Nimbix Blog

Super musing about all things supercomputing

Nimbix Ushers in Next-Generation GPUs for Cloud-Based Deep Learning

Enterprises and developers now have access to the most powerful GPU systems available in the Nimbix Cloud

Nimbix, a leading public cloud provider for supercomputing-class workloads, deep learning and AI, announced today the immediate availability of high-performance NVIDIA® Pascal™ GPUs using the NVIDIA DGX-1™ AI supercomputer in the Nimbix Cloud. For an on-demand rate, customers gain access to the industry-leading native bandwidth of eight NVIDIA NVLink™ interconnected NVIDIA Tesla® P100 GPUs to launch or develop state-of the-art machine learning workflows, accelerated analytics and a host of other GPU-powered applications.

The Nimbix Cloud offers the most diverse set of GPU-powered machines available from a public cloud provider, spanning the NVIDIA portfolio and supporting configurations for both Intel x86 and IBM Power8 processors to deliver the best performance and economics available for both enterprises and developers. Nimbix Cloud machines are interconnected with industry-leading 56Gbps FDR and 100Gbps EDR Infiniband for optimal GPU cluster performance.

“Nimbix has tremendous experience in GPU cloud computing, going all the way back to NVIDIA’s Fermi architecture,” said Steve Hebert, CEO of Nimbix. “We are looking forward to accelerating deep learning and analytics applications for customers seeking the latest generation GPU technology available in a public cloud.”

“Combining the optimized performance of NVIDIA DGX-1 with Nimbix’s cloud platform provides customers a flexible option to run their most challenging deep learning and AI workloads in an easy to use cloud system,” said Charlie Doyle, senior director for DGX-1, NVIDIA.

Tweet this: .@Nimbix Ushers in Next-Gen GPUs via @NVIDIAAI DGX-1 on the Nimbix #Cloud https://www.nimbix.net/nvidia-dgx-1

In addition to the rich catalog of DGX turn-key workflows for deep learning, developers can use the PushToCompute™ feature of the JARVICE platform to import the latest versions of their custom applications into the Nimbix Cloud and make them available for consumption at scale immediately. Each application, along with its dependencies, executes in JARVICE’s container runtime environment, which provides superior performance and scale. This includes sub-second launch times, faster execution, seamless access to supercomputing GPUs, automated heterogeneous data management, and rapid workflow deployment across multiple compute nodes either in a parallel or distributed paradigm. PushToCompute™ also facilitates continuous integration and continuous deployment (CI/CD) for the entire life cycles of containerized applications.

About Nimbix

Nimbix is the leading provider of purpose-built cloud computing for machine learning, AI and HPC applications. Powered by JARVICE™, the Nimbix Cloud provides high-performance software as a service, dramatically speeding up data processing for Energy, Life Sciences, Manufacturing, Media and Analytics applications. Nimbix delivers unique accelerated high-performance systems and applications from its world-class data centers as a pay-per-use service.

Media Contact
Alicia Hagan
Nimbix, Inc.
alicia.hagan@nimbix.net

Kinetica and Nimbix Team Up to Offer GPU Computing in the Cloud for Enterprise Customers

No special skills needed to leverage advanced analytics from GPUs in the cloud

kinetica logoSAN FRANCISCO, Calif., – MARCH 6 – Kinetica, provider of the fastest, in-memory database accelerated by GPUs, today announced its real-time analytics and visualization solution is immediately available on the Nimbix Cloud. Launched in seconds and ready to ingest data capable of delivering the highest performance from a public cloud provider on state-of-the-art infrastructure, Kinetica is the ideal solution for mission-critical enterprises, providing instant results and visualized insights across massive streaming datasets.

“Kinetica on the Nimbix Cloud harnesses the power of parallel GPUs to deliver real-time analytics and data written to Kinetica is automatically routed to parallel connections across the cluster,” said Amit Vij, cofounder and CEO, Kinetica. “The full Kinetica stack can be provisioned with a couple of mouse clicks from the Nimbix console or launched and automated with JARVICE’s powerful task API.”

