Showing posts with label Nvidia. Show all posts
Showing posts with label Nvidia. Show all posts

Thursday, July 9, 2020

Google Cloud activates NVIDIA Ampere GPUs

Google Cloud is now offering Accelerator-Optimized VM (A2) instance featuring the recently launched NVIDIA A100 Tensor Core GPU. Google is the first cloud service provider to offer the new NVIDIA GPU.

For large, demanding workloads, Google Compute Engine offers customers the a2-megagpu-16g instance, which comes with 16 A100 GPUs, offering a total of 640GB of GPU memory and 1.3TB of system memory — all connected through NVSwitch with up to 9.6TB/s of aggregate bandwidth.

For those with smaller workloads, Google Compute Engine is also offering A2 VMs in smaller configurations to match specific applications’ needs.

Google Cloud announced that additional NVIDIA A100 support is coming soon to Google Kubernetes Engine, Cloud AI Platform and other Google Cloud services.

https://blogs.nvidia.com/blog/2020/07/07/nvidia-ampere-gpus-google-cloud/

Thursday, May 21, 2020

NVIDIA's data center business tops $1 billion in quarterly sales, up 80% YoY

NVIDIA reported revenue of $3.08 billion for its first fiscal quarter ended April 26, 2020, up 39 percent from $2.22 billion a year earlier, and down 1 percent from $3.11 billion in the previous quarter.

GAAP earnings per diluted share for the quarter were $1.47, up 130 percent from $0.64 a year ago, and down 4 percent from $1.53 in the previous quarter. Non-GAAP earnings per diluted share were $1.80, up 105 percent from $0.88 a year earlier, and down 5 percent from $1.89 in the previous quarter.

NVIDIA completed its acquisition of Mellanox Technologies  April 27, 2020, for a transaction value of $7 billion. It also transitioned its GPU Technology Conference to an all-digital format, drawing more than 55,000 registered participants, while NVIDIA founder and CEO Jensen Huang’s keynote videos were viewed 3.8 million times in their first three days.



“As the world battles COVID-19, we salute the first responders, healthcare workers, and service workers who courageously step in harm’s way to save lives and keep the world going,” said Jensen Huang, NVIDIA's CEO. NVIDIA had an excellent quarter. The acquisition of Mellanox expands our cloud and data center opportunity. We raised the bar for AI computing with the launch and shipment of our Ampere GPU. And our digital GTC conference attracted a record number of developers, highlighting the accelerating adoption of NVIDIA GPU computing.

“Our Data Center business achieved a record and its first $1 billion quarter. NVIDIA is well positioned to advance the most powerful technology forces of our time – cloud computing and AI,” he said.

Some highlights:

  • Gaming - First-quarter revenue was $1.34 billion, down 10 percent sequentially and up 27 percent from a year earlier.
  • Data Center - First-quarter revenue was $1.14 billion, up 18 percent sequentially and up 80 percent from a year earlier.
  • Professional Visualization - First-quarter revenue was $307 million, down 7 percent sequentially and up 15 percent from a year earlier.
  • Automotive - First-quarter revenue was $155 million, down 5 percent sequentially and down 7 percent from a year earlier.


Thursday, May 14, 2020

NVIDIA unveils 8th-gen Ampere GPU architecture

NVIDIA unveiled its Ampere architecture, described as the "greatest generational performance leap of NVIDIA’s eight generations of GPUs."

In a keynote recorded at hi home kitchen, NVIDIA's CEO Jensen Huang said the Ampere architecture will boost performance by up to 20x over its predecessors. More specifically, 6x higher performance than NVIDIA’s previous generation Volta architecture for training and 7x higher performance for inference.

Key features of A100:

  • More than 54 billion transistors, making it the world’s largest 7-nanometer processor.
  • Third-generation Tensor Cores with TF32, a new math format that accelerates single-precision AI training out of the box. NVIDIA’s widely used Tensor Cores are now more flexible, faster and easier to use, Huang explained.
  • Structural sparsity acceleration, a new efficiency technique harnessing the inherently sparse nature of AI math for higher performance.
  • Multi-instance GPU, or MIG, allowing a single A100 to be partitioned into as many as seven independent GPUs, each with its own resources.
  • Third-generation NVLink technology, doubling high-speed connectivity between GPUs, allowing A100 servers to act as one giant GPU.

