Intelligent Application of SSDs to Accelerate HPC Workloads

By Nicole Hemsoth

October 1, 2012

Introduction

In most industries today, (whether it is financial services, manufacturing, academic research, healthcare and life sciences, or energy exploration) data analysis, modeling, and visualization efforts are critical to success.

To gain a competitive edge, most organizations are incorporating ever-large data sets and more variable data formats into these computational workflows to help derive better information upon which to make smarter decisions.

These big data applications are placing new attention on the high performance computing (HPC) solutions used to run the algorithms and process the raw data. Due to the larger volumes and greater variety of data types, as well as the desire to use more robust analysis, modeling, and visualization routines, HPC solutions can be used to provide high sustained I/O and throughput, while being optimized to cost-effectively handle highly variable workflows.

The essential element in all of this work is a need for speed. Organizations need fast time-to-results so that they can make the right decisions (which well to drill, which new drug candidate to develop, which product design to produce, which customer to award a lower rate loan to) before their competitors.

Complications and challenges that can impede HPC workflows

When looking to accelerate HPC workloads, there are several factors that can play a major role in overall performance.

To start, today’s analysis, modeling, and visualization efforts are carried out using much more sophisticated algorithms in order to derive more detailed and realistic results. The output from these routines offers finer spatial or temporal resolution and consequently results in much larger size output data sets. In a typical workflow, those output files might be used as input to another analysis, modeling, or visualization application.

These operations can impact HPC workflows since the great volumes of data produced by the initial run must be written to disk and saved and then the data must be ingested by yet another routine. Both operations can generate high I/O and throughput demands on an infrastructure. And if the infrastructure is not capable of sustaining these data transfers, the computational workflows can slow significantly.

Another factor has to do with the data that is being used in today’s analysis, modeling, and visualization efforts. Nearly every industry is now making use of much larger data sets, richer sets (such as that produced from newer seismic imaging tools or next-generation sequencers), and many more types of data. However, most users, even those who primarily have large data sets, also have large numbers of small files – even if they consume a relatively small percentage of the total capacity.

Big data and HPC solutions must therefore not only be capable of quickly accessing the large volumes of data required for the computations, they also must intelligently stage the different types of data, which comes in varying file formats and sizes, on suitably high performance storage.

Required storage solution characteristics

Organizations continually deploy new servers with more powerful CPUs to improve and speed up their analysis, modeling, and visualization efforts. To make the best use of such computing resources, an HPC solution must have a suitable storage solution to sustain HPC workflows.

A storage solution for today’s big data and HPC environments must be able to easily scale. Some solutions offer help meeting the growing data volume demands, but fall short when trying to keep CPUs satiated. To help accelerate HPC workflows, a storage solution must also scale in performance so that as the data volumes grow, the system supports the higher I/O and throughput required to get faster results.

Finally, a storage solution must be optimized to handle today’s HPC big data workflows consisting of data sets of files of all sizes. If all data used were in the same format – a structured database, for example – or of the same relative file size, a solution could be highly optimized to handle the specific data. Working with the mixed data sets used today requires a storage solution that optimizes workflow performance for each data type.

Panasas introduces an integrated SSD/SATA approach

Panasas ActiveStor storage systems have a modular blade architecture integrated with its PanFS parallel file system. The design eliminates the bottleneck of a single RAID controller to deliver high-performance, scalable storage. Prior generations of ActiveStor have been based solely on SATA drives and were well-tuned for high throughput.

With the fifth-generation ActiveStor 14, Panasas has taken a unique approach, leveraging lightning fast SSDs integrated with high capacity SATA disk to improve storage performance while keeping costs down. Rather than use SSD for caching or for “most recent” file access as many other vendors have done, ActiveStor 14 stores all metadata and small files (less than 60KB) on the SSDs and larger files on SATA drives.

Metadata is accessed frequently so fast metadata access benefits all types of workloads. All file operations, including reads and writes, require access to metadata. In many cases, such as directory listings, access to the metadata is all that is required to satisfy an I/O request. Storing metadata on SSD boosts performance for all storage operations, especially for directory functions (listing, searches, etc.) and RAID rebuilds in the event of a drive error. Rebuild performance has been improved so that the new 4TB drives can be rebuilt in the same amount of time as the 3TB drives in the prior generation ActiveStor 12, maintaining a high level of data integrity and system reliability.