“Kinetica’s GPU accelerated database platform paired with Nimbix’s Cloud is a natural fit for customers looking for industry-leading performance and ease-of-use from a cloud deployment,” said Steve Hebert, CEO, Nimbix. “With a few mouse clicks, customers can have unprecedented computing capabilities to help them solve some of their biggest data analytics challenges.”

The Nimbix Cloud offers customer selectable systems with either Intel x86 based processors or IBM POWERower8 Processors both coupled with NVIDIA GPUs to deliver the best performance and economics available for Kinetica customers. Nimbix is the only public cloud provider featuring NVIDIA’s latest generation Pascal Tesla P100 GPUs with NVLink, a high-bandwidth, energy-efficient interconnect that allows data sharing at rates 5 to 12 times faster than the traditional PCIe interconnects. Nimbix Cloud machines are interconnected with industry leading 56Gbps FDR Infiniband for optimal GPU Cluster performance.

“The IBM POWER8 NVLink server is ideally suited for databases and advanced analytic applications because the NVLink super-highway between the POWER8 CPU and the NVIDIA Tesla P100 Pascal GPU accelerator enables data to up to move 2.5x higher throughput from the system memory to the accelerator,” said Sumit Gupta, IBM vice president of High Performance Computing, AI and Analytics. “The availability of Kinetica running on these POWER8 NVLink servers in the Nimbix cloud enables enterprises to quickly try the real-time analytics of the Kinetica accelerated database.”

To learn more about how IBM, Kinetica, and Nimbix can help you take advantage of GPU acceleration for real-time analytics, please join our webinar “Democratizing High Performance Data Science in the Cloud” on March 21, 10am PST. Register here.

Download the Kinetica on Nimbix Solution Brief.

Tweet this: .@Kinetica GPU-accelerated database now available on the @Nimbix #Cloud https://wp.me/p76dAH-1j5

About Kinetica
Kinetica addresses today’s data paradigm by bringing Graphics Processing Units (GPUs) to the datacenter. Built from the ground up to scale linearly, Kinetica’s distributed, in-memory database accelerated by GPUs delivers truly real-time actionable intelligence on large, complex and streaming data sets: 100x faster performance at 1/10 of the hardware of traditional databases. Kinetica makes real time a reality. Organizations use Kinetica to simultaneously ingest, explore, analyze and visualize streaming data within milliseconds to make critical decisions and find efficiencies, lower cost, generate new revenue, and improve customer experience. Learn more at kinetica.com.

About Nimbix
Nimbix is the leading provider of purpose-built cloud computing for big data and computation. Powered by JARVICE™, the Nimbix Cloud provides high-performance software as a service, dramatically speeding up data processing for Energy, Life Sciences, Manufacturing, Media and Analytics applications. Nimbix delivers unique accelerated high-performance systems and applications from its world-class datacenters as a pay-per-use service.

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Nimbix Unveils Expanded Cloud Product Strategy for Enterprises and Developers

MaterialCompute™ will set a new standard for ease of use and accessibility of high-end computing services

RICHARDSON, Texas Jan. 18, 2017 — Nimbix, a leading provider of high-performance and cloud supercomputing services, announced today its new combined product strategy for enterprise computing, end users, and developers.  This new strategy will focus on three key capabilities – JARVICE™ Compute for high-performance processing, including Machine Learning, AI and HPC workloads; PushToCompute™ for application developers creating and monetizing high performance workflows; and MaterialCompute™, a brand new intuitive user interface, featuring the industry’s largest high performance application marketplace available from a cloud provider.

Nimbix’s JARVICE™ platform powers the Nimbix Cloud and is capable of processing massively parallel turnkey workflows ranging from enterprise simulation to machine learning and serving all major industries and organizations.  Unlike other cloud providers who leverage virtualization technology to provide slices of a physical machine to users, JARVICE™ delivers high-performance computation on bare-metal supercomputing systems using Nimbix’s patented Reconfigurable Cloud Computing technology and fully containerized application components for agility and security.  JARVICE™ powers the Nimbix Cloud and is also available as a product for both hosted and on-premises private cloud deployments.

