There is no price/performance data for ONTAP AI but we imagine millions of dollars are involved. AI at this level does not come cheap.
"If you have to ask how much, you can't afford it." :)
The clash of the million-dollar AI titans resumes. NetApp has designed an ONTAP AI architecture based on its topline A800 flash array and Nvidia DGX-1 to try to win fat-pocketed customers away from Pure and Nvidia's AIRI AI system-in-a-box. Fairy in the woods If you've got $1m+ to blow on AI, meet Pure, Nvidia's AIRI fairy: A …
Interview 2023 is shaping up to become a big year for Arm-based server chips, and a significant part of this drive will come from Nvidia, which appears steadfast in its belief in the future of Arm, even if it can't own the company.
Several system vendors are expected to push out servers next year that will use Nvidia's new Arm-based chips. These consist of the Grace Superchip, which combines two of Nvidia's Grace CPUs, and the Grace-Hopper Superchip, which brings together one Grace CPU with one Hopper GPU.
The vendors lining up servers include American companies like Dell Technologies, HPE and Supermicro, as well Lenovo in Hong Kong, Inspur in China, plus ASUS, Foxconn, Gigabyte, and Wiwynn in Taiwan are also on board. The servers will target application areas where high performance is key: AI training and inference, high-performance computing, digital twins, and cloud gaming and graphics.
Nvidia has chosen Intel's next-generation Xeon Scalable processor, known as Sapphire Rapids, to go inside its upcoming DGX H100 AI system to showcase its flagship H100 GPU.
Jensen Huang, co-founder and CEO of Nvidia, confirmed the CPU choice during a fireside chat Tuesday at the BofA Securities 2022 Global Technology Conference. Nvidia positions the DGX family as the premier vehicle for its datacenter GPUs, pre-loading the machines with its software and optimizing them to provide the fastest AI performance as individual systems or in large supercomputer clusters.
Huang's confirmation answers a question we and other observers have had about which next-generation x86 server CPU the new DGX system would use since it was announced in March.
Lenovo has unveiled a small desktop workstation in a new physical format that's smaller than previous compact designs, but which it claims still has the type of performance professional users require.
Available from the end of this month, the ThinkStation P360 Ultra comes in a chassis that is less than 4 liters in total volume, but packs in 12th Gen Intel Core processors – that's the latest Alder Lake generation with up to 16 cores, but not the Xeon chips that we would expect to see in a workstation – and an Nvidia RTX A5000 GPU.
Other specifications include up to 128GB of DDR5 memory, two PCIe 4.0 slots, up to 8TB of storage using plug-in M.2 cards, plus dual Ethernet and Thunderbolt 4 ports, and support for up to eight displays, the latter of which will please many professional users. Pricing is expected to start at $1,299 in the US.
Science fiction is littered with fantastic visions of computing. One of the more pervasive is the idea that one day computers will run on light. After all, what’s faster than the speed of light?
But it turns out Star Trek’s glowing circuit boards might be closer to reality than you think, Ayar Labs CTO Mark Wade tells The Register. While fiber optic communications have been around for half a century, we’ve only recently started applying the technology at the board level. Despite this, Wade expects, within the next decade, optical waveguides will begin supplanting the copper traces on PCBs as shipments of optical I/O products take off.
Driving this transition are a number of factors and emerging technologies that demand ever-higher bandwidths across longer distances without sacrificing on latency or power.
GPUs are a powerful tool for machine-learning workloads, though they’re not necessarily the right tool for every AI job, according to Michael Bronstein, Twitter’s head of graph learning research.
His team recently showed Graphcore’s AI hardware offered an “order of magnitude speedup when comparing a single IPU processor to an Nvidia A100 GPU,” in temporal graph network (TGN) models.
“The choice of hardware for implementing Graph ML models is a crucial, yet often overlooked problem,” reads a joint article penned by Bronstein with Emanuele Rossi, an ML researcher at Twitter, and Daniel Justus, a researcher at Graphcore.
Nvidia is expecting a $500 million hit to its global datacenter and consumer business in the second quarter due to COVID lockdowns in China and Russia's invasion of Ukraine. Despite those and other macroeconomic concerns, executives are still optimistic about future prospects.
"The full impact and duration of the war in Ukraine and COVID lockdowns in China is difficult to predict. However, the impact of our technology and our market opportunities remain unchanged," said Jensen Huang, Nvidia's CEO and co-founder, during the company's first-quarter earnings call.
Those two statements might sound a little contradictory, including to some investors, particularly following the stock selloff yesterday after concerns over Russia and China prompted Nvidia to issue lower-than-expected guidance for second-quarter revenue.
Nvidia will reveal more details about its Venado supercomputer project today at the International Supercomputing Conference in Hamburg, Germany.
Venado is hoped to be the first in a wave of high-performance computers that use an all-Nvidia architecture, in this case using Grace-Hopper Superchips that combine CPU and GPU dies, and Grace CPU-only Superchips.
This supercomputer "will be the first system deployed not just with Grace-Hopper in terms of the converged Superchip but it’ll also have a cluster of Grace CPU-only Superchip modules,” Dion Harris, Nvidia’s head of datacenter product marketing for HPC, AI, and Magnum IO, said during an Nvidia press conference ahead of ISC.
Analysis In a sign of how meteoric AMD's resurgence in high performance computing has become, the latest list of the world's 500 fastest publicly known supercomputers shows the chip designer has become a darling among organizations deploying x86-based HPC clusters.
The most eye-catching bit of AMD news among the supercomputing set is that the announcement of the Frontier supercomputer at the US Department of Energy's Oak Ridge National Laboratory, which displaced Japan's Arm-based Fugaku cluster for the No. 1 spot on the Top500 list of the world's most-powerful publicly known systems.
Top500 updates its list twice a year and published its most recent update on Monday.
European microprocessor designer SiPearl revealed deals with Nvidia and HPE today, saying they would up the development of high-performance compute (HPC) and exascale systems on the continent.
Announced to coincide with the ISC 2022 High Performance conference in Hamburg this week, the agreements see SiPearl working with two big dogs in the HPC market: HPE is the owner of supercomputing pioneer Cray and Nvidia is a leader in GPU acceleration.
With HPE, SiPearl said it is working to jointly develop a supercomputer platform that combines HPE's technology and SiPearl's upcoming Rhea processor. Rhea is an Arm-based chip with RISC-V controllers, planned to appear in next-generation exascale computers.
Computex Nvidia's Grace CPU and Hopper Superchips will make their first appearance early next year in systems that'll be based on reference servers unveiled at Computex 2022 this week.
It's hoped these Arm-compatible HGX-series designs will be used to build computer systems that power what Nvidia believes will be a "half trillion dollar" market of machine learning, digital-twin simulation, and cloud gaming applications.
"This transformation requires us to reimagine the datacenter at every level, from hardware to software from chips to infrastructure to systems," Paresh Kharya, senior director of product management and marketing at Nvidia, said during a press briefing.
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