DDN, Nvidia Blueprint Unified AI Appliance with Up to 9 DGX-1s

By Tiffany Trader

October 4, 2018

Continuing the roll-out of the A3I (Accelerated, Any-Scale AI) storage strategy kicked off in June, DDN today announced a new set of solutions that combine the A3I platform with Nvidia DGX-1 AI servers in a validated, pre-configured solution available from a number of channel partners.

In a first for the company, DDN is launching a reference architecture that combines DGX-1 8-way V100 GPU boxes with DDN’s Lustre-based parallel file storage systems in a rack-level solution, designed to provide an entire AI environment out of the box.

Available today through a number of resellers are three reference architectures, starting as small as a single DGX-1 with a single storage box and scaling up to what Nvidia is calling a DGX-1 Pod with 9 DGX-1s plus the recommended storage systems. The storage options are the same ones that DDN announced when it rolled out A3I back in June: AI200 and the AI7990.

The all-flash AI200 appliance delivers 20GB/s of filesystem throughput, over 1 million IOPS and 360 terabytes of dual ported NVMe flash in a 2U enclosure. It can scale horizontally as a single namespace, and can integrate with hard disk tiers to help economically manage growing data volumes.

DDN claims that with AI200, Caffe applications running on a DGX-1 server demonstrate 2.4X increased image throughput and complete twice as fast (compared to “other storage products”). Company testing also showed 2X shorter runtimes for TensorFlow training applications and a doubling of image throughput. The parallel architecture is said to maintain linear performance for applications that leverage distributed computing on multiple DGX-1 servers, such as Horovod.

For customers that need to prioritize capacity, DDN also offers a larger hybrid storage system, the AI7990, which integrates flash and spinning disk, touting up to 600 terabytes of SSD in a 4U form factor. The AI7990 storage platform offers up to 20GB/s of filesystem throughput and over 1 million IOPS as a single namespace.

Both storage systems will connect to the DGX-1 server with EDR InfiniBand or 100 Gbps Ethernet.

Kurt Kuckein, senior director for DDN marketing, interviewed by HPCwire ahead of the launch, said the major goal with these reference architectures is to make AI as easy as possible.

“What we are hearing from our customers, and this is echoed by Nvidia, is that many of the customers don’t fundamentally know where to start when it comes to deployment infrastructure. They may have an AI initiative, they may have hired a couple of very expensive scientists, but when it comes to the infrastructure piece, they are struggling to figure out the right servers, the OS, the environment and storage system to support it,” he said. “Alternately we also have quite a few customers who have had some initial success putting together their own servers with perhaps Nvidia GPUs and some kind of storage system on the back-end maybe leveraging existing enterprise storage or building their own Ceph-like storage system and now that they are successful, they’re trying to scale their project and they just can’t do it. They’re spending more time engineering a solution and rearchitectuing a solution to be able to meet their scaling needs than they are finding the algorithm or growing their business that way. And so the design of this solution is really to slot easily into the datacenter and be scalable over time so that as projects are successful our systems can scale just along with the needs of the customers.”

DDN’s play with Nvidia is a little different than some of the Nvidia+X partnerships we’ve seen in the past year, notably from Pure and NetApp.

“Most of the competition is generally leveraging NFS and we are leveraging a parallel file system that’s really designed to deliver the high throughput and low latency requirements that a GPU-intensive environment has,” said Kuckein. “And what you get into especially at scale is problems where the GPUs are not being fully saturated and so with NFS generally you are going to have peaks and valleys during read operation because of the nature of the NFS protocol versus a parallel file system, which is going to keep the GPUs fully saturated because we are maximizing the internal architecture of the DGX-1. We are taking advantage of the design of the DGX-1 which is designed around an RDMA network and we are connecting to that network rather than leveraging a more traditional enterprise-oriented network.”

DDN also states that its A3I products have been rigorously tested and integrated around a set of widely-used deep learning frameworks, including TensorFlow, Horovod, Torch, PyTorch, Nvidia TensorRT, Caffe, Caffe2, CNTK, MXNET and Theano.

A real-world example of deep learning in action comes from a DDN customer, autonomous retail specialists Standard Cognition. They have a store with multiple cameras that use AI software to identify the items shoppers have selected for purchase, such that the shopper can just grab something off the shelf and walk out with automatic detection of payment. Standard Cognition does all processing locally, in the interest of real time performance and customer privacy.

A number of other use cases are expected across the enterprise, from retail to oil and gas to healthcare. A popular deployment example is the hub-and-spoke model, where customers have a remote field need for data acquisition as well as inference so they need to do things in real-time in the field but then they send that data from the field back to an aggregated central system, which makes optimizations for the device in the field. This hub and spoke model could use the smaller form factor AI200 for real-time analysis within the local retail outlet itself and then the larger capacity AI7990 in their centralized system to further refine their model based on aggregated data collected from multiple locations.

