Architecting HPC Data Storage Solutions

By Ken Claffey

December 19, 2011

Innovation has been the cornerstone of success in our heritage in the data storage industry for the last twenty-five years.   About two years ago, Xyratex initiated an investigation into additional market opportunities for enterprise class data storage solutions.  Our research yielded interesting data points that aligned with the strengths of Xyratex.  We discovered that not only was the High Performance Computing (HPC) a high growth area for storage, it also represented a dynamic market opportunity with a substantial need for better data storage design. We also learned that the way data storage was being implemented at many of these sites was unduly complicated in terms of initial installation, performance optimization and ongoing management.  

The performance requirements of HPC environments with ever-larger compute clusters have placed unprecedented demands on the I/O performance of supporting storage systems. Storage I/O has become the performance bottleneck for many HPC clusters, as traditional storage systems cannot keep pace with the increasing scale of these deployments. Clearly, a state-of-the-art, scalable HPC storage solution is required. What would a high-performance storage architecture that offers a new level of component integration and performance optimization in HPC environments look like?

The HPC market is going through a paradigm shift. The adoption of low-cost, Linux-based clusters that offer significant computing performance and the ability to run a wide array of applications has extended HPC’s reach from its roots in scientific laboratories to smaller workgroups and departments across a broad range of industrial segments, from biotechnology and cloud computing, to manufacturing sectors such as aeronautics, automotive, and energy.

With dramatic drops in server prices, the introduction of multi-core processors, and the availability of high-performance network interconnects, proprietary monolithic systems have given way to commodity scale-out deployments. Users wanting to leverage the proven benefits of HPC can configure hundreds, even thousands, of low-cost servers into clusters that deliver aggregate compute power traditionally only available in supercomputing environments.

As HPC architecture has evolved, there has been a fundamental change in the type of data managed in clustered systems. Many new deployments require large amounts of unstructured data to be processed. Managing the proliferation of digital data – documents, images, video, and other formats, places a premium on high-throughput, high-availability storage. The explosive growth of large data has created a demand for storage systems that deliver superior I/O performance. However, technical limitations in traditional storage technology have prevented these systems from being optimized for I/O throughput. Performance bottlenecks occur when legacy storage systems cannot balance I/O loads or keep up with high-performance compute clusters that scale linearly as new nodes are added.

Despite the obvious advantage in application performance offered by HPC cluster environments, the difficulty in optimizing traditional storage systems for I/O throughput, combined with architectural complexities, integration challenges, and system cost have been barriers to wider adoption of clustered storage solutions in industrial settings. With the introduction of the Xyratex ClusterStor 3000™, a fully integrated, Lustre® based storage cluster solution, these challenges have been met.

Scale-Out Storage Architecture Overview

At the heart of the ClusterStor 3000 is the Scale-Out Storage Architecture, an advanced storage design that provides higher density and system reliability at lower cost. Fully integrating the Scale-Out Storage Architecture with the Lustre file system creates a next-generation HPC storage solution that delivers simplified system installation and operation, optimized HPC performance, and non-disruptive cluster expansion.

Limitations of Traditional Server/Storage Systems

Traditional storage clusters are made up of a number of disparate building blocks, including servers to run the file system and associated software, a high-speed storage interconnect, such as InfiniBand, connected to a RAID controller, and a high-density storage system housing the disk. Each subsystem in this hardware/software combination adds complexity and potential bottlenecks in terms of balancing I/O, reliability, and system scalability.

Scale-Out Storage Architecture – Distributed I/O Processing at Scale

The ClusterStor Scale-Out Storage Architecture is a consolidated hardware and software environment, designed from the ground up to uniquely address the demand for  Lustre scalability and performance, which features an integrated Scalable Storage Unit (SSU). Each SSU supports two industry-standard x86 Embedded Server Modules (ESMs), which connect directly through a common midplane to all drives in the SSU, and share a redundant high-speed interconnect across the midplane for failover services. The ESMs are capable of running industry-standard Linux distributions, and each module has its own dedicated CPU, memory, network, and storage connectivity. When new SSUs are added to the cluster, performance scales linearly as incremental processing network connectivity and storage media are added with each unit. This modular design removes the performance limitation of traditional models in which servers or RAID heads quickly become the bottleneck as more drives are added to the cluster. The Scale-Out Storage Architecture combines enclosure and server enhancements with software stack optimizations to deliver balanced I/O performance (even on large data workloads), and outperform traditional storage topologies by adding easy-to-install, modular SSUs that scale ESMs as HPC storage scales, distributing I/O processing throughout the solution.

