBM’s OpenCL-SDK is promoted for their POWER-line)
L = Linux-only
W= Windows-only
? = Unknown if planned
Steve Streeting tweeted a few weeks ago: “Remember, experts are always wrong about disruptive tech, because it disrupts what they’re experts in.”. I’m happy I evangelise and work with such a disruptive technology and it will take time until it is bypassed by other technologies. And that other technologies will be probably be source-to-OpenCL-source compilers. At StreamHPC we therefore keep track of all these pre-compilers continuously.
Steve’s tweet got me triggered, since the stability-vs-progression-balance make changes quite hard (we see it all around us). Another reason was heard during the opening-speech of engineering world 2011 about “the cloud”, with a statement which went something like: “80% of today’s IT will be replaced by standardised cloud-solutions”. Most probably true; today any manager could and should click his/her “data from A to B”-report instead of buying a “oh, that’s very specialised and difficult” solution. But at the other side companies try to let their business live as long as possible. It’s therefore an intriguing balance.
So I came up with the idea to play my own devil’s advocate and try to disrupt GPGPU. I think it’s important to see what can disrupt the current parallel-kernel-execution model of OpenCL, CUDA and the others.
[Dutch] Op het Sogeti Engineering World 2011 heb ik een presentatie gehouden over OpenCL in de cloud, in het Nederlands. Om the coolheidsfactor te verhogen heb ik gebruik gemaakt van Prezi als contrast met de standaard dia-show-presentaties. Het resultaat treft u hier beneden, maar kan helaas onmogelijk het hele verhaal vertellen dat ik gedeeld heb tijdens de presentatie. Wilt u ergens iets meer van afweten, vraag gewoon of zet een comment onderaan dit artikel. Ik luister naar mijn lezers via Twitter.
De presentation bestaat uit 4 delen: een introductie, uitleg van OpenCL, Mobiele apparaten en and Data-centres. De laatste twee vormen cloud-computing.
[English] At the Sogeti Engineering World 2011 I presented about OpenCL in the cloud, in Dutch. To increase the relative cool-factor I made sure I had the only Prezi-presentation between the standard sheet-flip presentations. The result you can see below, but can impossibly tell all I shared at the presentation. If you want to know more, just ask or put an comment under this article. I listen to my readers via Twitter.
The presentation has four parts: an introduction, explanation of OpenCL, Mobile devices and data centres. The last two form a segment cloud-computing I want to focus on.
Continue reading “Engineering World 2011: OpenCL in the Cloud”
About 5 months ago we started waiting for Mobile OpenCL. Meanwhile we had all the news around ARM on CES in January, and of course all those beta-programs made progress meanwhile. And after a year of having “support“, we actually want to see the words “SDK” and/or “driver“. So who’s leading? Ziilabs, ImTech, Vivante, Qualcomm, FreeScale or newcomer nVIDIA?
Mobile phone manufacturers could have a big problem with the low-level access to the GPU. While most software can be sandboxed in some form, OpenCL can crash the phone. But at the other side, if the program hasn’t taken down the developer’s test-phone, the chances are low it will take any other phone. And also there are more low-level access-points to the phone. So let’s check what has happened until now.
Note: this article will be updated if more news comes from MWC ’11.
For mobile devices Khronos has specified a profile, which is optimised for (ARM) phones: OpenCL Embedded Profile. Read on for the main differences (taken from a presentation by Nokia).
February Benchmark Month. The idea is that you do at least one of the following benchmarks and put the results on the Khronos Forum. If you encounter any technical problems or you think the benchmark favours a certain brand, discuss it below this post. If I missed a benchmark, please put a comment under this post.
Since OpenCL works on all kinds of hardware, we can find out which is the fastest: Intel, AMD or NVIDIA.I don’t think all benchmarks are fit for IBM’s hardware, but I hope to see results of some IBM Cells too. If all goes well, I’ll show the first results of the fastest cards posted in April . Know that if the numbers are off too much, I might want to see further proof.
Happy benchmarking!
This discussion is about a role OpenCL could play in a diversifying processor-market.
Both AMD and Intel have added parallel instruction-sets for their CPUs to accelerate in media-operations. Each time a new instruction-set comes out, code needs to be recompiled to make use of it. But what about support for older processors, without penalties? Intel had some troubles with how to get support for their AVX-instructions, and choose for both their own Array Building Blocks and OpenCL. What I want to discuss here are the possibilities available to make these things easier. Also I want to focus on if a general solution “OpenCL for any future extensions” could hold. I make an assumption that most extensions target mostly parallelisation with media in mind, most notable embedded GPUs on upcoming hybrid processors. I talked about this subject before in “The rise of the GPGPU compiler“.
Java started in 1996 with the idea that end-point optimisation should be done by compiling intermediate code to the target-platform. The idea still holds and there are many possibilities to optimise intermediate code for SSE4/5, AVX, FMA, XOP, CLMUL and any other extension. Same is of course for dotNET.
Disadvantage is the device-models that are embedded in such compilers, which have not really take specialised instructions into account. So if I have a normal loop, I’m not sure it will work great on processors launched this year. C has pragmas for message-protocols, Java needs extensions. See Neal Gafter’s discussion about concurrent loops from 2006 for a nice discussion.