The NVIDIA DGX A100 will power the third generation of the NVIDIA DGX AI server, boasting 5-petaflops of performance.

Tuesday, May 5, 2020

Digital Realty hosts AI clusters powered by NVIDIA GPUs

Digital Realty announced a new solution to deliver AI-ready IT infrastructure powered by NVIDIA DGX systems. The solution enables the rapid deployment of artificial intelligence and machine learning workloads, and provides the components customers need to solve global coverage, capacity and network needs.

Powered by PlatformDIGITAL and NVIDIA DGX, the Data Hub solution accommodates typical enterprise deployments of AI infrastructure to address the placement, connectivity and hosting of critical data infrastructure in proximity to users, networks, clouds and things. It localizes data aggregation, staging, analytics, streaming and data management to optimize data exchange, empowering businesses to distribute intelligence across the enterprise to accelerate digital transformation initiatives.

NVIDIA DGX-1 delivers over 1 petaFLOPS of performance; NVIDIA DGX-2 delivers over 2 petaFLOPS.

https://www.digitalrealty.com/nvidia-digital-realty-partnership

Monday, May 4, 2020

NVIDIA acquires Cumulus, promising full-stack data center innovation

NVIDIA has acquired Cumulus Networks. Financial terms were not disclosed.

Cumulus, which was founded in 2010 by JR Rivers and Nolan Leake, developed a Linux-based operating system for network switches. The company signed licensing deals with Dell, HPE, Mellanox, and Lenovo. Cumulus is also known for its pioneering work with the open network install environment (ONIE) project.  Investors in the company included Andreessen Horowitz, Battery Ventures, Sequoia Capital, Peter Wagner and 4 of the 5 original VMware founders. Cumulus is based in Mountain View, California.

NVIDIA said the combination of its recently-acquired Mellanox division with Cumulus Networks will enable a new era for accelerated, software-defined data centers.

NVIDIA's target is to "innovate and optimize across the entire networking stack from chips and systems to software including analytics like Cumulus NetQ, delivering great performance and value to customers."

Mellanox has been collaborating with Cumulus since 2013. Mellanox Spectrum switches already ship with Cumulus Linux and SONiC, the open source offering forged in Microsoft’s Azure cloud and managed by the Open Compute Project.

NVIDIA acquires Mellanox - focus on Next Gen Data Centers

NVIDIA completed its $7 billion acquisition of Mellanox Technologies. The deal was originally announced on March 11, 2019.

NVIDIA says that by combining its computing expertise with Mellanox’s high-performance networking technology, data center customers will achieve higher performance, greater utilization of computing resources and lower operating costs.

“The emergence of AI and data science, as well as billions of simultaneous computer users, is fueling skyrocketing demand on the world’s datacenters,” said Jensen Huang, founder and CEO of NVIDIA. “Addressing this demand will require holistic architectures that connect vast numbers of fast computing nodes over intelligent networking fabrics to form a giant datacenter-scale compute engine.

“We share the same vision for accelerated computing as NVIDIA,” said Eyal Waldman, founder and CEO of Mellanox. “Combining our two companies comes as a natural extension of our longstanding partnership and is a great fit given our common performance-driven cultures. This combination will foster the creation of powerful technology and fantastic opportunities for our people.”

NVIDIA also promised to continue investing in Israel, where Mellanox is based.

The companies expect to close the deal by the end of 2019.




Monday, April 27, 2020

NVIDIA acquires Mellanox - focus on Next Gen Data Centers

NVIDIA completed its $7 billion acquisition of Mellanox Technologies. The deal was originally announced on March 11, 2019.

NVIDIA says that by combining its computing expertise with Mellanox’s high-performance networking technology, data center customers will achieve higher performance, greater utilization of computing resources and lower operating costs.

“The expanding use of AI and data science is reshaping computing and data center architectures,” said Jensen Huang, founder and CEO of NVIDIA. “With Mellanox, the new NVIDIA has end-to-end technologies from AI computing to networking, full-stack offerings from processors to software, and significant scale to advance next-generation data centers. Our combined expertise, supported by a rich ecosystem of partners, will meet the challenge of surging global demand for consumer internet services, and the application of AI and accelerated data science from cloud to edge to robotics.”

