Acquisition Datacenter Newss

Nvidia acquires Israeli networking firm Mellanox for $6.9B

Nvidia is acquiring the Israel-based networking firm Mellanox for around $6.9 billion in cash.

Mellanox is a prominent supplier of end-to-end Ethernet and InfiniBand smart interconnect solutions and services for servers and storage. These solutions help companies to boost datacenter efficiency by optimizing throughput and latency, providing data faster to applications, and unlocking system performance capability.

Nvidia is a leading company in the world in high-performance computing (HPC), whereas Mellanox is an early innovator in high-performance interconnect technology. The acquisition will combine the expertise of Nvidia and Mellanox.

“The emergence of AI and data science, as well as billions of simultaneous computer users, is fueling skyrocketing demand on the world’s datacenters. 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,” said Jensen Huang, founder and CEO of NVIDIA.

More than half of the world’s Top 500 supercomputers and leading hyperscale datacenters are using Nvidia’s computing platform and Mellanox’s interconnects technology.

With the acquisition of Mellanox, Nvidia will optimize datacenter-scale workloads across the entire computing, networking and storage stack, the companies said. This will help customers to achieve higher performance, greater utilization and lower operating cost.

“We’re excited to unite NVIDIA’s accelerated computing platform with Mellanox’s world-renowned accelerated networking platform under one roof to create next-generation datacenter-scale computing solutions. I am particularly thrilled to work closely with the visionary leaders of Mellanox and their amazing people to invent the computers of tomorrow,” added Jensen Huang.

Nvidia and Mellanox have been working closely for a while now. They jointly contributed in the development of world’s two fastest supercomputers—Sierra and Summit.

Following the completion of acquisition, Nvidia will continue to invest in local excellence and talent in Israel. No changes will be made to customer sales and support.

Also read: NetApp and Nvidia join forces to help businesses accelerate journey into AI revolution

“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.”

Image source: Nvidia

Cloud Cloud News Datacenter Newss

Nvidia pairs its GPUs with Kubernetes to accelerate data-intensive workloads

With graphics processing units (GPUs) gaining more ground in datacenter world to speed up the data-intensive workloads, Nvidia is pairing its GPUs with Kubernetes clusters. The company has made its release candidate Kubernetes on Nvidia GPUs freely available to developers.

Being the largest GPU maker in the world, Nvidia aims to help enterprises seamlessly train deep learning models on multi-cloud GPU clusters.

Announced at the Computer Vision and Pattern Recognition (CVPR) conference, the Kubernetes on Nvidia GPUs can automate the deployment, maintenance, scheduling and operation of containers across clusters of nodes.

“With increasing number of AI powered applications and services and the broad availability of GPUs in public cloud, there is a need for open-source Kubernetes to be GPU-aware,” wrote Nvidia in the announcement post. “With Kubernetes on NVIDIA GPUs, software developers and DevOps engineers can build and deploy GPU-accelerated deep learning training or inference applications to heterogeneous GPU clusters at scale, seamlessly.”

The new offering will be tested, validated and maintained by Nvidia. The GPU maker said that it can orchestrate resources on heterogeneous GPU clusters, and optimize the utilization of GPU clusters with active health monitoring.

Kubernetes on Nvidia GPUs is now freely available to developers for testing.

At the CVPR 2018, Nvidia also announced the latest version of its TensorRT runtime engine— TensorRT 4, to include new recurrent neural network layers for Neural Machine Translation apps, and new multilayer perception operations and optimizations for Recommender Systems. It has now been integrated with TensorFlow.

The company made available new libraries (Nvidia DALI and Nvidia nvJPEG) for data augmentation and images decoding.

“With DALI, deep learning researchers can scale training performance on image classification models such as ResNet-50 with MXNet,TensorFlow , and PyTorch across Amazon Web Services P3 8 GPU instances or DGX-1 systems with Volta GPUs,” wrote Nvidia.

Nvidia DALI is open-source and is now available on GitHub.