With for instance LLVM and Intel’s fast compilers, a lot can be done to get code optimised for all current processors. A real danger is that too many specialised processors will arrive the coming years; how to get maximum speed at all processors? We already have 32 and 64 bit; 128 bit is really not the only direction there is. Multi-target compilers can be something we should be getting used to, for which no standard is created for yet – only Apple has packed 32 and 64 bits together.
Years ago when CPUs started to have support for the multiply-add operation, a part of the compiled code had to be specially for this type of processor – giving a bigger binary. With any new type of extension, the binary gets bigger. It has to, else the potential of your processor will not be used and sales will drop in favour of cheaper chips. To sell software with support for each new extension, it takes time – in most cases reserved only for major releases.
Because not everybody has Gentoo (A Linux-distribution which compiles each piece of software targeting the user’s computer for maximum optimisation), it takes at least a year to get full use of the processor for most software.
So where does OpenCL fit in this picture? Virtual machines are optimised for threads and platform-targeting compilers are slow in distribution. Since drivers for CPUs are part of the OS-updating system, OpenCL-support in those drivers can get the new extensions utilised soon after market-introduction. The coming year more will be done for automatic optimisation for a broad range of processor-types – more about that later. This focus from the compiler to an OpenCL-library for handling optimal kernel-launching will get an optimum somewhere in between.
The coming time we will see OpenCL is indeed a more stable solution than for instance Intel’s Array Building Blocks, seen from the light of recompiling. If OpenCL can target all kinds of parallel extensions, it will offer the demanded flexibility the market demands in this diversifying processor-market. I used the word ‘demand’, because the consumer (being it an individual or company) who buys a new computer, wants his software to be faster, not potentially faster. What do you think?
Update 17-06-2011: updated version of opencl.lang and added opencl_host.lang.
When learning a language it is nice to do it the hard way, so you take the default txt-file editor provided with your OS. No colours, not help, no nothing, pure hard-core learning. But in Linux-desktop Gnome the default editor Gedit is quite powerful without doing too much, has an official Windows-port and has a OSX Darwin-port. It took just a few hours to understand how highlighting in Gedit works and to get it implemented. I got some nice help from the work done at the cuda-highlighter by Hüseyin Temucin (for showing how to extend the c-highlighter the best way) and the VIM OpenCL-highlighter by Terence Ou (for all the reserved words). This is work in progress; I will tell about updates via Twitter.
Windows-users first need to download Gedit for Windows. OSX-folks can check Darwin-ports. Then the files opencl.lang (.cl-files) and opencl_host.lang (extension of c to highlight OpenCL-keywords) needs to be put in /usr/share/gtksourceview-2.0/language-specs/ (or in ~/.local/share/gtksourceview-2.0/language-specs/ for local usage only), or for Window in C:Program Filesgeditsharegtksourceview-2.0language-specs or for OSX in /Applications/gedit.app/Contents/Resources/share/gtksourceview-2.0/language-specs/. Make sure all Gedit-windows are closed so the configuration will be re-read, and then open a .cl-file with Gedit. If you have opened cl-files as C or Cuda, you have to set the highlighting to OpenCL manually (under view -> highlighting). For host-code you always need to set the highlighting manually to “OpenCL host”. You might want to associate cl-files with Gedit.
VIM: http://www.vim.org/scripts/script.php?script_id=3157
Notepad++: http://sourceforge.net/tracker/?func=detail&aid=2957794&group_id=95717&atid=612384
SciTE: http://forums.nvidia.com/index.php?showtopic=106156
StreamHPC is working on Eclipse-support and I’ve understood also work is done for Netbeans-support. Let me know if there are more alternatives.
For a customer I’m writing a plugin for ImageJ, a toolkit for image-processing and analysis in Java. Rick Lentz has written an OpenCL-plugin using JOCL. In the tutorial step 1 is installing the great OS Ubuntu, but that would not be the fastest way to get it going, and since JOCL is multi-platform this step should be skippable. Furthermore I rewrote most of the code, so it is a little more convenient to use.
In this blog-post I’ll explain how to get it up and running within 10 minutes with the provided information.
The Wine 1.3 branch has support for OpenCL 1.0 since 1.3.9. Since Microsoft likes to get a little part of the Linux-dominated HPC-market, support for GPGPU is pretty good under the $799.00 costing Visual Studio – the free Express-version is not supported well. But why not take the produced software back via Wine? Problem is that OpenCL is not in the current Wine binaries for some reason, but that is fixable until we wait for inclusion…
Lazy or not much time? You can try my binaries (Ubuntu 32, NVIDIA), but I cannot guarantee they work for you and it is on your own responsibility: download (reported not working by some). See second part of step 3, what to do with it.
I assume you have the OpenCL-SDK installed, but let me know if I need to add more details or clear up some steps.
The sources are available here. Be sure you download at least version 1.3.9. Alternatively you download the latest from git. You can get it by going to a directory and execute:
git clone git://source.winehq.org/git/wine.git
A directory “wine” will be created. That was easy, so lets go to bake some binaries.