Eyal Waldman, founder and CEO of Mellanox, said: “This is a powerful, complementary combination of cultures, technology and ambitions. Our people are enormously enthusiastic about the many opportunities ahead. As Mellanox steps into the next exciting phase of its journey, we will continue to offer cutting-edge solutions and innovative products to our customers and partners. We look forward to bringing NVIDIA products and solutions into our markets, and to bringing Mellanox products and solutions into NVIDIA’s markets. Together, our technologies will provide leading solutions into compute and storage platforms wherever they are required.”

The acquisition is expected to be immediately accretive to NVIDIA’s non-GAAP gross margin, non-GAAP EPS and free cash flow, inclusive of incremental interest expense related to NVIDIA’s recent issuance of $5 billion of notes.

With Mellanox, NVIDIA targets full compute/network/storage stack

NVIDIA agreed to acquire Mellanox in a deal valued at approximately $6.9 billion.

The merger targets data centers in general and the high-performance computing (HPC) market in particular. Together, NVIDIA’s computing platform and Mellanox’s interconnects power over 250 of the world’s TOP500 supercomputers and have as customers every major cloud service provider and computer maker. Mellanox pioneered the InfiniBand interconnect technology, which along with its high-speed Ethernet products is now used in over half of the world’s fastest supercomputers and in many leading hyperscale datacenters.

NVIDIA said the acquired assets enables it to data center-scale workloads across the entire computing, networking and storage stack to achieve higher performance, greater utilization and lower operating cost for customers.

“The emergence of AI and data science, as well as billions of simultaneous computer users, is fueling skyrocketing demand on the world’s datacenters,” said Jensen Huang, founder and CEO of NVIDIA. “Addressing this demand will require holistic architectures that connect vast numbers of fast computing nodes over intelligent networking fabrics to form a giant datacenter-scale compute engine.

“We share the same vision for accelerated computing as NVIDIA,” said Eyal Waldman, founder and CEO of Mellanox. “Combining our two companies comes as a natural extension of our longstanding partnership and is a great fit given our common performance-driven cultures. This combination will foster the creation of powerful technology and fantastic opportunities for our people.”

NVIDIA also promised to continue investing in Israel, where Mellanox is based.

The companies expect to close the deal by the end of 2019.



NVIDIA cites increasing GPUdemand from data centers and gaming

NVIDIA reported quarterly revenue of $3.11 billion, up 41 percent from $2.21 billion a year earlier, and up 3 percent from $3.01 billion in the previous quarter.

GAAP earnings per diluted share for the quarter were $1.53, up 66 percent from $0.92 a year ago, and up 6 percent from $1.45 in the previous quarter. Non-GAAP earnings per diluted share were $1.89, up 136 percent from $0.80 a year earlier, and up 6 percent from $1.78 in the previous quarter.

For fiscal 2020, revenue was $10.92 billion, down 7 percent from $11.72 billion a year earlier. GAAP earnings per diluted share were $4.52, down 32 percent from $6.63 a year earlier. Non-GAAP earnings per diluted share were $5.79, down 13 percent from $6.64 a year earlier.

“Adoption of NVIDIA accelerated computing drove excellent results, with record data center revenue,” said Jensen Huang, founder and CEO of NVIDIA. “Our initiatives are achieving great success.

“NVIDIA RTX ray tracing is reinventing computer graphics, driving powerful adoption across gaming, VR and design markets, while opening new opportunities in rendering and cloud gaming. NVIDIA AI is enabling breakthroughs in language understanding, conversational AI and recommendation engines ― the core algorithms that power the internet today. And new NVIDIA computing applications in 5G, genomics, robotics and autonomous vehicles enable us to continue important work that has great impact."


Mellanox hits revenue of $429 million, up 40% yoy

Mellanox Technologies reported Q1 2020 revenue of $428.7 million, an increase of 40.5%, compared to $305.2 million in the first quarter of 2019.
GAAP gross margins were 66.8%, compared to 64.6% in the first quarter of 2019.

“Mellanox delivered record revenue and operating income in the first quarter of 2020. All our major product lines continued to grow. We are pleased to be shipping end-to-end solutions at speeds of 200 gigabits per second (Gbps) for both InfiniBand and Ethernet. In addition, we are shipping 400 Gbps Ethernet switches,” said Eyal Waldman, President and CEO of Mellanox Technologies.

