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  1. NVIDIA CEO Jensen Huang to Keynote World’s Premier AI Conference

    GLOBE NEWSWIRE -- NVIDIA founder and CEO Jensen Huang will deliver the opening keynote address at the 10th annual GPU Technology Conference, being held March 17-21, in San Jose, Calif.

    Huang will highlight the company’s latest innovations in AI, autonomous vehicles and robotics in his keynote on Monday, March 18, at 2 pm. As many as 10,000 developers, data scientists and industry executives are expected to register for this year’s conference, being held at the San Jose McEnery Convention Center.
  2. NVIDIA-Based Computer Vision Camera Built for Smart City Applications - Security Sales & Integration

    Entropix, a provider of AI-powered computational imaging software and Boulder AI, a manufacturer of intelligent camera solutions, have teamed up to produce and distribute what it claims is “the world’s most powerful computer vision data collection system.”

    The camera will utilize NVIDIA’s latest generation Tegra and Xavier processing architectures and will be built upon the DNNCam platform, fully integrated with the Entropix Resolution Engine and Enterprise Computer Vision Management System (ECVMS).
  3. NVIDIA's TITAN RTX Helps Researchers More Quickly Detect Osteoporosis

    A team of researchers at Dartmouth College are reporting promising results after swapping their Titan Xp GPU for the TITAN RTX. Running their existing code on the new GPU, the team achieved an 80% performance increase when training a pair of neural networks to detect osteoporotic vertebral fractures.

    To evaluate the new GPUs performance, the team compared a TITAN Xp with the new generation TITAN RTX GPU.

    “We trained our proposed deep neural network (CNN + LSTM) on a dataset of CT images for automatic detection of osteoporotic vertebral fractures as it was presented in our 2018 paper,” the team said.

    Trained for 300 epochs on dataset that included over 1400 CT scans, comprised of 10,546 two-dimensional 2D images, the training process was 80% faster with the new TITAN RTX GPU, the researchers said.
  4. France Merges Cascade Lake Xeons With Volta Tesla GPUs For AI Supercomputer

    In terms of hardware, Jean Zay is based on the HPE SGI 8600 platform and will be comprised of 1,528 CPU-only nodes, which are outfitted with two “Cascade Lake” Xeon SP 6248 processors (20 cores at 2.5 GHz), and an additional 261 GPU-accelerated nodes, each equipped with two of those same Cascade Lake processors plus four Nvidia Tesla “Volta” V100 GPU accelerators. Each of the nodes will sport 192 GB of main memory, with each of the GPU outfitted with 32 GB of its own local memory. The system will be hooked together using Intel’s Omni-Path fabric using a quad-rail interconnect that delivers 400 Gb/sec of aggregate bandwidth. It will be France’s second most powerful supercomputer in the country, trailing only the 23 petaflops Tera 1000 BullSequana system.
  5. GPU Applications Get The Container Treatment

    Containerized high performance computing is fast becoming one of the more popular ways of running HPC workloads. And perhaps nowhere is this more apparent than in the realm of GPU computing, where Nvidia and its partners have devoted considerable attention to making this method as seamless as possible.

    This is all the more appreciated in HPC set-ups, where GPUs add another layer of software complexity, which, in turn, has provided an extra bit of motivation for Nvidia to embrace the container model. The company’s efforts in this area has centered on the Nvidia GPU Cloud (NGC) which encompasses its own registry of GPU-based containers. The only significant drawback is that compatibility is limited to Nvidia GPUs of fairly recent vintage, specifically the Pascal-generation and Volta-generation processors.
  6. NVLink Bridge Comparison: Quadro RTX vs. GV100 - What's the Difference? - Exxact

    Today we’ll compare the NVLink Bridge for the New NVIDIA Quadro RTX, and the previous generation NVIDIA Quadro GV100 graphics cards. There are some major differences here, so be sure to pay attention!