Developing with OpenCL is fun, if you like debugging. Having software with support for OpenCL is even more fun, because no debugging is needed. But what would be a good machine? Below is an overview of what kind of hardware you have to think about; it is not in-depth, but gives you enough information to make a decision in your local or online computer store.
Companies who want to build a cluster, contact us for information. Professional clusters need different hardware than described here.
So you want OpenCL-benchmarks? Phoronix is a benchmark for OSX and Linux, created by Michael Larabel, Matthew Tippett (http://en.wikipedia.org/wiki/Phoronix_Test_Suite). On Ubuntu Phoronix version 2.8 is in the Ubuntu “app store” (Synaptic), but 3.0 has those nice OpenCL-tests. The tests are based on David Bucciarelli‘s OpenCL demos. Starting to use Phonornix 3.0 (beta 1) is done in 4 easy steps:
WARNING: It is beta-software and the following might not work on your machine! If you have problems with this tutorial and want or found a fix, post a reply.
In 2010 Microsoft got interested in ARM, because of low-power solutions for server-parks. ARM tried to lobby for years to convince Microsoft to port Windows to their architecture and now the result is there. Let’s not look to the past, why they did not do it earlier and depended completely on Intel, AMD/ATI and NVIDIA. NB: This article is a personal opinion, to open up the conversation about Windows plus OpenCL.
While Google and Apple have taken their share on the ARM-OS market, Microsoft wants some too. A wise choice, but again late. We’ve seen how the Windows-PC market was targeted first from the cloud (run services in the browser on any platform) and Apple’s user-friendly eye-candy (A personal computer had to be distinguished from a dull working-machine), then from the smartphones and tablets (many users want e-mail and a browser, not sit behind their desk). MS’s responses were Azure (Cloud, Q1 2010), Windows 7 (OS with slick user-interface, Q3 2009), Windows Phone 7 (Smartphones, Q4 2010) and now Windows 8 (OS for X86 PCs and ARM tablets, 2012 or later).
Windows 8 for ARM will be made with assistance from NVIDIA, Qualcomm and Texas Instruments, according to their press-release [1]. They even demonstrated a beta of Windows 8 running Microsoft Office on ARM-hardware, so it is not just a promise.
How can Microsoft support this new platform and (for StreamHPC more important) what will the consequences be for OpenCL, CUDA and DirectCompute.
Intel has Sandy Bridge, AMD has Fusion, now NVIDIA has a combination of CPU and GPU too: Project Denver. The only difference is that it is not X86-based, but an ARM-architecture. And most-probable the most powerful ARM-GPU of 2011.
For years there were ARM-based Systems-on-a-chip: a CPU and a GPU combined (see list below). On the X86-platform the “integrated GPU” was on the motherboard, and since this year now both AMD/ATI and Intel hit this “new market”.The big advantage is that it’s cheaper to produce, is more powerful per Watt (in total) and has good acceleration-potential. NVIDIA does not have X86-chips and would have been the big loser of 2011; they did everything to reinvent themselves: 3D was reintroduced, CUDA was actively developed and pushed (free libraries and tools, university-programs, many books and trainings, Tesla, etc), a mobile Tegra graphics solution [1] (see image at the right), and all existing products got extra backing from the marketing-department. A great time for researchers who needed to get free products in exchange of naming NVIDIA in their research-reports.
NVIDIA chose for ARM; interesting for who is watching the CUDA-vs-OpenCL battle, since CUDA was for GPUs of NVIDIA on X86 and ARM was solely for OpenCL. Period. In the contrary to their other ARM-based chips, this new chip probably won’t be in smartphones (yet); it targets systems that need more GPU-power like CUDA and games.
In a few days the article about Windows-on-ARM is to be released, which completes this article.
About a year ago this site was launched and a half year ago StreamHPC as a company was official for the Chamber of Commerce. It has been a year of hard work, but the reason for this all started after seeing the cover of a book about bore-outs. The result is there with a growing number of visitors from all over the world (from 62 countries since 23-Dec-2010) and new twitter-followers every week. Now some mixed news for 2011:
In a few words: 2011 is going to be exciting! We wish all our readers, business-partners, friends, family and (new) customers a super-accelerated 2011!
StreamHPC – we accelerate your computations
In the world of GPGPU we have currently 4 players: Khronos OpenCL, NVIDIA CUDA, Microsoft DirectCompute and PathScal ENZO. You probably know CUDA and OpenCL already (or start reading more articles from this blog). ENZO is a 64bit-compiler which serves a small niche-market, and DirectCompute is built on top of CUDA/OpenCL or at least uses the same drivers.
Edit 2011-01-03: I was contacted by Pathscale about my conclusions about ENZO. The reason why not much is out there is that they’re still in closed alpha. Expect more to hear from them about ENZO somewhere in the coming 3 months.
A while ago there was an article introducing OpenCL by David Kanter who claimed on page 4 that DirectCompute will win from CUDA. I quote:
Judging by history though, OpenCL and DirectCompute will eventually come to dominate the landscape, just as OpenGL and DirectX became the standards for graphics.
I twittered that I totally disagreed with him and in this article I will explain why I think that.