“Sales of Ethernet adapter products increased 112% year-over-year. We expect our new ConnectX-6 Dx adapters and Bluefield-2 I/O Processing Units (IPUs), the latest additions to our industry-leading family of Smart NICs, to bring unprecedented security and co-processing capabilities to enterprise and cloud data centers. These capabilities will be further strengthened by our recent acquisition of Titan IC, the leading developer of network intelligence and security technology to accelerate search and big data analytics across a broad range of applications in data centers worldwide. The product line revenue of our Spectrum ASIC based Ethernet switch business grew 66% year-over-year. We recently began shipping Spectrum-3 based switches, the world’s first 12.8 Tbps networking platforms optimized for cloud, storage, and artificial intelligence,” continued Waldman.

“We are experiencing very strong adoption of InfiniBand for hyperscale artificial intelligence and cloud environments, resulting in tens of thousands of compute nodes connected with InfiniBand, which demonstrates the superior performance and scalability of InfiniBand. We saw 27% year-over-year growth in InfiniBand, led by strong demand for our HDR 200 gigabit solutions. HDR InfiniBand has been selected to interconnect national Exascale programs, large scale artificial intelligence and cloud platforms, and enterprise compute and storage infrastructures. We are proud that our InfiniBand technology is being utilized by many of the supercomputers in the Covid-19 High-Performance Computing Consortium, which is helping to aggregate computing capabilities for researchers to execute complex computations to help fight the novel Corona virus,” continued Waldman. “We are excited to participate in such important global initiatives through the adoption of our industry-leading adapters, switches, cables, and software, while also delivering strong financial performance for the first quarter of 2020.”

Thursday, February 13, 2020

NVIDIA cites increasing GPUdemand from data centers and gaming

NVIDIA reported quarterly revenue of $3.11 billion, up 41 percent from $2.21 billion a year earlier, and up 3 percent from $3.01 billion in the previous quarter.

GAAP earnings per diluted share for the quarter were $1.53, up 66 percent from $0.92 a year ago, and up 6 percent from $1.45 in the previous quarter. Non-GAAP earnings per diluted share were $1.89, up 136 percent from $0.80 a year earlier, and up 6 percent from $1.78 in the previous quarter.

For fiscal 2020, revenue was $10.92 billion, down 7 percent from $11.72 billion a year earlier. GAAP earnings per diluted share were $4.52, down 32 percent from $6.63 a year earlier. Non-GAAP earnings per diluted share were $5.79, down 13 percent from $6.64 a year earlier.

“Adoption of NVIDIA accelerated computing drove excellent results, with record data center revenue,” said Jensen Huang, founder and CEO of NVIDIA. “Our initiatives are achieving great success.

“NVIDIA RTX ray tracing is reinventing computer graphics, driving powerful adoption across gaming, VR and design markets, while opening new opportunities in rendering and cloud gaming. NVIDIA AI is enabling breakthroughs in language understanding, conversational AI and recommendation engines ― the core algorithms that power the internet today. And new NVIDIA computing applications in 5G, genomics, robotics and autonomous vehicles enable us to continue important work that has great impact."


Monday, October 21, 2019

NVIDIA unveils EGX Edge Supercomputing platform

NVIDIA introduced a high-performance, cloud-native edge platform.

The NVIDIA EGX Edge Supercomputing Platform combines NVIDIA CUDA-X software with NVIDIA-certified GPU servers and devices.

The EGX platform features software to support a wide range of applications, including NVIDIA Metropolis, which can be used to build smart cities and intelligent video analytics applications, as well as the just-announced NVIDIA Aerial software, which allows telcos to build completely virtualized 5G radio access networks that are highly programmable, scalable and energy efficient.

Early ecosystem partners include Microsoft, Ericsson and Red Hat. The EGX software stack architecture is supported by leading hybrid-cloud partners Canonical, Cisco, Nutanix, Red Hat and VMware.

Early adopters include Walmart, BMW, Procter & Gamble, Samsung Electronics and NTT East, as well as the cities of San Francisco and Las Vegas.

