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nVidia Releases CUDA
Nvidia has released CUDA – its code that lets developers run their code on GPUs – to server vendors in order to get 64-bit ARM cores into the high performance computing (HPC) market.
The firm said today that ARM64 server processors, which are designed for microservers and web servers because of their energy efficiency, can now process HPC workloads when paired with GPU accelerators using the Nvidia CUDA 6.5 parallel programming framework, which supports 64-bit ARM processors.
“Nvidia’s GPUs provide ARM64 server vendors with the muscle to tackle HPC workloads, enabling them to build high-performance systems that maximise the ARM architecture’s power efficiency and system configurability,” the firm said.
The first GPU-accelerated ARM64 software development servers will be available in July from Cirrascale and E4 Computer Engineering, with production systems expected to ship later this year. The Eurotech Group also plans to ship production systems later this year.
Cirrascale’s system will be the RM1905D, a high density two-in-one 1U server with two Tesla K20 GPU accelerators, which the firm claims provides high performance and low total cost of ownership for private cloud, public cloud, HPC and enterprise applications.
E4′s EK003 is a production-ready, low-power 3U dual-motherboard server appliance with two Tesla K20 GPU accelerators designed for seismic, signal and image processing, video analytics, track analysis, web applications and Mapreduce processing.
Eurotech’s system is an “ultra-high density”, energy efficient and modular Aurora HPC server configuration, based on proprietary Brick Technology and featuring direct hot liquid cooling.
Featuring Applied Micro X-Gene ARM64 CPUs and Nvidia Tesla K20 GPU accelerators, the new ARM64 servers will provide customers with an expanded range of efficient, high-performance computing options to drive compute-intensive HPC and enterprise data centre workloads, Nvidia said.
Nvidia added, “Users will immediately be able to take advantage of hundreds of existing CUDA-accelerated scientific and engineering HPC applications by simply recompiling them to ARM64 systems.”
ARM said that it is working with Nvidia to “explore how we can unite GPU acceleration with novel technologies” and drive “new levels of scientific discovery and innovation”.
nVidia Outs CUDA 6
Nvidia has made the latest GPU programming language CUDA 6 Release Candidate available for developers to download for free.
The release arrives with several new features and improvements to make parallel programming “better, faster and easier” for developers creating next generation scientific, engineering, enterprise and other applications.
Nvidia has aggressively promoted its CUDA programming language as a way for developers to exploit the floating point performance of its GPUs. Available now, the CUDA 6 Release Candidate brings a major new update in unified memory access, which lets CUDA applications access CPU and GPU memory without the need to manually copy data from one to the other.
“This is a major time saver that simplifies the programming process, and makes it easier for programmers to add GPU acceleration in a wider range of applications,” Nvidia said in a blog post on Thursday.
There’s also the addition of “drop-in libraries”, which Nvidia said will accelerate applications by up to eight times.
“The new drop-in libraries can automatically accelerate your BLAS and FFTW calculations by simply replacing the existing CPU-only BLAS or FFTW library with the new, GPU-accelerated equivalent,” the chip designer added.
Multi-GPU Scaling has also been added to the CUDA 6 programming language, introducing re-designed BLAS and FFT GPU libraries that automatically scale performance across up to eight GPUs in a single node. Nvidia said this provides over nine teraflops of double-precision performance per node, supporting larger workloads of up to 512GB in size, more than it’s supported before.
“In addition to the new features, the CUDA 6 platform offers a full suite of programming tools, GPU-accelerated math libraries, documentation and programming guides,” Nvidia said.
The previous CUDA 5.5 Release Candidate was issued last June, and added support for ARM based processors.
Aside from ARM support, Nvidia also improved Hyper-Q support in CUDA 5.5, which allowed developers to use MPI workload prioritisation. The firm also touted improved performance analysis and improved performance for cross-compilation on x86 processors.
nVidia Launching New Cards
We weren’t expecting this and it is just a rumour, but reports are emerging that Nvidia is readying two new cards for the winter season. AMD of course is launching new cards four weeks from now, so it is possible that Nvidia would try to counter it.
The big question is with what?
VideoCardz claims one of the cards is an Ultra, possibly the GTX Titan Ultra, while the second one is a dual-GPU job, the Geforce GTX 790. The Ultra is supposedly GK110 based, but it has 2880 unlocked CUDA cores, which is a bit more than the 2688 on the Titan.
The GTX 790 is said to feature two GK110 GPUs, but Nvidia will probably have to clip their wings to get a reasonable TDP.
We’re not entirely sure this is legit. It is plausible, but that doesn’t make it true. It would be good for Nvidia’s image, especially if the revamped GK110 products manage to steal the performance crown from AMD’s new Radeons. However, with such specs, they would end up quite pricey and Nvidia wouldn’t sell that many of them – most enthusiasts would probably be better off waiting for Maxwell.
nVidia’s CUDA 5.5 Available
Nvidia has made its CUDA 5.5 release candidate supporting ARM based processors available for download.
Nvidia has been aggressively pushing its CUDA programming language as a way for developers to exploit the floating point performance of its GPUs. Now the firm has announced the availability of a CUDA 5.5 release candidate, the first version of the language that supports ARM based processors.
Aside from ARM support, Nvidia has improved supported Hyper-Q support and now allows developers to have MPI workload prioritisation. The firm also touted improved performance analysis and improved performance for cross-compilation on x86 processors.