PushToCompute™, released in September of 2016, is the fastest, easiest way for developers to onboard commercial or open source compute-intensive applications into the cloud.  Using the industry standard Docker format, PushToCompute™ seamlessly interfaces with major third party registries such as Docker Hub, Google Container Registry, and others, as well as private registries.  PushToCompute™ is available as a subscription service and will expand to include build capabilities for both x86 and POWER architectures in the first half of 2017.  With these new capabilities, PushToCompute™ will offer end to end continuous integration as well as continuous delivery services for developers of compute intensive workflows such as machine learning and other complex algorithms.  Once deployed, these workflows can be made available in the public marketplace for monetization in an on-demand fashion.

MaterialCompute™, Nimbix’s newest offering, sets a new standard for ease of use and accessibility of high-end computing services.  MaterialCompute™ aims to reduce clicks, improve flows, and optimize display on both desktop and mobile devices.  With MaterialCompute™, users choose applications and workflows from the marketplace and execute these on the Nimbix Cloud at any scale, from any network, on any device, and leveraging any advanced computing technologies such as the latest GPUs from NVIDIA and FPGAs from Xilinx.   Developers can also leverage MaterialCompute™ to create and manage applications, and interface seamlessly to PushToCompute™ mechanisms.

“Delivering optimized technology capabilities to different communities is key to a successful public cloud offering,” said Nimbix Chief Technology Officer Leo Reiter.  “With this unified approach, Nimbix delivers discrete product capabilities to different audiences while maximizing value to all parties with the underlying power of the JARVICE™ platform.”

JARVICE™ and PushToCompute™ are available with both on-demand and subscription pricing.  MaterialCompute™ will be available for public access in February 2017 and will serve as the primary front-end for all Nimbix Cloud services.

About Nimbix
Nimbix is the leading provider of purpose-built cloud computing for big data and computation. Powered by JARVICE™, the Nimbix Cloud provides high-performance software as a service, dramatically speeding up data processing for Energy, Life Sciences, Manufacturing, Media and Analytics applications. Nimbix delivers unique accelerated high-performance systems and applications from its world-class datacenters as a pay-per-use service. Additional information about Nimbix is included in the company overview, which is available on the Nimbix website at https://www.nimbix.net.

How Big Compute Helps Genomics

Big Compute HPC applicationsModern science involves sorting through mountains of data, and nowhere is this truer than in the study of genes. Modern computers have enough power to make sequencing an organism’s genome fairly easy, but that wasn’t always the case. The best way to see the difference computing power can make is to look at the Human Genome Project.

The Human Genome Project

The Human Genome Project had a simple goal. The scientists wanted to sequence every euchromatic gene in the human genome, a process that involved analyzing more than three billion base pairs of nucleotides. The scientists hoped to do it within fifteen years, but technological developments allowed them to pull it off in only thirteen.

Gene sequencing relies on a process that breaks DNA into relatively small sections. It’s possible to use chemical markers to identify the individual base pairs in a small sequence, but large sequences are impossible because it’s impossible to tell where each marker landed. Once the researchers have figured out each small sequence, they can find overlapping sections and use that information to reconstruct the entire chain.

When the project started, researchers had to do that by hand. They quickly developed programs that could automate it, but their core method was still fairly slow. Researchers realized that they were unlikely to finish within fifteen years, which brought the Celera Corporation into the picture. Celera used new programs that could handle huge sections of DNA by matching the ends of long sequences instead of looking for overlap in a variety of small sections.

That method required a lot of computing power. Celera needed a computer with about 700 linked processors to run their program, but it was enough to finish the project in nine months. A weaker computer would have taken much longer, and modern computers can do it much faster. The most powerful modern systems can sequence an individual’s genome in merely 26 hours!