    Probably the most stark difference is the fact that the RTX only has 1x NVLink bridge, as where the older Volta Quadro GV100 has two. As where the top of the link Quadro RTX 8000/6000 has a maximum bandwidth of 100 GB/s, the older Quadro GV100 having two bridges, effectively allowing for a maximum bandwidth of 200 GB/s! Furthermore, on the lower end Quadro RTX 5000, the maximum bandwidth is (only) 50GB/s, half that of the higher end RTX cards.
  7. The New Chip From NVIDIA Is All Set To Become The Brain Of Robots

    This Ikea kitchen is incubating the robots of the future

    Nvidia today opened its robotics research lab, a 13,000-foot facility in Seattle. The lab will house 50 roboticists, 20 from Nvidia Research staff, and others from the wider academic research community.

    Dieter Fox, a member of University of Washington computer science faculty, is the director of the lab. The lab was intentionally opened in Seattle to be close to knowledgable people from the University of Washington such as Human-Centered Robotics Lab director Maya Cakmak.

    The lab officially opened last November but moved to its permanent headquarters today.
  8. NVIDIA's $1,100 AI brain for robots goes on sale

    NVIDIA's plan to power autonomous robots has kicked off in earnest. The company has released a Jetson AGX Xavier Module that gives robots and other intelligent machines the processing oomph they need for their AI 'brains.' You're not about to buy one yourself -- it costs $1,099 each in batches of 1,000 units. However, it could be important for delivery robots and other automatons that need a lot of specialized performance with relatively little power use.

    The Jetson Xavier system-on-chip at the heart of the module relies on no less than six processors to get its work done. There's a relatively conventional eight-core ARM chip, but you'll also find a Volta-based GPU, two NVDLA deep learning chips and dedicated image, video and vision components.
  9. Mercedes and NVIDIA team up to build next-gen AI vehicles

    From modular vans to autonomous cars -- and, as recently revealed at CES, gesture-based controls -- Mercedes has some big ambitions for the next generation of its vehicles. Now, it's announced that AI company NVIDIA will be the team to help it achieve them.

    Speaking to the audience at the Mercedes-Benz booth at this year's CES, Mercedes-Benz Executive Vice President Sajjad Khan and NVIDIA founder and CEO Jensen Huang unveiled their vision for the next-generation of AI vehicles. "We're announcing a new partnership going forward, creating a computer that defines the future of autonomous vehicles, the future of AI and the future of mobility," said Huang.
  10. Nvidia’s T4 GPUs are now available in beta on Google Cloud – TechCrunch

    Google Cloud today announced that Nvidia’s Turing-based Tesla T4 data center GPUs are now available in beta in its data centers in Brazil, India, Netherlands, Singapore, Tokyo and the United States. Google first announced a private test of these cards in November, but that was a very limited alpha test. All developers can now take these new T4 GPUs for a spin through Google’s Compute Engine service.

    The T4, which essentially uses the same processor architecture as Nvidia’s RTX cards for consumers, slots in-between the existing Nvidia V100 and P4 GPUs on the Google Cloud Platform. While the V100 is optimized for machine learning, though, the T4 (as its P4 predecessor) is more of a general-purpose GPU that also turns out to be great for training models and inferencing.
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Über Pro_PainKiller
Liest PCGH:
PCGH.de & Heft (Abo)
Biografie:
HPC Consultant
Wohnort:
LinkX Kybernetik Interconnect
Interessen:
Machine Learning: deep structured & hierarchical learning
Beruf:
HPC IT Verantwortlicher
Mein PC
Prozessor:
Intel Xeon E5-4650L FibreCluster
Mainboard:
HP ProLiant BL660c Gen8
Arbeitsspeicher:
512GB +64 GB
Festplatte(n):
SAS-SSD 1200.2 6-fach 3840GB Fibreraid @ VMware vSphere Enterprise & Oracle VM VirtualBox
Grafikkarte:
Titan Xp @ SLi
Sound:
Onboard deaktiviert
Netzteil:
Enterprise Server Redundant Hot-Plug-Netzteil mit 2200 W
Gehäuse:
Server-Racks TS 8, High Performance Cooling Systeme HPC
Betriebssystem:
Linux (alle Distributionen)

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NVIDIA DGX Station | Intel Xeon Platinum 8180 @ 4.6 GHz (28-Core) | 512GB LRDIMM DDR4 | 4X Tesla V100 | 128GB HBM2 | NVLink Quad-GPU
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