Ian Buck, GM of GPU Computing Software at Nvidia said, “Since developers started using CUDA in 2006, successive generations of better, exponentially faster CUDA GPUs have dramatically boosted the performance of applications on x86-based systems. With support for ARM, the new CUDA release gives developers tremendous flexibility to quickly and easily add GPU acceleration to applications on the broadest range of next-generation HPC platforms.”
Nvidia’s support for ARM processors in CUDA 5.5 is an indication that it will release CUDA enabled Tegra processors in the near future. However outside of the firm’s own Tegra processors, CUDA support is largely useless, as almost all other chip designers have chosen OpenCL as the programming language for their GPUs.
Nvidia did not say when it will release CUDA 5.5, but in the meantime the firm’s release candidate supports Windows, Mac OS X and just about every major Linux distribution.
Are CUDA Applications Limited?
Acceleware said at Nvidia’s GPU Technology Conference (GTC) today that most algorithms that run on GPGPUs are bound by GPU memory size.
Acceleware is partly funded by Nvidia to provide developer training for CUDA to help sell the language to those that are used to traditional C and C++ programming. The firm said that most CUDA algorithms are now limited by GPU local memory size rather than GPU computational performance.
Both AMD and Nvidia provide general purpose GPU (GPGPU) accelerator parts that provide significantly faster computational processing than traditional CPUs, however they have only between 6GB and 8GB of local memory that constrains the size of the dataset the GPU can process. While developers can push more data from system main memory, the latency cost negates the raw performance benefit of the GPU.
Kelly Goss, training program manager at Acceleware, said that “most algorithms are memory bound rather than GPU bound” and “maximising memory usage is key” to optimising GPGPU performance.
She further said that developers need to understand and take advantage of the memory hierarchy of Nvidia’s Kepler GPU and look at ways of reducing the number of memory accesses for every line of GPU computing.
The point Goss was making is that GPU computing is relatively cheap in terms of clock cycles relative to the time it takes to fetch data from local memory, let alone loading GPU memory from system main memory.
Goss, talking to a room full of developers, proceeded to outline some of the performance characteristics of the memory hierarchy in Nvidia’s Kepler GPU architecture, showing the level of detail that CUDA programmers need to pay attention to if they want to extract the full performance potential from Nvidia’s GPGPU computing architecture.
Given Goss’s observation that algorithms running on Nvidia’s GPGPUs are often constrained by local memory size rather than by the GPU itself, the firm might want to look at simplifying the tiers of memory involved and increasing the amount of GPU local memory so that CUDA software developers can process larger datasets.
nVidia Soars
Nvidia has published its third quarter earnings and the results are impressive to say the least. With record revenue of $1.2 billion, Nvidia’s net income in Q3 was $209.1 million (GAAP).
Quarterly revenue is up 12.9 percent year-over-year and represents a 15.3 percent sequential bump, beating analyst expectations. However, Nvidia expects its revenue to dip to between $1.02 and $1.17 billion in the fourth quarter.
The company blames the projected slump on a declining PC market. It seems Nvidia does not expect Windows 8 will have a very positive impact on the PC market.
Cars May Come With nVidia’s Tegra
January 23, 2012 by admin
Filed under Around The Net
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One of the things that we keep hearing as a big business opportunity for ARM manufacturers is to get their chips in cars. We heard this before, but this time we are not talking about navigation / entertainment systems.
The idea behind the concept is that more and more cars will come with collision detection mechanisms, road tracking that can keep your car stay in the high way lane. It gets better, the car can now lock on the car in front of you and accelerate and decelerate with it, so called adaptive cruise control with some manufacturers.
Fancier cars today come with elaborate stability assistance systems and many other features that might put such processors to good use, for something far more useful than just navigation and playing music.
Most Tegra 2 Tablets Will Get ICS
Sources have confirmed that most Tegra 2 tablets you know will get Ice Cream Sandwich. We are still sniffing around to find out if the ICS is going to end up as Android 4.0 but it will bring phones and tablets much closer and should ship in October or November.
Many Asus, Samsung, Toshiba, Lenovo, Sony and any other Android 3.x compatible tablets on market will have a chance to get the new one. The upgrade will come as manufacturers get it ready and customized for its tablets but most tablets will ship with Android 4.0, Ice Cream Sandwich, probably early next year at the latest.
This is good news for many who were brave to buy the first generation of tablets not based on Apple’s architecture and it will help Google to gather even more momentum for 2012. 2012 looks like a year when Google will be ready for real war against Apple, but at the same time, Android supporters fear that Windows 8 will get a lot of attention when it ships in late 2012.
nVidia’s Tegra 3 Coming To Smartphones
July 18, 2011 by admin
Filed under Smartphones
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It appears as though Nvidia’s next generation quad-core Kal-El (Tegra 3) quad core SoC will also show up on smartphones too. Originally, it was believed that the SoC would only support the ever growing tablet space.
Inside sources have confirmed that projects are already underway and that Tegra 3 aka Kal-El smartphones will be make a debut as well.
Nvidia had hoped to get a lot of play out of Tegra 2, unfortunately the chip was not as embraced as Nvidia had wanted. Even though the Tegra 2 SoC did manage to get a few design wins.
Acer Launches Sandy Bridge Notebooks
Acer updated its Timeline notebook series with Intel’s Sandy Bridge family of CPUs. The Timeline X series will come in three sizes, 13.3-inch, 14-inch and 15.6-inch and they are about an inch thick. Furthermore, the notebooks will be equipped with Acer’s PowerSmart Technology that is supposed to provide battery life of up to nine hours on models with integrated graphics and up to eight hours for those models with discrete graphics.