Showing posts with label GPU. Show all posts
Showing posts with label GPU. Show all posts

Monday, November 6, 2017

Intel partners with AMD on Embedded Multi-Die Interconnect Bridge for GPUs

Intel announced a partnership with AMD to tie together its high-performance processors with discrete graphics processors using the Intel Embedded Multi-Die Interconnect Bridge (EMIB) technology along with a new power-sharing framework.
The goal is to reduce the usual silicon footprint to less than half that of standard discrete components on a motherboard.

The first implementation matches the new 8th Gen Intel Core Core H-series processor, second generation High Bandwidth Memory (HBM2) and a custom-to-Intel third-party discrete graphics chip from AMD’s Radeon Technologies Group – all in a single processor package.

“Our collaboration with Intel expands the installed base for AMD Radeon GPUs and brings to market a differentiated solution for high-performance graphics,” said Scott Herkelman, vice president and general manager, AMD Radeon Technologies Group. “Together we are offering gamers and content creators the opportunity to have a thinner-and-lighter PC capable of delivering discrete performance-tier graphics experiences in AAA games and content creation applications. This new semi-custom GPU puts the performance and capabilities of Radeon graphics into the hands of an expanded set of enthusiasts who want the best visual experience possible.”

Wednesday, September 27, 2017

NVIDIA secures server design wins with leading manufacturers

NVIDIA has secured design wins for its Volta architecture-based Tesla V100 GPU accelerators with the leading server manufacturers, including Dell EMC, Hewlett Packard Enterprise, IBM, Supermicro, Inspur, Lenovo and Huawei.

Each NVIDIA V100 GPU features over 21 billion transistors, as well as 640 Tensor Cores, the latest NVLink high-speed interconnect technology, and 900 GB/sec HBM2 DRAM to achieve 50 percent more memory bandwidth than previous generation GPUs. NVIDIA says this enables 120 teraflops of deep learning performance.

V100-based systems announced include:

  • Dell EMC -- The PowerEdge R740 supporting up to three V100 GPUs for PCIe, the PowerEdge R740XD supporting up to three V100 GPUs for PCIe, and the PowerEdge C4130 supporting up to four V100 GPUs for PCIe or four V100 GPUs for NVIDIA NVLink™ interconnect technology in an SXM2 form factor.
  • HPE -- HPE Apollo 6500 supporting up to eight V100 GPUs for PCIe and HPE ProLiant DL380 systems supporting up to three V100 GPUs for PCIe.
  • IBM -- The next generation of IBM Power Systems servers based on the POWER9 processor will incorporate multiple V100 GPUs and take advantage of the latest generation NVLink interconnect technology -- featuring fast GPU-to-GPU interconnects and an industry-unique OpenPOWER CPU-to-GPU design for maximum throughput.
  • Supermicro -- Products supporting the new Volta GPUs include a 7048GR-TR workstation for all-around high-performance GPU computing, 4028GR-TXRT, 4028GR-TRT and 4028GR-TR2 servers designed to handle the most demanding deep learning applications, and 1028GQ-TRT servers built for applications such as advanced analytics.

Friday, August 11, 2017

NVIDIA Cits Growth in Data center, Auto

NVIDIA reported record revenue for its second quarter ended July 30, 2017, of $2.23 billion, up 56 percent from $1.43 billion a year earlier, and up 15 percent from $1.94 billion in the previous quarter. GAAP EPS was $0.92, up 124 percent from a year ago.
"Adoption of NVIDIA GPU computing is accelerating, driving growth across our businesses," said Jensen Huang, founder and chief executive officer of NVIDIA. "Datacenter revenue increased more than two and a half times. A growing number of car and robot-taxi companies are choosing our DRIVE PX self-driving computing platform. And in Gaming, increasingly the world's most popular form of entertainment, we power the fastest growing platforms - GeForce and Nintendo Switch.

"Nearly every industry and company is awakening to the power of AI. Our new Volta GPU, the most complex processor ever built, delivers a 100-fold speedup for deep learning beyond our best GPU of four years ago. This quarter, we shipped Volta in volume to leading AI customers. This is the era of AI, and the NVIDIA GPU has become its brain. We have incredible opportunities ahead of us," he said.

http://investor.nvidia.com/results.cfm


NVIDIA Debuts Latest Quadro Pascal GPUs


NVIDIA introduced its latest line-up of Quadro GPUs products, all based on its Pascal architecture and designed for professional workflows in engineering, deep learning, VR, and many vertical applications. "Professional workflows are now infused with artificial intelligence, virtual reality and photorealism, creating new challenges for our most demanding users," said Bob Pette, vice president of Professional Visualization at NVIDIA. "Our new Quadro...





