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NVidia has published the agenda for the upcoming GPU Technology Conference online, and it looks like an amazing collection of talks.  Many people today claim GPU’s are unnecessary for compute because the CPU can match it in speed, but leave out the part about new and future algorithms that could easily put the power back in the GPU court.  Looks like NVidia has gone out of their way to collect speakers to drive this point home.  Look at some of the briefs.  CFD Simulations:

Shockingly Fast and Accurate CFD Simulations (#2078) – Timothy Warburton, Rice University

In the last three years we have demonstrated how GPU accelerated discontinuous Galerkin methods have enabled simulation of time-dependent, electromagnetic scattering from airplanes and helicopters. In this talk we will discuss how we have extended these techniques to enable GPU accelerated simulation of supersonic airflow as well.

Biomedical Imaging:

Nearly Instantaneous Reconstruction for MRIs (#2094) – General Electric

GE’s Autocalibrating Reconstruction for Cartesian Imaging (ARC) is a computationally intensive, widely used algorithm in MRI Reconstruction using Parallel Imaging. We demonstrate that an optimized CUDA implementation of ARC on a GPU can enable nearly instantaneous reconstruction and speedups of up to 10x over an optimized dual socket QuadCore CPU implementation. We will discuss challenges both with computational intensity and data read/write efficiency. We will also compare the Fermi C2050 with the C1060.

The Large Hadron Collider:

Processing Petabytes per Second at the Large Hadron Collider at CERN (#2135) – Philip Clark, University of Edinburgh; Andy Washbrook, University of Edinburgh

Learn how GPUs could be adopted by the ATLAS detector at the Large Hadron Collider (LHC) at CERN. The detector, located at one of the collision points, must trigger on unprecedented data acquisition rates (PB/s), to decide whether to record the event, or lose it forever. In the beginning we introduce the ATLAS experiment and the computational challenges it faces. The second part will focus on how GPUs can be used for algorithm acceleration – using two critical algorithms as exemplars. Finally, we will outline how GPGPU acceleration could be exploited and incorporated into the future ATLAS computing framework.

Entertainment (You didn’t think I’ld leave you out, did you?):

Developing GPU Enabled Visual Effects For Film And Video (#2125) – Bruno Nicoletti, The Foundry; Jack Greasley, The Foundry

The arrival of fully programmable GPUs is now changing the visual effects industry, which traditionally relied on CPU computation to create their spectacular imagery. Implementing the complex image processing algorithms used by VFX is a challenge, but the payoffs in terms of interactivity and throughput can be enormous. Hear how The Foundry’s novel image processing architecture simplifies the implementation of GPU-enabled VFX software and eases the transition from a CPU based infrastructure to a GPU based one.

Rendering Revolution (#2165) – Ken Pimentel, Autodesk

Learn how GPU technologies are transforming the making of pixels. This talk will cover GPU-centric rendering techniques that leverage both the raw computational capabilities of NVIDIA’s GPUs and advanced pixel-shading techniques for interactive visualization and rendering.

Looks like a great event this year, be sure to check out the entire agenda by day or by session.  What else do you see that looks interesting? Post in the comments!

Science conference, gpgpu, gtc, nvidia

NVidia has published most of the recordings from the recent GPU Technology Conference on their website.  Head on over there to download the posters, watch the keynotes, or see the recordings of any of the sessions.

GPU Technology Conference.

Hardware, Science conference, gtc, nvidia

At the recent GPU Technology Conference in San Jose, NVidia’s Principal System Software Engineer Mark Kilgard spoke about what you can expect to see in the upcoming OpenGL3.2 and some of the other things NVidia has in development, such as:

• BGRA Vertex Component Ordering
• OpenGLSL 1.50
• Improved interoperability between Direct3D & OpenGL
• Geometry Shaders
• Depth Clamping (a better solution to clipping planes)
• Seamless Cube Maps
• Synchronization support

And much much more.. The 84-slide presentation is available on SlideShare, and I’ve embedded it after the break for you to see.

Read more…

Hardware, Science gtc, nvidia, opengl

In response to the big news about the breakdown of NVidia’s Fermi presentation at GTC, Nvidia has issued a format response confirming what I suspected:  Fermi is real, and was running at GTC, but it’s still very much an “engineering prototype”:

Nvidia confirms Fermi that was running PhysX at Jensen’s GTC keynote was real but the one that we all took pictures of was a mock-up.

The real engineering sample card is full of dangling wires. Basically, it looks like an octopus of modules and wires and the top brass at Nvidia didn’t want to give that thing to Jensen. This was confirmed today by a top Nvidia VP president class chap, but the same person did confirm that the card is real and that it does exist.

via Fudzilla.

Hardware fermi, gt300, gtc, nvidia

Be sure to read the followup to this, including comments from NVidia.

NVidia showed the GT300 (Fermi) board up on stage during the keynote of the GTC this week, but was it a real Fermi board? Or merely a prop?  They were pretty positive about release and production schedules, but SemiAccurate takes a close-up look at the photos and PR material Nvidia gave out and paints a less rosy picture of the situation.

Some things to note on it. First is that the second set of digits on the first line says 0935A1. A1 is for first silicon, something that, when coupled with a direct quote from Jen-Hsun of, “You are currently looking at a few day old silicon” (from here select the video “See video of Jen-Hsun Huang announcing Fermi”) kind of blows the whole ‘silicon in Santa Clara last spring’ story out of the water. I wonder if anyone will retract that, or just change the article retroactively?

To make matters worse, the other digits are a date code, 0935 means 2009, work week 35. If Nvidia starts its work week on the first full week of the year like everyone else, that would put WW35 at August 28 to September 5, 2009. Where have I heard that date before? Oh yeah, here. (edit: Referring to the 2% Yield number rumors).

