GTC 2013: Jen-Hsun Huang Takes the Stage to Discuss NVIDIA's Future, New Hardware
Subject: General Tech, Graphics Cards | March 19, 2013 - 02:55 PM | Tim Verry
Tagged: unified virtual memory, ray tracing, nvidia, GTC 2013, grid vca, grid, graphics cards
Today, NVIDIA's CEO Jen-Hsun Huang stepped on stage to present the GTC keynote. In the presentation (which was live streamed on the GTC website and archived here.), NVIDIA discussed five major points, looking back over 2013 and into the future of its mobile and professional products. In addition to the product roadmap, NVIDIA discussed the state of computer graphics and GPGPU software. Remote graphics and GPU virtualization was also on tap. Finally, towards the end of the Keynote, the company revealed its first appliance with the NVIDIA GRID VCA. The culmination of NVIDIA's GRID and GPU virtualization technology, the VCA is a device that hosts up to 16 virtual machines which each can tap into one of 16 Kepler-based graphics processors (8 cards, 16 GPUs per card) to fully hardware accelerate software running of the VCA. Three new mobile Tegra parts and two new desktop graphics processors were also hinted at, with improvements to power efficiency and performance.
On the desktop side of things, NVIDIA's roadmap included two new GPUs. Following Kepler, NVIDIA will introduce Maxwell and Volta. Maxwell will feature a new virtualized memory technology called Unified Virtual Memory. This tech will allow both the CPU and GPU to read from a single (virtual) memory store. Much as with the promise of AMD's Kaveri APU, the Unified Virtual Meory will result in speed improvements in heterogeneous applications because data will not have to be copied to/from the GPU and CPU in order for the data to be processed. Server applications will really benefit from the shared memory tech. NVIDIA did not provide details, but from the sound of it, the CPU and GPU both continue to write to their own physical memory, but their is a layer of virtualized memory on top of that, that will allow the two (or more) different processors to read from each other's memory store.
Following Maxwell, Volta will be a physically smaller chip with more transistors (likely a smaller process node). In addition to the power efficiency improvements over Maxwell, it steps up the memory bandwidth significantly. NVIDIA will use TSV (through silicon via) technology to physically mount the graphics DRAM chips over the GPU (attached to the same silicon substrate electrically). According to NVIDIA, this new TSV-mounted memory will achieve up to 1 Terabytes/second of memory bandwidth, which is a notable increase over existing GPUs.
NVIDIA continues to pursue the mobile market with its line of Tegra chips that pair an ARM CPU, NVIDIA GPU, and SDR modem. Two new mobile chips called Logan and Parker will follow Tegra 4. Both new chips will support the full CUDA 5 stack and OpenGL 4.3 out of the box. Logan will feature a Kepler-based graphics porcessor on the chip that can “everything a modern computer ought to do” according to NVIDIA. Parker will have a yet-to-be-revealed graphics processor (Kepler successor). This mobile chip will utilize 3D FinFET transistors. It will have a greater number of transistors in a smaller package than previous Tegra parts (it will be about the size of a dime), and NVIDIA also plans to ramp up the frequency to wrangle more performance out of the mobile chip. NVIDIA has stated that Logan silicon should be completed towards the end of 2013, with the mobile chips entering production in 2014.
Interestingly, Logan has a sister chip that NVIDIA is calling Kayla. This mobile chip is capable of running ray tracing applications and features OpenGL geometric shaders. It can support GPGPU code and will be compatible with Linux.
NVIDIA has been pushing CUDA for several years, now. The company has seen some respectable adoption rates, by growing from 1 Tesla supercomputer in 2008 to its graphics cards being used in 50 supercomputers, with 500 million CUDA processors on the market. There are now allegedly 640 universities working with CUDA and 37,000 academic papers on CUDA.
Finally, NVIDIA's hinted-at new product announcement was the NVIDIA VCA, which is a GPU virtualization appliance that hooks into the network and can deliver up to 16 virtual machines running independant applications. These GPU accelerated workspaces can be presneted to thin clinets over the netowrk by installing the GRID client software on users' workstations. The specifications of the GRID VCA is rather impressive, as well.
The GRID VCA features:
- 2 x Intel Xeon processors with 16 threads each (32 total threads)
- 192GB to 384GB of system memory
- 8 Kepler-based graphics cards, with two GPUs each (16 total GPUs)
- 16 x GPU-accelerated virtual machines
The GRID VCA fits into a 4U case. It can deliver remote graphics to workstations, and is allegedly fast enough to deliver gpu accelerated software that is equivalent to having it run on the local machine (at least over LAN). The GRID Visual Computing Appliance will come in two flavors at different price points. The first will have 8 Kepler GPUs with 4GB of memory each, 16 CPU threads, and 192GB of system memory for $24,900. The other version will cost $34,900 and features 16 Kepler GPUs (4GB memory), 32 CPU threads, and 384GB system memory. On top of the hardware cost, NVIDIA is also charging licensing fees. While both GRID VCA devices can support unlimited devices, the licenses cost $2,400 and $4,800 per year respectively.
Overall, it was an interesting keynote, and the proposed graphics cards look to be offering up some unique and necessary features that should help hasten the day of ubiquitous general purpose GPU computing. The Unified Virtual Memory was something I was not expecting, and it will be interesting to see how AMD responds. AMD is already promising shared memory in its Kaveri APU, but I am interested to see the details of how NVIDIA and AMD will accomplish shared memory with dedicated grapahics cards (and whether CrossFire/SLI setups will all have a single shared memory pool)..
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