It’s interesting that DDN, while it has a 20-year history of deploying successful solutions with OEM vendors like HPE and Dell, has never worked with a server maker and channel partners to develop a reference architecture like this, and it’s really a sign of the times when end users with AI workloads require HPC with an “easy button.”

The approach got a nod from Steve Conway, senior research vice president, Hyperion Research, who said, “the powerful trend toward AI and other high-performance data analytics workloads is driving the need for storage and compute systems that deliver simplified scale and extremely fast data rates.” He further added, “DDN A3I with Nvidia DGX-1 is an impressive effort to meet the demanding workload requirements of data scientists across AI and deep learning environments.”

The DDN A3I with Nvidia DGX-1 solutions are available today through U.S. value-added resellers Microway, Meadowgate Technologies and Groupware Technology. Other authorized partners include Penguin Computing, World Wide Technology, and ePlus, in the U.S., and GDEP Solutions, XENON and E4 Computer Engineering, in select international regions. All channel partners are certified to deliver and support the rack-level solution.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Data West Brings Technology Leaders to SDSC

December 6, 2018

Data and technology enthusiasts from around the world descended upon the San Diego Supercomputing Center (SDSC) for the third annual Data West conference, which is taking place this week on the campus of the University o Read more…

By Alex Woodie

Topology Can Help Us Find Patterns in Weather

December 6, 2018

Topology--–the study of shapes-- seems to be all the rage. You could even say that data has shape, and shape matters. Shapes are comfortable and familiar concepts, so it is intriguing to see that many applications are Read more…

By James Reinders

What’s New in HPC Research: Automatic Energy Efficiency, DNA Data Analysis, Post-Exascale & More

December 6, 2018

In this bimonthly feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From exascale to quantum computing, the details are here. Read more…

By Oliver Peckham

HPE Extreme Performance Solutions

AI Can Be Scary. But Choosing the Wrong Partners Can Be Mortifying!

As you continue to dive deeper into AI, you will discover it is more than just deep learning. AI is an extremely complex set of machine learning, deep learning, reinforcement, and analytics algorithms with varying compute, storage, memory, and communications needs. Read more…

IBM Accelerated Insights

Five Steps to Building a Data Strategy for AI

Our data-centric world is driving many organizations to apply advanced analytics that use artificial intelligence (AI). AI provides intelligent answers to challenging business questions. AI also enables highly personalized user experiences, built when data scientists and analysts learn new information from data that would otherwise go undetected using traditional analytics methods. Read more…

Zettascale by 2035? China Thinks So

December 6, 2018

Exascale machines (of at least a 1 exaflops peak) are anticipated to arrive by around 2020, a few years behind original predictions; and given extreme-scale performance challenges are not getting any easier, it makes sense that researchers are already looking ahead to the next big 1,000x performance goal post: zettascale computing. Read more…

By Tiffany Trader

Topology Can Help Us Find Patterns in Weather

December 6, 2018

Topology--–the study of shapes-- seems to be all the rage. You could even say that data has shape, and shape matters. Shapes are comfortable and familiar conc Read more…

By James Reinders

Zettascale by 2035? China Thinks So

December 6, 2018

Exascale machines (of at least a 1 exaflops peak) are anticipated to arrive by around 2020, a few years behind original predictions; and given extreme-scale performance challenges are not getting any easier, it makes sense that researchers are already looking ahead to the next big 1,000x performance goal post: zettascale computing. Read more…

By Tiffany Trader

Robust Quantum Computers Still a Decade Away, Says Nat’l Academies Report

December 5, 2018

The National Academies of Science, Engineering, and Medicine yesterday released a report – Quantum Computing: Progress and Prospects – whose optimism about Read more…

By John Russell

Revisiting the 2008 Exascale Computing Study at SC18

November 29, 2018

A report published a decade ago conveyed the results of a study aimed at determining if it were possible to achieve 1000X the computational power of the the Read more…

By Scott Gibson

AWS Debuts Lustre as a Service, Accelerates Data Transfer

November 28, 2018

From the Amazon re:Invent main stage in Las Vegas today, Amazon Web Services CEO Andy Jassy introduced Amazon FSx for Lustre, citing a growing body of applicati Read more…

By Tiffany Trader

AWS Launches First Arm Cloud Instances

November 28, 2018

AWS, a macrocosm of the emerging high-performance technology landscape, wants to be everywhere you want to be and offer everything you want to use (or at least Read more…

By Doug Black

Move Over Lustre & Spectrum Scale – Here Comes BeeGFS?