While it’s no surprise that the boards were engineering prototypes (in reference to the author’s shock of finding common wood-screws holding it together), it is a bit disturbing if his analysis of the chip production numbers is correct.  He also gets into amazing depth on some of the odd solder design and PCB layout issues, like this:

The 6-pin connector, on the other hand, lines up with, umm, nothing. There is a potential 4-pin floppy/sound/jumper block below it, but you can clearly see there is nothing in the vias, not even solder. The 6-pin connector connects to nothing, and nothing is holding it in. Except glue. Notice the connector is black and the hole below it shows white. The only real question now is, Elmers or glue stick?

To make matters worse, the mounting holes for the 8-pin connector, which should be between the 6-pin and 8-pin fakes if the card was real, are empty. Piss-poor fake job guys. Go read your fanboi forums, they do a better job, and work for much cheaper than your ‘geniuses’.

Unlike the original author, I do believe that Fermi was alive and well at the conference, but he does raise some interesting questions.  Perhaps that was a “defective board” held up to show, or a very early engineering prototype (as all the functioning boards were in-use).  Perhaps that was Huang’s personal “lucky presentation board” that he likes to use, but has long-since been obsoleted.  Who knows.

Thoughts?

via SemiAccurate :: Nvidia fakes Fermi boards at GPU Technology Conference.

Hardware conference, fermi, gt300, gtc, nvidia

Nvidia has posted videos from the GTC all week long covering big stories, product demos, and a great wrapup at the end of each day.  If you weren’t able to attend then these will serve double duty to keep you informed and make you feel guilty enough to attend next year :)

See some of the videos after the break, and check out the full NVidia Youtube channel for more.

Read more…

Graphics, Hardware, Science conference, gtc, nvidia

The previously mentioned “Nexus” toolsuite for GPU/CPU Debugging inside of Visual Studio was formally announced today at the NVidia GTC to the attendees.  Some new details:

NVIDIA Nexus radically improves productivity by enabling developers of GPU computing applications to use the popular Microsoft Visual Studio-based tools and workflow in a transparent manner, without having to create a separate version of the application that incorporates diagnostic software calls. NVIDIA Nexus also includes the ability to run the code remotely on a different computer. Nexus includes advanced tools for simultaneously analyzing efficiency, performance, and speed of both the graphics processing unit (GPU) and central processing unit (CPU) to give developers immediate insight into how co-processing affects their applications.

The Nexus suite comes with 3 components:

• Nexus Debugger – source code debugger for GPU source code
• Nexus Analyzer – System-wide event viewer for both GPU & CPU events
• Nexus Graphics Inspector – for deep inspection of textures and geometry

Read the full announcement after the break.

Read more…

Hardware gpgpu, gtc, nexus, nvidia, visual studio

It seems the GT300 news was actually under embargo until the GTC keynote was finished (guess BSN decided to ignore it, oh well), and now that it’s over the information is pouring out.  One great resource is an article from John West over at InsideHPC touting the new HPC-centric features of the design.

The new design features a dedicated 64KB L1 cache per Streaming Multiprocessor (GPU cores are organized hierarchically into “Streaming Multiprocessors,” or SMs; 32 cores form an SM, and there are 16 SMs on a board), and a 768KB L2 cache shared among all SMs. NVIDIA calls this the “Parallel DataCache Hierarchy,” and Sumit Gupta, senior manager in the Tesla GPU Computing group, says that this feature is very important not only to sparse matrix and physics calculations (for gaming), but also for traditional graphics applications like ray tracing. Application engineers should now see a much more familiar programming environment when porting code from CPUs.

via NVIDIA’s next generation GPU architecture has a lot for HPC to love | insideHPC.com.

Hardware gpgpu, gt300, gtc, hpc, nvidia

That’s right, today is the first day of NVidia’s GPU Technology Conference.  Unfortunately VizWorld wasn’t able to attend, but we’ll be doing our best to collect information from around the internet and present it here for you to view!  First step of that is that the VizWorld sidebar now contains a life twitter-stream of events at the conference (tagged #gputechconf).  Keep checking back regularly for more information, we’ll publish as we get it!

Oh, and if you’re lucky enough to be at GTC then definately contact us!  We’ld love to hear from you about anything you find interesting!  Send us pics or text to tips@vizworld.com and we’ll happily post it and give you full credit (send a web link and we’ll even link to your own site!)

If you couldn’t make it, then make sure to take in some of the Live-streams they’ll be publishing.  Guaranteed to be some great information coming out there.

Graphics, Hardware, Science, Website conference, gtc, nvidia

The NVidia GPU Technology Conference starts tomorrow in San Jose, CA.  If you’re one of the unfortunate people tethered to your desk and unavailable to attend the conference, then this post is for you!

NVidia will be live-streaming some of the talks via their website:

• Wed. Sept 30 – 1:00 PM to 2:30 PM: Opening Keynote with Jen-Hsun Huang, CEO and Co-Founder, NVIDIA
• Wed. Sept 30 – 3:00 PM to 4:15 PM: General Session on Important Trends in Visual Computing
• Wed. Sept 30 – 4:30 PM to 5:45 PM: General Session on Breakthroughs in High Performance Computing
• Thurs. Oct 1 – 9:00 AM to 10:30 AM: Day 2 Keynote with Hanspeter Pfister, Professor and Computing Visionary, Harvard University
• Fri. Oct 2 – 8:30 AM to 10:00 AM: Day 3 Keynote with Richard Kerris, CTO, Lucasfilm

Sounds like a good thing to fire up at your desk and stay informed about the cutting-edge of GPU technology.

Hardware, Science conference, gtc, nvidia