“We’ve entered a new era, where billions of always-on IoT sensors will be connected by 5G and processed by AI,” said Jensen Huang, NVIDIA founder and CEO, at a keynote at the start of MWC Los Angeles. “Its foundation requires a new class of highly secure, networked computers operated with ease from far away.

“At Walmart, we’re using AI to define the future of retail and re-think how technology can further enhance how we operate our stores,” said Mike Hanrahan, CEO of Walmart Intelligent Retail Lab. “With NVIDIA’s EGX edge computing platform, Walmart’s Intelligent Retail Lab is able to bring real-time AI compute to our store, automate processes and free up our associates to create a better and more convenient shopping experience for our customers.”

NVIDIA brings GPU power to Ericsson's virtualized 5G RAN

Ericsson and NVIDIA are collaborating on technologies for virtualized 5G radio access networks (RAN).

The companies said their ultimate goal is to commercialize virtualized RAN technologies to deliver radio networks with flexibility and shorter time to market for new services, such as augmented reality, virtual reality and gaming.

Fredrik Jejdling, Executive Vice President and Head of Networks, Ericsson, says: “As a technology leader, we embrace openness and new platforms where we can continue to innovate and push boundaries to provide our customers with the best possible solutions. With NVIDIA we will jointly look at bringing alternatives to market for virtualizing the complete radio access network.”

Jensen Huang, founder and chief executive officer of NVIDIA, says: “5G is set to turbocharge the intelligent edge revolution. Fusing 5G, supercomputing, and AI has enabled us to create a revolutionary communications platform supporting, someday, trillions of always-on, AI-enabled smart devices. Combining our world-leading capabilities, NVIDIA and Ericsson are helping to invent this exciting future.”

Thursday, July 11, 2019

NVIDIA expands DGX-Ready Data Center program

NVIDIA announced the international expansion of its DGX-Ready Data Center program with three new partners in Europe, five in Asia and two in North America. NVIDIA's program now includes 19 validated partners around the world.

DGX-Ready Data Center partners offer world-class facilities to host DGX AI compute infrastructure, giving more customers access to AI-ready data center facilities while saving on capital expenditures and keeping operational costs low.

The program is now offered in 24 markets, including Australia, Austria, Brazil, Canada, China, Colombia, Denmark, France, Germany, Hong Kong, Iceland, Ireland, Italy, Japan, the Netherlands, Peru, Singapore, South Korea, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States — with more coming soon.

Among the new locations is the Fujitsu Yokohama Data Center in Japan, which hosts dozens of NVIDIA AI systems.

“The Fujitsu Yokohama Data Center hosts more than 60 NVIDIA DGX-1 and DGX-2 systems,” said Hisaya Nakagawa, director at Fujitsu. “As a DGX-Ready Data Center program partner, we’re able to offer customers our world-class, state-of-the-art facility to run their most important AI workloads. With this program, customers can operationalize AI infrastructure swiftly and enjoy a jumpstart on their business transformation.”

NVIDIA brings 10x performance for Deep Learning System

At its annual GTC conference in San Jose, NVIDIA introduced its 2 petaflop, DGX-2 Deep Learning System, promising a 10x performance boost on deep learning workloads compared with the previous generation from six months ago.

Key advancements in NVIDIA platform include a 2x memory boost to NVIDIA Tesla V100 datacenter GPU, and a revolutionary new GPU interconnect fabric called NVIDIA NVSwitch, which enables up to 16 Tesla V100 GPUs to simultaneously communicate at a record speed of 2.4 terabytes per second. NVIDIA also introduced an updated, fully optimized software stack.

These advancements enable the NVIDIA DGX-2 server to deliver two petaflops of computational power -- the equivalent of 300 servers occupying 15 racks of datacenter space, while being 60x smaller and 18x more power efficient.

“The extraordinary advances of deep learning only hint at what is still to come,” said Jensen Huang, NVIDIA founder and CEO, as he unveiled the news at GTC 2018. “Many of these advances stand on NVIDIA’s deep learning platform, which has quickly become the world’s standard. We are dramatically enhancing our platform’s performance at a pace far exceeding Moore’s law, enabling breakthroughs that will help revolutionize healthcare, transportation, science exploration and countless other areas.”