Overcoming Lustre’s Challenges

Despite the obvious advantages of using Lustre as a clustered file system in HPC deployments, legacy installations have shown limitations and challenges to users. Integrating Lustre into an HPC solution that overcomes these challenges drove the development and design of the ClusterStor 3000.

Installation and Administration

Lustre is traditionally installed and administered from a command-line interface, requiring fairly advanced knowledge of Linux administration and experience provisioning clusters and managing distributed nodes. System administrators may lack this knowledge or not understand the complexities of the Lustre software, requiring them to rely heavily on professional services and external support to deploy and administer the file system. Additionally, integrating Lustre into a storage system with heterogeneous hardware adds system and support complexity. It can take weeks to get the system up and running reliably, with additional effort required to tune system performance or upgrade large systems without interruption of service

ClusterStor Approach:

ClusterStor systems come installed and configured from the factory, fully optimized to work with Lustre, and ready to deploy right from the loading dock. This innovative HPC storage design leaves behind the complexities of other systems that integrate third-party equipment and require tuning of file system performance in a heterogeneous, multi-vendor infrastructure.

Additionally, the ClusterStor 3000 includes a browser-based GUI that features intuitive wizards to guide administrators though automated Lustre network configuration and user authentication, greatly easing cluster setup. Once the file system is running, the ClusterStor Manager is used to administer the Lustre cluster (including failover and other tasks), monitor operations, analyze performance, gather statistics, generate reports and update the system non-disruptively.

Data Redundancy and Protection

Lustre maintains the integrity of data in the file system, but it does not back up data. Lustre relies exclusively on the redundancy of backing storage devices. To protect data from loss, Lustre users must attach external RAID storage.

ClusterStor Approach:

ClusterStor’s Scale-Out Storage Architecture uses a highly-available RAID 6 array to protect system data and provide optimal fault tolerance and performance. The Lustre file system’s Object Storage Servers (OSSs) are configured for active-active failover, enabling all logical drives to be seen by both OSSs at all times. If one OSS node fails, the active OSS takes over OST management and operations of the failed node. In normal non-failure mode, I/O load is balanced between the OSSs.

System Monitoring and Troubleshooting

Lustre generates events to indicate changing states and conditions in the file system, but it does not provide comprehensive file system monitoring. In the event of file system errors, log descriptions may clearly indicate the problem, but many entries are difficult to interpret without Lustre troubleshooting experience. Additionally, Lustre does not isolate file system errors from faults in the client/server hardware, network interconnect, or backing storage system. In a large-scale file system, determining root cause may be difficult.

ClusterStor Approach:

ClusterStor Manager provides a unified system view of all Lustre nodes, with combined syslogs available to monitor events in the cluster. To enhance the usability of the Lustre logs, filtering and record sorting is available. Additionally, the ClusterStor Manager rolls up log information into diagnostic payloads, ensuring that support engineers have all the information needed to help customers diagnose and resolve issues quickly.

As part of the ClusterStor 3000, Lustre is deployed on a hardware platform offering sophisticated fault isolation to pinpoint the location of a failure, with easy field serviceability to quickly replace failed parts and system wide high-availability, enabling uninterrupted cluster operations if a component fails.

ClusterStor 3000 delivers:

Industry-leading IOPS performance and solution bandwidth – distributed I/O processing and balanced workloads as the system scales linearly

Faster, easier system implementation and reliable expansion – factory-installed and tested components, reduced cable complexity with solution setup in hours, not days or weeks, plus streamlined system expansion with turnkey Scalable Storage Units (additional storage and processing nodes)

Fully integrated hardware and software platform – smaller solution footprint (fewer components, lower cost, and improved investment protection)

Simplified cluster management – ClusterStor Manager automates configuration and node provisioning, and provides performance statistics, system snapshots, and syslog reporting

Extreme reliability, availability, and serviceability – No single point of failure and redundancy built in throughout.