Cloud News News

Nvidia, IBM release security patches to mitigate Meltdown and Spectre. Intel customers looking for substitutes 

Nvidia is latest in the list to provide security updates to mitigate the impact of Meltdown and Spectre. Though Nvidia claimed that their core business is GPU computing, and Nvidia GPUs are safe from the malicious actors.

At Consumer Electronics Show (CES) 2018 in Las Vegas, Nvidia CEO Jensen Huang illustrated how the technology leaders are scrambling to find patches to the Spectre and Meltdown attacks. These attacks enable the hackers to steal private information of users from the CPUs having processors from Intel, AMD, and ARM.

“We believe our GPU hardware is immune to the reported security issue. As for our driver software, we are providing updates to help mitigate the CPU security issue,” Nvidia wrote in their security bulletin.

So, Nvidia has released updates for its software drivers that interact with vulnerable CPUs and operating systems.

The vulnerabilities take place in three variants- Variant 1, Variant 2, and Variant 3. Nvidia has released driver updates for Variant 1 and Variant 2. The company said none of its software is vulnerable to Variant 3.

Nvidia has provided security updates for these products- GeForce, Quadro, NVS Driver Software, Tesla Driver Software, and GRID Driver Software.

IBM had made no comments whether their systems were affected or not by these attacks. But Red Hat last week reported that IBM’s System Z, and POWER platforms are exploited by Spectre and Meltdown.

To that, IBM responded and released firmware patches for Power7+ and Power8 platforms. Patches for Power9 processors will be available by January 15, while AIX and IBM i operating system patches will be available by February 12.

The tech giants are issuing security updates to fix Spectre and Meltdown, but these security updates are reportedly impacting the performance of computers and servers.

Intel’s 8th Generation Core platforms with solid state storage are still seeing performance impact of around 6%. This seems to have upset the customers, and they are looking for substitutes to Intel chips.

The substitutes can be AMD (Advanced Micro Devices) which works with Intel for x86 processors. The companies like Backblaze, the data storage provider, have already indicated that building with AMD won’t be difficult.

Rubbing salt in Intel’s wound, the CEO of leading cloud computing provider Infinity Virtual, said in an interview that if Intel doesn’t make things right, his company will no longer purchase their products.

Also read: Intel creates new cybersecurity group addressing Meltdown and Spectre attacks

“If ARM provides enough computing power at lower cost or lower power than x86, it would be a strong incentive for us to switch,” said Gleb Budman, CEO, Backblaze. “If the fix for x86 results in a dramatically decreased level of performance, that might increasingly push in favor of switching to ARM.”

Datacenter News

Nvidia prohibits datacenter deployment of GeForce GPUs 

Nvidia recently made a big change to the licensing agreement of its GeForce software which doesn’t allow users to deploy GeForce GPUs and Titan GPUs in data centers. Certainly, the users aren’t happy about it. 

Graphical User Interfaces (GPUs), being a common choice for artificial intelligence researchers, has helped Nvidia to surge 85% in its stock price in 2017.  

The customers aren’t happy about the changes to End-User Licensing Agreement (EULA) because it doesn’t allow them to deploy the GeForce and Titan based graphic cards in the data centers provided by other service providers including Amazon Web Services and Microsoft Azure.  

Here is the statement from the EULA- “No Datacenter Deployment. The SOFTWARE is not licensed for datacenter deployment, except that blockchain processing in a datacenter is permitted.” 

The changes are forcing users to go for expensive Tesla GPUs inside data centers, instead of lower-cost processors. The new Tesla V100 costs around $8000 while the Titan V starts at only $3000. 

To defend itself, Nvidia said that it made changes to EULA to prevent the potential misuse of its GeForce and Titan GPUs which were not built for demanding, and large-scale enterprise environments.  

“NVIDIA addresses the unique mechanical, physical, management, functional, reliability, and availability needs of servers with our Tesla products, which include a three-year warranty covering data center workloads, NVIDIA enterprise support, guaranteed continuity of supply and extended SKU life expectancy for data center components. This has been communicated to the market since the Tesla products were first released,” said Nvidia in statement to CNBC. 