Monday, May 27, 2019

NVIDIA unveils EGX Edge Computing Platform

NVIDIA introduced its EGX edge computing platform for performing low-latency AI on continuous streaming data between 5G base stations or other edge locations.

NVIDIA said EGX was created to perform instantaneous, high-throughput AI where data is created – with guaranteed response times, while reducing the amount of data that must be sent to the cloud.

“Enterprises demand more powerful computing at the edge to process their oceans of raw data — streaming in from countless interactions with customers and facilities — to make rapid, AI-enhanced decisions that can drive their business,” said Bob Pette, vice president and general manager of Enterprise and Edge Computing at NVIDIA. “A scalable platform like NVIDIA EGX allows them to easily deploy systems to meet their needs on premises, in the cloud or both.”

EGX begins with the tiny NVIDIA Jetson Nano, which delivers one-half trillion operations per second (TOPS) of processing in only a few watts, and scales all the way to a full rack of NVIDIA T4 servers, delivering more than 10,000 TOPS.

EGX servers are available from global enterprise computing providers ATOS, Cisco, Dell EMC, Fujitsu, Hewlett Packard Enterprise, Inspur and Lenovo. They are also available from major server and IoT system makers Abaco, Acer, ADLINK, Advantech, ASRock Rack, ASUS, AverMedia, Cloudian, Connect Tech, Curtiss-Wright, GIGABYTE, Leetop, MiiVii, Musashi Seimitsu, QCT, Sugon, Supermicro, Tyan, WiBase and Wiwynn.

NVIDIA EGX servers are tuned for NVIDIA Edge Stack and NGC-Ready validated for CUDA-accelerated containers.

NVIDIA has partnered with Red Hat to integrate and optimize NVIDIA Edge Stack with OpenShift. NVIDIA Edge Stack is optimized software that includes NVIDIA drivers, a CUDA Kubernetes plugin, a CUDA container runtime, CUDA-X libraries and containerized AI frameworks and applications, including TensorRT, TensorRT Inference Server and DeepStream.

NVIDIA is also promoting “On-Prem AI Cloud-in-a-Box”, which combines the full range of NVIDIA AI computing technologies with Red Hat OpenShift and NVIDIA Edge Stack together with Mellanox and Cisco security, networking and storage technologies.

“Mellanox Smart NICs and switches provide the ideal I/O connectivity for data access that scale from the edge to hyperscale data centers,” said Michael Kagan, chief technology officer at Mellanox Technologies. “The combination of high-performance, low-latency and accelerated networking provides a new infrastructure tier of computing that is critical to efficiently access and supply the data needed to fuel the next generation of advanced AI solutions on edge platforms such as NVIDIA EGX.”

“Cisco is excited to collaborate with NVIDIA to provide edge-to-core full stack solutions for our customers, leveraging Cisco’s EGX-enabled platforms with Cisco compute, fabric, storage, and management software and our leading Ethernet and IP-based networking technologies,” said Kaustubh Das, vice president of Cisco Computing Systems.

https://nvidianews.nvidia.com/news/nvidia-launches-edge-computing-platform-to-bring-real-time-ai-to-global-industries

Monday, March 18, 2019

AWS to offer NVIDIA T4 Tensor Core GPUs

Amazon Web Services will begin offering NVIDIA T4 Tensor Core GPUs as part of its Amazon Elastic Compute Cloud (EC2) G4 instances.

The new G4 instances are aimed at AI services. Through AWS Marketplace, customers will be able to pair the G4 instances with NVIDIA GPU acceleration software, including NVIDIA CUDA-X AI libraries for accelerating deep learning, machine learning and data analytics.

T4 will also be supported by Amazon Elastic Container Service for Kubernetes, making it possible to deploy, manage and scale containerized applications on EC2 G4 GPU instances using Kubernetes.

“NVIDIA and AWS have worked together for a long time to help customers run compute-intensive AI workloads in the cloud and create incredible new AI solutions,” said Matt Garman, vice president of Compute Services at AWS. “With our new T4-based G4 instances, we’re making it even easier and more cost-effective for customers to accelerate their machine learning inference and graphics-intensive applications.”

T4 will join other Amazon EC2 instances featuring NVIDIA GPUs, providing developers and data scientists with the most sophisticated compute resources available to support a variety of customer needs.