Visit  to learn more about the ClusterStor HPC data storage 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!

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is built to run artificial intelligence (AI) workloads and, as Read more…

By Tiffany Trader

New Exascale System for Earth Simulation Introduced

April 23, 2018

After four years of development, the Energy Exascale Earth System Model (E3SM) will be unveiled today and released to the broader scientific community this month. The E3SM project is supported by the Department of Energy Read more…

By Staff

RSC Reports 500Tflops, Hot Water Cooled System Deployed at JINR

April 18, 2018

RSC, developer of supercomputers and advanced HPC systems based in Russia, today reported deployment of “the world's first 100% ‘hot water’ liquid cooled supercomputer” at Joint Institute for Nuclear Research (JI Read more…

By Staff

HPE Extreme Performance Solutions

Hybrid HPC is Speeding Time to Insight and Revolutionizing Medicine

High performance computing (HPC) is a key driver of success in many verticals today, and health and life science industries are extensively leveraging these capabilities. Read more…

New Device Spots Quantum Particle ‘Fingerprint’

April 18, 2018

Majorana particles have been observed by university researchers employing a device consisting of layers of magnetic insulators on a superconducting material. The advance opens the door to controlling the elusive particle Read more…

By George Leopold

AI-Focused ‘Genius’ Supercomputer Installed at KU Leuven

April 24, 2018

Hewlett Packard Enterprise has deployed a new approximately half-petaflops supercomputer, named Genius, at Flemish research university KU Leuven. The system is Read more…

By Tiffany Trader

Cray Rolls Out AMD-Based CS500; More to Follow?

April 18, 2018

Cray was the latest OEM to bring AMD back into the fold with introduction today of a CS500 option based on AMD’s Epyc processor line. The move follows Cray’ Read more…

By John Russell

IBM: Software Ecosystem for OpenPOWER is Ready for Prime Time

April 16, 2018

With key pieces of the IBM/OpenPOWER versus Intel/x86 gambit settling into place – e.g., the arrival of Power9 chips and Power9-based systems, hyperscaler sup Read more…

By John Russell

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Cloud-Readiness and Looking Beyond Application Scaling

April 11, 2018

There are two aspects to consider when determining if an application is suitable for running in the cloud. The first, which we will discuss here under the title Read more…

By Chris Downing

Transitioning from Big Data to Discovery: Data Management as a Keystone Analytics Strategy

April 9, 2018

The past 10-15 years has seen a stark rise in the density, size, and diversity of scientific data being generated in every scientific discipline in the world. Key among the sciences has been the explosion of laboratory technologies that generate large amounts of data in life-sciences and healthcare research. Large amounts of data are now being stored in very large storage name spaces, with little to no organization and a general unease about how to approach analyzing it. Read more…

By Ari Berman, BioTeam, Inc.

IBM Expands Quantum Computing Network

April 5, 2018

IBM is positioning itself as a first mover in establishing the era of commercial quantum computing. The company believes in order for quantum to work, taming qu Read more…

By Tiffany Trader

FY18 Budget & CORAL-2 – Exascale USA Continues to Move Ahead

April 2, 2018

It was not pretty. However, despite some twists and turns, the federal government’s Fiscal Year 2018 (FY18) budget is complete and ended with some very positi Read more…

By Alex R. Larzelere

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

Leading Solution Providers

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

HPC and AI – Two Communities Same Future

January 25, 2018

According to Al Gara (Intel Fellow, Data Center Group), high performance computing and artificial intelligence will increasingly intertwine as we transition to Read more…

By Rob Farber

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

New Blueprint for Converging HPC, Big Data

January 18, 2018

After five annual workshops on Big Data and Extreme-Scale Computing (BDEC), a group of international HPC heavyweights including Jack Dongarra (University of Te Read more…

By John Russell

Momentum Builds for US Exascale

January 9, 2018

2018 looks to be a great year for the U.S. exascale program. The last several months of 2017 revealed a number of important developments that help put the U.S. Read more…

By Alex R. Larzelere

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This