NVIDIA Advances its Pascal-based GPUs for AI


NVIDIA is expanding its Pascal™ architecture-based deep learning platform with the introduction of new Tesla P4 and P40 GPU accelerators and new software. The solution is aimed at accelerating inferencing production workloads for artificial intelligence services, such as voice-activated assistance, email spam filters, and movie and product recommendation engines. NVIDIA said its GPU are better at these tasks than current CPU-based technology, which...


Sunday, February 5, 2017

NVIDIA Debuts Latest Quadro Pascal GPUs

NVIDIA introduced its latest line-up of Quadro GPUs products, all based on its Pascal architecture and designed for professional workflows in engineering, deep learning, VR, and many vertical applications.

"Professional workflows are now infused with artificial intelligence, virtual reality and photorealism, creating new challenges for our most demanding users," said Bob Pette, vice president of Professional Visualization at NVIDIA. "Our new Quadro lineup provides the graphics and compute performance required to address these challenges. And, by unifying compute and design, the Quadro GP100 transforms the average desktop workstation with the power of a supercomputer."

Some highlight of the new generation of Quadro Pascal-based GPUs:

  • the GP100 combines double precision performance with 16GB of high-bandwidth memory (HBM2) so users can conduct simulations during the design process and gather realistic multiphysics simulations faster than ever before. Customers can combine two GP100 GPUs with NVLink technology and scale to 32GB of HBM2 to create a massive visual computing solution on a single workstation.
  • the GP100 provides more than 20 TFLOPS of 16-bit floating point precision computing, making it an ideal development platform to enable deep learning in Windows and Linux environments.
  • the "VR Ready" Quadro GP100 and P4000 have the power to create detailed, lifelike, immersive environments. Larger, more complex designs can be experienced at scale.
  • Pascal-based Quadro GPUs can render photorealistic images more than 18 times faster than a CPU.
  • Visualize data in high resolution and HDR color on up to four 5K displays.
  • for digital signage, up to 32 4K displays can be configured through a single chassis by combining up to eight P4000 GPUs and two Quadro Sync II cards.

The new cards complete the entire NVIDIA Quadro Pascal lineup including the previously announced P6000, P5000 and mobile GPUs. The entire NVIDIA Quadro Pascal lineup supports the latest NVIDIA CUDA 8 compute platform providing developers access to powerful new Pascal features in developer tools, performance enhancements and new libraries including nvGraph.

http://www.nvidia.com

Sunday, October 16, 2016

Aliyun Looks to AMD for Cloud-based GPUs

AMD and Alibaba Cloud (Aliyun) announced a collaboration to strengthen research and cooperation related to the use of AMD Radeon Pro GPU technology in Alibaba Cloud’s global data centers.

“The partnership between AMD and Alibaba Cloud will bring both of our customers more diversified, cloud-based graphic processing solutions. It is our vision to work together with leading technology firms like AMD to empower businesses in every industry with cutting-edge technologies and computing capabilities,” said Simon Hu, president of Alibaba Cloud.

“The collaboration between AMD and Alibaba Cloud leverages the world-class technology and software engineering capabilities of both companies to meet the growing demand for standards-based GPU computing solutions capable of enabling more immersive and intuitive cloud services,” said AMD President and CEO Dr. Lisa Su. “Working closely with industry leaders like Alibaba Cloud helps ensure the investments AMD is making in our high-performance graphics and computing datacenter products continue to align with the needs of the broader cloud market.”

At this week's Computing Conference in Hangzhou, China, AMD is conducting the following demos:


  • An Alibaba Cloud Single Root Input/Output Virtualization (SR-IOV) Solution featuring AMD Radeon Pro server technology. The demo is powered by the Radeon FirePro™ S7150 x2 GPU featuring AMD Multi-user GPU (MxGPU) hardware-based server virtualization technology. The solution features the industry’s only hardware-virtualized GPU technology, which provides guaranteed service levels and improves security for remote workstation, cloud gaming, cloud computing, and Virtual Desktop Infrastructure (VDI) implementations.
  • A virtual reality (VR) experience demo powered by AMD Radeon VR Ready Premium graphics featuring AMD’s powerful, energy efficient Polaris graphics architecture.


http://www.amd.com

Tuesday, April 5, 2016

NVIDIA Unveils GPU Accelerators for Deep Learning AI

NVIDIA unveiled its most advanced accelerator to date -- the Tesla P100 -- based on Pascal architecture and composed of an array of Graphics Processing Clusters (GPCs), Streaming Multiprocessors (SMs), and memory controllers. The Tesla P100, which is implemented in 16nm FinFET on a massive 610mm2die, enables a new class of servers that can deliver the performance of hundreds of CPU server nodes.