Monday, March 11, 2019

With Mellanox, NVIDIA targets full compute/network/storage stack

NVIDIA agreed to acquire Mellanox in a deal valued at approximately $6.9 billion.

The merger targets data centers in general and the high-performance computing (HPC) market in particular. Together, NVIDIA’s computing platform and Mellanox’s interconnects power over 250 of the world’s TOP500 supercomputers and have as customers every major cloud service provider and computer maker. Mellanox pioneered the InfiniBand interconnect technology, which along with its high-speed Ethernet products is now used in over half of the world’s fastest supercomputers and in many leading hyperscale datacenters.

NVIDIA said the acquired assets enables it to data center-scale workloads across the entire computing, networking and storage stack to achieve higher performance, greater utilization and lower operating cost for customers.

“The emergence of AI and data science, as well as billions of simultaneous computer users, is fueling skyrocketing demand on the world’s datacenters,” said Jensen Huang, founder and CEO of NVIDIA. “Addressing this demand will require holistic architectures that connect vast numbers of fast computing nodes over intelligent networking fabrics to form a giant datacenter-scale compute engine.

“We share the same vision for accelerated computing as NVIDIA,” said Eyal Waldman, founder and CEO of Mellanox. “Combining our two companies comes as a natural extension of our longstanding partnership and is a great fit given our common performance-driven cultures. This combination will foster the creation of powerful technology and fantastic opportunities for our people.”

NVIDIA also promised to continue investing in Israel, where Mellanox is based.

The companies expect to close the deal by the end of 2019.




Thursday, February 14, 2019

NVIDIA expects return to sustained growth

NVIDIA reported revenue of $2.21 billion for its fourth quarter ended Jan. 27, 2019, down 24 percent from $2.91 billion a year earlier, and down 31 percent from $3.18 billion in the previous quarter. GAAP earnings per diluted share for the quarter were $0.92, down 48 percent from $1.78 a year ago and down 53 percent from $1.97 in the previous quarter. Non-GAAP earnings per diluted share were $0.80, down 53 percent from $1.72 a year earlier and down 57 percent from $1.84 in the previous quarter.

For fiscal 2019, revenue was $11.72 billion, up 21 percent from $9.71 billion a year earlier. GAAP earnings per diluted share were $6.63, up 38 percent from $4.82 a year earlier. Non-GAAP earnings per diluted share were $6.64, up 35 percent from $4.92 a year earlier.

“This was a turbulent close to what had been a great year,” said Jensen Huang, founder and CEO of NVIDIA. “The combination of post-crypto excess channel inventory and recent deteriorating end-market conditions drove a disappointing quarter."

“Despite this setback, NVIDIA’s fundamental position and the markets we serve are strong. The accelerated computing platform we pioneered is central to some of world’s most important and fastest growing industries – from artificial intelligence to autonomous vehicles to robotics. We fully expect to return to sustained growth."

Tuesday, January 29, 2019

Microsoft Azure adds Nvidia Quadro Virtual Workstation

Microsoft Azure will begin offering NVIDIA Tesla GPU-accelerated Quadro Virtual Workstation (Quadro vWS). Customers can spin up a GPU-accelerated virtual workstation in minutes from the Azure marketplace without having to manage endpoints or back-end infrastructure.

"We’re focused on delivering the best and broadest range of GPU-accelerated capabilities in the public cloud,” said Talal Alqinawi, senior director of Microsoft Azure at Microsoft Corp. “NVIDIA Quadro vWS expands customer choice of GPU offerings on Azure to bring powerful professional workstations in the cloud to meet the needs of the most demanding applications from any device, anywhere."

Monday, January 28, 2019

NVIDIA trims guidance citing weakness in gaming and data centers

NVIDIA now estimates its Q4 revenue to be $2.20 billion compared to previous guidance of $2.70 billion. The company cited weakness in gaming and data center segments, as well as "deteriorating macroeconomic conditions, particularly in China."

In gaming, NVIDIA said there was a sequential decline due to excess mid-range channel inventory following the crypto-currency boom that proceeded as expected. However, consumer demand for NVIDIA gaming GPUs weakened faster than expected and sales of certain high-end GPUs using NVIDIA’s new Turing architecture were lower than expected. 