November 26, 2018

Is BeeGFS – the parallel file system with European roots – on a path to compete with Lustre and Spectrum Scale worldwide in HPC environments? Frank Herold Read more…

By John Russell

DOE Under Secretary for Science Paul Dabbar Interviewed at SC18

November 21, 2018

During the 30th annual SC conference in Dallas last week, SC18 hosted U.S. Department of Energy Under Secretary for Science Paul M. Dabbar. In attendance Nov. 13-14, Dabbar delivered remarks at the Top500 panel, met with a number of industry stakeholders and toured the show floor. He also met with HPCwire for an interview, where we discussed the role of the DOE in advancing leadership computing. Read more…

By Tiffany Trader

Quantum Computing Will Never Work

November 27, 2018

Amid the gush of money and enthusiastic predictions being thrown at quantum computing comes a proposed cold shower in the form of an essay by physicist Mikhail Read more…

By John Russell

Cray Unveils Shasta, Lands NERSC-9 Contract

October 30, 2018

Cray revealed today the details of its next-gen supercomputing architecture, Shasta, selected to be the next flagship system at NERSC. We've known of the code-name "Shasta" since the Argonne slice of the CORAL project was announced in 2015 and although the details of that plan have changed considerably, Cray didn't slow down its timeline for Shasta. Read more…

By Tiffany Trader

IBM at Hot Chips: What’s Next for Power

August 23, 2018

With processor, memory and networking technologies all racing to fill in for an ailing Moore’s law, the era of the heterogeneous datacenter is well underway, Read more…

By Tiffany Trader

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

CERN Project Sees Orders-of-Magnitude Speedup with AI Approach

August 14, 2018

An award-winning effort at CERN has demonstrated potential to significantly change how the physics based modeling and simulation communities view machine learni Read more…

By Rob Farber

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Read more…

By John Russell

AMD Sets Up for Epyc Epoch

November 16, 2018

It’s been a good two weeks, AMD’s Gary Silcott and Andy Parma told me on the last day of SC18 in Dallas at the restaurant where we met to discuss their show news and recent successes. Heck, it’s been a good year. Read more…

By Tiffany Trader

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

Leading Solution Providers

SC 18 Virtual Booth Video Tour

Advania @ SC18 AMD @ SC18
ASRock Rack @ SC18
DDN Storage @ SC18
HPE @ SC18
IBM @ SC18
Lenovo @ SC18 Mellanox Technologies @ SC18
One Stop Systems @ SC18
Oracle @ SC18 Panasas @ SC18
Supermicro @ SC18 SUSE @ SC18 TYAN @ SC18
Verne Global @ SC18

TACC’s ‘Frontera’ Supercomputer Expands Horizon for Extreme-Scale Science

August 29, 2018

The National Science Foundation and the Texas Advanced Computing Center announced today that a new system, called Frontera, will overtake Stampede 2 as the fast Read more…

By Tiffany Trader

HPE No. 1, IBM Surges, in ‘Bucking Bronco’ High Performance Server Market

September 27, 2018

Riding healthy U.S. and global economies, strong demand for AI-capable hardware and other tailwind trends, the high performance computing server market jumped 28 percent in the second quarter 2018 to $3.7 billion, up from $2.9 billion for the same period last year, according to industry analyst firm Hyperion Research. Read more…

By Doug Black

Nvidia’s Jensen Huang Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can do. Animated. Backstopped by a stream of data charts, product photos, and even a beautiful image of supernovae... Read more…

By John Russell

Germany Celebrates Launch of Two Fastest Supercomputers

September 26, 2018

The new high-performance computer SuperMUC-NG at the Leibniz Supercomputing Center (LRZ) in Garching is the fastest computer in Germany and one of the fastest i Read more…

By Tiffany Trader

Houston to Field Massive, ‘Geophysically Configured’ Cloud Supercomputer

October 11, 2018

Based on some news stories out today, one might get the impression that the next system to crack number one on the Top500 would be an industrial oil and gas mon Read more…

By Tiffany Trader

Intel Confirms 48-Core Cascade Lake-AP for 2019

November 4, 2018

As part of the run-up to SC18, taking place in Dallas next week (Nov. 11-16), Intel is doling out info on its next-gen Cascade Lake family of Xeon processors, specifically the “Advanced Processor” version (Cascade Lake-AP), architected for high-performance computing, artificial intelligence and infrastructure-as-a-service workloads. Read more…

By Tiffany Trader

Google Releases Machine Learning “What-If” Analysis Tool

September 12, 2018

Training machine learning models has long been time-consuming process. Yesterday, Google released a “What-If Tool” for probing how data point changes affect a model’s prediction. The new tool is being launched as a new feature of the open source TensorBoard web application... Read more…

By John Russell

The Convergence of Big Data and Extreme-Scale HPC

August 31, 2018

As we are heading towards extreme-scale HPC coupled with data intensive analytics like machine learning, the necessary integration of big data and HPC is a curr Read more…

By Rob Farber

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This