NVIDIA said its accelerator brings five breakthroughs:

  • NVIDIA Pascal architecture for exponential performance leap -- a Pascal-based Tesla P100 solution delivers over a 12x increase in neural network training performance compared with a previous-generation NVIDIA Maxwell-based solution.
  • NVIDIA NVLink for maximum application scalability -- The NVIDIA NVLink high-speed GPU interconnect scales applications across multiple GPUs, delivering a 5x acceleration in bandwidth compared to today's best-in-class solution. Up to eight Tesla P100 GPUs can be interconnected with NVLink to maximize application performance in a single node, and IBM has implemented NVLink on its POWER8 CPUs for fast CPU-to-GPU communication.
  • 16nm FinFET for unprecedented energy efficiency -- with 15.3 billion transistors built on 16 nanometer FinFET fabrication technology, the Pascal GPU is the world's largest FinFET chip ever built.
  • CoWoS with HBM2 for big data workloads -- the Pascal architecture unifies processor and data into a single package to deliver unprecedented compute efficiency. An innovative approach to memory design, Chip on Wafer on Substrate (CoWoS) with HBM2, provides a 3x boost in memory bandwidth performance, or 720GB/sec, compared to the Maxwell architecture.
  • New AI algorithms for peak performance -- new half-precision instructions deliver more than 21 teraflops of peak performance for deep learning.

At its GPU Technology conference in San Jose, Nvidia also unveiled its DGX-1 Deep Learning supercomputer. It is a turnkey system that integrates eight Tesla P100 GPU accelerators, delivering the equivalent throughput of 250 x86 servers.

"Artificial intelligence is the most far-reaching technological advancement in our lifetime," said Jen-Hsun Huang, CEO and co-founder of NVIDIA. "It changes every industry, every company, everything. It will open up markets to benefit everyone. Data scientists and AI researchers today spend far too much time on home-brewed high performance computing solutions. The DGX-1 is easy to deploy and was created for one purpose: to unlock the powers of superhuman capabilities and apply them to problems that were once unsolvable."

"NVIDIA GPU is accelerating progress in AI. As neural nets become larger and larger, we not only need faster GPUs with larger and faster memory, but also much faster GPU-to-GPU communication, as well as hardware that can take advantage of reduced-precision arithmetic. This is precisely what Pascal delivers," said Yann LeCun, director of AI Research at Facebook.

http://nvidianews.nvidia.com

Monday, January 4, 2016

NVIDIA Develops Supercomputer for Self-Driving Cars

NVIDIA unveiled an artificial-intelligence supercomputer for self-driving cars.

In a pre-CES keynote in Las Vegas, NVIDIA's CEO Jen-Hsun Huang said the onboard processing needs of future automobiles far exceeds the silicon capabilities currently on the market.

NVIDIA's DRIVE PX 2 will pack the processing equivalent of 150 MacBook Pros -- 8 teraflops of power -- enough to process data from multiple sensors in real time, providing 360-degree detection of lanes, vehicles, pedestrians, signs, etc. The design will use the company's next gen Tegra processors plus two discrete, Pascal-based GPUs. NVIDIA is also developing a suite of software tools, libraries and modules to accelerate the development and testing of autonomous vehicles.

Volvo will be the first company to deploy the DRIVE PX 2. A public test of 100 autonomous cars using this technology is planned for Gothenburg, Sweden.

http://nvidianews.nvidia.com/news/nvidia-boosts-iq-of-self-driving-cars-with-world-s-first-in-car-artificial-intelligence-supercomputer

Tuesday, November 10, 2015

NVIDIA's Jetson Wants to be the Brain of Autonomous Robots and Drones

NVIDIA unveiled a credit-card sized module named Jetson for a new generation of smart, autonomous machines that can learn.

The NVIDIA Jetson TX1 module is an embedded computer designed to process deep neural networks -- computer software that can learn to recognize objects or interpret information. The module brings 1 teraflops of processing performance to enable autonomous devices to recognize visual data or interpret images, process conversational speech or navigate real world environments.

"Jetson TX1 will enable a new generation of incredibly capable autonomous devices," said Deepu Talla, vice president and general manager of the Tegra business at NVIDIA. "They will navigate on their own, recognize objects and faces, and become increasingly intelligent through machine learning. It will enable developers to create industry-changing products."

Key features of Jetson TX1 include:

  • GPU: 1 teraflops, 256-core Maxwell architecture-based GPU offering best-in-class performance
  • CPU: 64-bit ARM A57 CPUs
  • Video: 4K video encode and decode
  • Camera: Support for 1400 megapixels/second
  • Memory: 4GB LPDDR4; 25.6 gigabits/second
  • Storage: 16GB eMMC
  • Wi-Fi/Bluetooth: 802.11ac 2x2 Bluetooth ready
  • Networking: 1GB Ethernet
  • OS Support: Linux for Tegra
  • Size: 50mm x 87mm, slightly smaller than a credit card

http://www.nvidia.com

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