Nvidia welds together ARM-Kepler ceepie-geepie system for the impatient

The Kayla machine is not just interesting in its own right as a software development platform, but perhaps for experimental clusters that set the stage for future machines based on future Tegra processors with beefier ARM cores and beefier GPUs on the same piece of silicon.

Kayla definitely sets the stage for the future "Logan" Tegra 5 processors, due next year perhaps. The Logan chips will marry a Tegra ARM processor complex with a Kepler GPU, while the "Parker" Tegra 6 chip will sport a custom 64-bit ARMv8 processor and a "Maxwell" GPU all on the same chip.

The Kayla board is a kicker the the Karma board launched at the SC11 supercomputing conference in 2011. And obviously it could also be used to build a prototype ARM-GPU supercomputer, as the Barcelona Supercomputing Center in Spain has been doing for a few years now using a mix of different ARM processors.

Jen-Hsun Huang, co-founder and CEO at Nvidia, showed the Kayla board running real-time ray tracing on a set of wine glasses. "The entire modern software stack we know of - CUDA 5 with OpenGL 4.3 geometry shaders, with physics, running Linux - all on the same platform."

Huang added that Nvidia will be able to take what now is a pretty hefty baby system embodied in the Kayla hybrid system and shrink it down to the size of a dime with the Logan CPU-GPU chip. That will be very interesting indeed, particularly if the Tegra 5 has 40-bit memory addressing and a reasonable number of ARM cores and a Kepler GPU with a whole lot of CUDA cores.

But back to the Kayla ceepie-geepie system. You would think that Nvidia would be using the latest Tegra 4 chip in this board, but it is in fact based on a Tegra 3 processor card, just like the predecessor Karma system made by Seco. The other details of the system were not divulged.

But we can do a little guessing about Kayla based on Karma. With the Karma board, the Tegra 3 ran at 1.5GHz and delivering around 6 gigaflops of number-crunching power; it had 4GB of main memory on the board and a Gigabit Ethernet port.

The Karma system plugged in a GeForce GT520MX mobile GPU coprocessor, which had 48 cores (only 9 percent of the total cores actually on the chip activated) spinning at 900MHz (instead of 1.3GHz); that GPU delivered around 142 gigaflops of floating point oomph.

It stands to reason that Nvidia will once again use a GeForce mobile discrete GPU adapter for the Kayla system, but for now the company is not saying which one it is plugging in.

The Karma system had a rumored street price of $500, and that sounds like the right price point two years later for the Kayla system. The Kayla hybrid machine will ship sometime in the spring. ®

Now to Fudzilla and some details:

Nvidia details Kayla, dev platform for CUDA on ARM

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To get developers ready for Logan

In addition to GPU and Tegra roadmap updates Nvidia also showed and detailed its newest Kayla developer platform for CUDA on ARM, which should get developers ready for Logan SoCs scheduled for next year.

Built on a mini-ITX-like motherboard, the Kayla developement platform is based on a Tegra 3 CPU and connected via PCI-Express to a yet to be detailed dedicated GPU based on the Kepler design. The GPU has 2 SMXs for a total of 384 CUDA cores, according to a post over at PCGameshardware. The developer platform is solely made in order to give developers something to work with in case they want to see how well CUDA works on ARM, since Logan, with a Kepler-based GPU, will be the first CUDA-capable ARM SoC.

nvidia kayla 1

The Tegra 3 CPU part, paired up with 2GB of RAM, was most likely picked due to its PCI-Exprsss bus capability and should not reflect the actual performance of the Logan SoC, both performance and power consumption wise, considering the fact that the current Kalya board sucks around 10W. The "unnamed" GPU, paired up with 1GB of its own RAM, will be available in both MXM and PCI-Express form depedning on developers choice. It will bring all those neat CUDA features including OpenGL 4.3 features like tesselation, geometry shaders and compute shaders, all to be available on Logan as well since it is also based on the Kepler GPU.

The Kayla developer platform is certainly different from what we will see with Logan, at least on the specification and performance level, but should offer similar feature list, at least when CUDA is concerned.

nvidia tegraroadmap 1

Nvidia did not shed any light on specific details of Kayla, as it keeps all the juicy details for developers interested in it. It should be available in next few months and it would be quite interesting to see what some developers can do with it as it will certainly be a good indication on what to expect in Logan parts.

Thanks to the fact that Nvidia is currently quite keen on giving superhero names to its Tegra related products and Jen-Hsun note that Kayla is "Logan's girlfried" it was just a matter of time before it can be pin-pointed to Kayla Silverfox that appeared in X-Men Origins: Wolverine and the original X-Men Animated Series.

Last modified on Wednesday, 20 March 2013 16:17

Another little board for hobbyists and developers...video:

Video: A Closer Look at the Kayla ARM-based Development Platform for CUDA and OpenGL

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In this video from the GPU Technology Conference, Ian Buck from Nvidia describes the new Kayla development platform for ARM-based CUDA and OpenGL.

“Introducing the Kayla Platform for computing on the ARM architecture – where supercomputing meets mobile computing. The Kayla platform is powered by an NVIDIA Tegra Quad-core ARM processor and a Kepler GPU to deliver the highest performance, highest efficiency for the next generation of CUDA and OpenGL application. Pre-installed with CUDA 5 and supporting OpenGL 4.3, it provides ARM applications development across the widest range of application types. The Kayla platform will be available Spring 2013.”

Read the Full Story.

heh heh heh

THIS is what I mean ... :

What the HECK is being SAID here?

"The Karma system plugged in a GeForce GT520MX mobile GPU coprocessor, which had 48 cores (only 9 percent of the total cores actually on the chip activated) spinning at 900MHz (instead of 1.3GHz); that GPU delivered around 142 gigaflops of floating point oomph."

gigaflops of floating point oomph?

from Wash DC, right ?

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Development board for CPU-GPU hybrid apps, or nodes in a parallel cluster perhaps