How Nimbix Helps

That sort of feat requires a massive amount of computing power, but modern services such as Nimbix are making it more common. Nimbix is a cloud computing system designed to provide that power and turnkey access to important tools. Our cloud platform makes it easy to work through complex technical problems, which has the potential to make genomics even easier in the future.


bioinformatics applications nimbix

Nimbix offers turnkey bioinformatics workflows that don’t require IT skills to set up.   Our cloud is optimized for bioinformatics processing tasks such as gene sequencing.  Results can be up to 15 times faster than other cloud solutions. One popular example is to use SMRT Portal from Pacific Biosciences, a browser-based application on the Nimbix Cloud to create, submit and monitor secondary analysis jobs as well as view and download the results. With this tool, you can align reads to a reference sequence or assemble reads into a de novo genome.  You can also create interactive visualizations of assembly graphs with Bandage (a Bioinformatics Application for Navigating De novo Assembly Graphs Easily).

Getting started on the Nimbix Cloud is easy.  Click here to create your free account then view and choose from our library of applications that will help you visualize and conduct your research.

Trends in the AI Revolution from 2016

Artificial Intelligence TrendsThe AI Revolution is in full swing.  We are lucky to see a lot of activity in the AI Revolution first-hand as the premier cloud provider for accelerated computational resources. 2016 has been an incredible year for machine learning. We have seen powerful frameworks continue to mature. The next generation of GPUs, crafted and designed by NVIDIA for the purpose of accelerating deep learning pipelines, have been released and are available publicly in the cloud. And the quantity of data continues to explode far beyond the capabilities of our incredible computing resources of today.  Machine learning and deep learning were also among some of the hottest topics at Supercomputing 2016.

The three biggest AI trends that we have seen are:

1. Frameworks

The top frameworks are maturing rapidly. Caffe, Torch, and Tensorflow are the three most popular frameworks that we have seen in both academia and industry. Our users have built everything from simple on-demand web services using the JARVICE API to entire businesses based around these powerful machine learning frameworks. Tensorflow’s architecture departs from the traditional deep learning mold and provides really powerful mechanisms for different types of training and inference architectures.  These three frameworks are on the verge of being able to support distributed GPU computations out of the box, and this should drive some powerful innovation in 2017 by being able to leverage technologies such as NVLink and Infiniband RDMA.

2. Accelerators

GPUs and accelerators such as FPGAs are ushering in massively parallel computational capabilities. In 2016, NVIDIA released its new Pascal architecture GPUs, the NVIDIA Tesla P100s. Nimbix has IBM Power8 machines with 4 x P100s available on-demand connected with NVLink for inter-GPU communication, and FDR Infiniband for distributed communication across machines. Our library of on-demand, turn-key applications for Minsky+NVIDIA P100s includes Power AI and NVIDIA DIGITS, and custom applications can be deployed with a simple git push to Github. The NVIDIA P100s are optimized for convolutional neural networks and matrix multiplication with better throughput and memory performance than ever before. 2017 will have a lot of exciting development in hardware acceleration. Much like Google’s Tensorflow Processing Unit (TPU), which is a CPLD, specialized FPGAs in the cloud make it possible to iterate faster than ever by designing specialized logic to accelerate challenging deep learning problems.

3. Massive Data

Data sets are continuing to grow, and almost every industry wants a bite of the AI Revolution apple. As any newcomer to this space will quickly learn, data has mass and moving it around can easily be the bottleneck of your algorithm. New architectures are being envisioned to address this in innovative ways. As the world becomes more connected with IoT sensors of all shapes and sizes, real-time data processing architectures will continue to grow to process and respond to this data more effectively. Machine learning experts will focus on developing algorithms to train more effectively on less data while computational capabilities continue to improve.

We can’t wait to see the innovations in machine learning, deep learning, and artificial intelligence in 2017. What trends have you noticed in AI and machine learning throughout 2016 and what are your predictions for 2017? Tweet us @nimbix!

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