Also read: Nvidia is ending driver support for 32-bit operating systems 

With this change in EULA, many leading companies using GeForce were affected, but Nvidia looks unmoved, and doesn’t seem to change its policy any sooner.  



Nvidia is ending driver support for 32-bit operating systems 

With the 64-bit systems becoming norm, Nvidia announced that it will no longer release graphics card drivers for 32-bit operating systems after the Version 390.

The Version 390 will be the last one to support 32-bit systems, and will impact Windows (7, 8, 8.1, and 10), Linux and FreeBSD.

There are some organizations and folks who still work with legacy hardware. They must now know that they won’t be able to operate or install the later versions of Nvidia drivers on their 32-bit operating systems. The drivers and chipsets with 32-bit systems will still work but they won’t get any updates regarding bugs, security, etc.

Driver enhancements, driver optimizations, and operating system features in driver versions after Release 390 will not be incorporated back into Release 390 or earlier versions,” Nvidia stated.


The users running 32-bit systems on Windows, Linux and FreeBSD, and relying on Nvidia graphics cards, better upgrade to 64-bit operating systems. The 64- bit systems not only provide better compatibility with latest hardware and software, but also it is more secure and protects from viruses and malware.

32-bit systems are less secure and can be impacted by malware. For reference, the WannaCry ransomware that crippled the banks, hospitals and other businesses across 150 countries globally.

Now is the time to upgrade to 64-bit versions, and if you need more reasons for it, Intel has planned to drop BIOS (Basic input/output System) compatibility from firmware by 2020, which will not allow users to boot 16-bit and almost all 32-bit systems on modern hardware.

Also read: Sensitive information of 123 million American households exposed online in Alteryx data breach

Version 390 will be available in early January 2017, and Nvidia will address critical bug and security issues for 32-bit systems for one more year, until December 2019.


Dell EMC’s new Machine and Deep Learning solutions to bring power of HPC and data analytics to enterprises

Dell EMC at SuperComputing conference 2017, announced its new machine learning and deep learning solutions to bring the power of HPC (high performance computing) and data analytics to the mainstream enterprises.

The new solutions combine HPC and data analytics to empower enterprises with opportunities in image processing, fraud detection, financial investment analysis and other similar areas through ready bundles for easier deployment.

Artificial Intelligence techniques like machine and deep learning have been increasingly deployed and used by enterprises but not many have the required skill set and expertise to manage such systems effectively. Here, Dell EMC’s new solutions built around its expertise in HPC and data analytics, offer customers the ability to leverage maximum insights from their collected data for faster and better performances.

Our customers consistently tell us that one of their biggest challenges is how to best manage and learn from the ever-increasing amount of data they collect daily. With Dell EMC’s high-performance computing experience, we’ve seen how our artificial intelligence solutions can deliver critical insights from this data, faster than ever before possible. Working with our strategic technology partners, we’re able to bring these powerful capabilities to all enterprises. When you think about what this means for industries like financial services or personalized medicine, the possibilities are endless and exciting.Armughan Ahmad, senior vice president/general manager, Hybrid Cloud and Ready Solutions, Dell EMC.

The new solution bring together optimized pre-tested and validated servers, storage and networking for machine and deep learning applications. Simplified identification, analysis and automation of data patterns will help customers use data insights in a variety of applications from facial recognition in security to studying human behavior in retail industry.

Customers will also be benefitting from the introduction of new Dell EMC PowerEdge C4140 server – supporting NVIDIA latest generation technology.

The Dell EMC Ready Bundles will be available in the first innings of 2018 via Dell EMC and its efficient channel partners, while Dell EMC PowerEdge C4140 will be available by December 2017.

With AI going mainstream, technology vendors like IBM, HPE and Dell EMC are pushing their services to be HPC and AI capable, and help developers and enterprises deploy HPC applications. While, HPE has been a leading name in HPC and supercomputing for years, other vendors are also increasing their efforts in the realm. This include IBM integrating its deep learning PowerAI enterprise software with its Data Science Experience.