In the data center segment, revenue also came in short of expectations. A number of deals in the company’s forecast did not close in the last month of the quarter as customers shifted to a more cautious approach.

“Q4 was an extraordinary, unusually turbulent, and disappointing quarter,” said Jensen Huang, founder and CEO of NVIDIA. “Looking forward, we are confident in our strategies and growth drivers. The foundation of our business is strong and more evident than ever – the accelerated computing model NVIDIA pioneered is the best path forward to serve the world’s insatiable computing needs.  The markets we are creating – gaming, design, HPC, AI and autonomous vehicles – are important, growing and will be very large. We have excellent strategic positions in all of them.”

Thursday, August 16, 2018

NVIDIA posts 40% sales growth in Q2 but warns on crypto sales

NVIDIA reported revenue of $3.12 billion for its second quarter ended July 29, 2018, up 40 percent from $2.23 billion a year earlier, and down 3 percent from $3.21 billion in the previous quarter.
GAAP earnings per diluted share for the quarter were $1.76, up 91 percent from $0.92 a year ago and down 11 percent from $1.98 in the previous quarter. Non-GAAP earnings per diluted share were $1.94, up 92 percent from $1.01 a year earlier and down 5 percent from $2.05 in the previous quarter.

“Growth across every platform - AI, Gaming, Professional Visualization, self-driving cars - drove another great quarter,” said Jensen Huang, founder and CEO of NVIDIA. “Fueling our growth is the widening gap between demand for computing across every industry and the limits reached by traditional computing. Developers are jumping on the GPU-accelerated computing model that we pioneered for the boost they need.

However, Colette Kress, NVIDIA's CFO, warned that boom in sales for crypto mining applications is over. In a prepared statement on the company's investor call she said "“Our revenue outlook had anticipated cryptocurrency-specific products declining to approximately $100 million, while actual crypto-specific product revenue was $18 million.”

For its data centers category, quarterly sales amounted to $760 million, driven by demand from hyperscale customers.

Monday, August 13, 2018

Samsung supplies 16Gb GDDR6 Memory for NVIDIA Quadro

Samsung Electronics has supplied its latest 16-gigabit (Gb) Graphics Double Data Rate 6 (GDDR6) memory for NVIDIA’s new Turing architecture-based Quadro RTX™ GPUs.

Samsung's 16Gb GDDR6, which doubles the device capacity of the company’s 20-nanometer 8Gb GDDR5 memory. The new solution performs at a 14 Gbps pin speed with data transfers of 56 gigabytes per second (GB/s), which represents a 75 percent increase over 8Gb GDDR5 with its 8Gbps pin speed.

Samsung says its GDDR6 consumes 35 percent less power than that required by the leading GDDR5 graphics solutions.

"It’s a tremendous privilege to have been selected by NVIDIA to launch Samsung’s 16Gb GDDR6, and to have enjoyed the full confidence of their design team in making our key contribution to the NVIDIA Quadro RTX GPUs," said Jim Elliott, Corporate Senior Vice President at Samsung Semiconductor, Inc.

Monday, August 6, 2018

Google Cloud expands its virtual workstations with NVIDIA Tesla GPUs

Google Cloud Platform began offering virtual workstations optimized for graphics-intensive applications and machine learning inference based on the NVIDIA Tesla P4 GPU.

The new support enables users to turn any instance with one or more GPUs into a high-end workstation. P4s offer 8GB of GDDR5 memory

https://cloud.google.com/


Tuesday, May 29, 2018

Supermicro unveils 2 PetaFLOP SuperServer based on New NVIDIA HGX-2

Super Micro Computer is using the new NVIDIA HGX-2 cloud server platform to develop a 2 PetaFLOP "SuperServer" aimed at artificial intelligence (AI) and high-performance computing (HPC) applications.

"To help address the rapidly expanding size of AI models that sometimes require weeks to train, Supermicro is developing cloud servers based on the HGX-2 platform that will deliver more than double the performance," said Charles Liang, president and CEO of Supermicro. "The HGX-2 system will enable efficient training of complex models. It combines 16 Tesla V100 32GB SXM3 GPUs connected via NVLink and NVSwitch to work as a unified 2 PetaFlop accelerator with half a terabyte of aggregate memory to deliver unmatched compute power."

The design packs over 80,000 CUDA cores.