Small file access can be disproportionately slow when read from, or written to, standard hard disk drives. Accesses of less than a full sector are inefficient, particularly for random I/O. Furthermore, reads and writes of small files can conflict with streaming reads or writes of large files to the same disk. By maintaining small files on SSD, such conflicts are eliminated. In addition, ActiveStor 14 stores the first 12KB of all files inside the file system metadata, improving SSD efficiency while increasing small file performance. This efficient storage of small files on SSD, dramatically improves response time and IOPS, as evidenced by very impressive SPEC sfs2008 NFS IOPS results that Panasas has published.

ActiveStor 14 is available in three configurations with varying sizes of SSD, SATA and cache. The amount of SSD for acceleration ranges from 1.5 percent up to 10.7 percent of total storage capacity. The bulk of the storage capacity, however, is on cost-effective SATA drives, keeping the overall cost per terabyte lower than the prior generation, and very competitive in the market today.

The Importance of Ease of Use and Management

Equally important to the performance and reliability of any storage system is the ease of use and management of the product. With ActiveStor, organizations can simply add blade enclosures to non-disruptively increase capacity and performance of the global file system as storage requirements grow. Parallel access to data and automated load balancing ensure that performance is optimized. This makes it easy to linearly scale capacity to over eight petabytes and performance to 150GB/s or 1.4M IOPS.

Conclusion

The end result is a high-performance storage system that delivers high throughput and IOPS, ideal for the most demanding HPC and big data workloads and accelerates time-to-results. ActiveStor delivers unmatched scale-out NAS performance in addition to the manageability, reliability, and value required by demanding computing organizations in the biosciences, energy, finance, government, manufacturing, media, and other research sectors.

To learn more about how the Panasas ActiveStor 14 can help your organization, register for the live webinar: http://www.panasas.com/news/webinars

 

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!

What’s New in HPC Research: September (Part 1)

September 18, 2018

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

By Oliver Peckham

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 development. Among other things it would establish a National Quantu Read more…

By John Russell

Nvidia Accelerates AI Inference in the Datacenter with T4 GPU

September 14, 2018

Nvidia is upping its game for AI inference in the datacenter with a new platform consisting of an inference accelerator chip--the new Turing-based Tesla T4 GPU--and a refresh of its inference server software packaged as Read more…

By George Leopold

HPE Extreme Performance Solutions

Introducing the First Integrated System Management Software for HPC Clusters from HPE

How do you manage your complex, growing cluster environments? Answer that big challenge with the new HPC cluster management solution: HPE Performance Cluster Manager. Read more…

IBM Accelerated Insights

A Crystal Ball for HPC

People are notoriously bad at predicting the future.  This very much includes experts. In the Forbes article “Why Most Predictions Are So Bad” Philip Tetlock discusses the largest and best-known test of the accuracy of expert predictions which show that any experts would do better if they make random guesses. Read more…

NSF Highlights Expanded Efforts for Broadening Participation in Computing

September 13, 2018

Today, the Directorate of Computer and Information Science and Engineering (CISE) of the NSF released a letter highlighting the expansion of its broadening participation in computing efforts. The letter was penned by Jam Read more…

By Staff

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

Nvidia Accelerates AI Inference in the Datacenter with T4 GPU

September 14, 2018

Nvidia is upping its game for AI inference in the datacenter with a new platform consisting of an inference accelerator chip--the new Turing-based Tesla T4 GPU- Read more…

By George Leopold

DeepSense Combines HPC and AI to Bolster Canada’s Ocean Economy

September 13, 2018

We often hear scientists say that we know less than 10 percent of the life of the oceans. This week, IBM and a group of Canadian industry and government partner Read more…

By Tiffany Trader

Rigetti (and Others) Pursuit of Quantum Advantage

September 11, 2018

Remember ‘quantum supremacy’, the much-touted but little-loved idea that the age of quantum computing would be signaled when quantum computers could tackle Read more…

By John Russell

How FPGAs Accelerate Financial Services Workloads

September 11, 2018

While FSI companies are unlikely, for competitive reasons, to disclose their FPGA strategies, James Reinders offers insights into the case for FPGAs as accelerators for FSI by discussing performance, power, size, latency, jitter and inline processing. Read more…

By James Reinders

Update from Gregory Kurtzer on Singularity’s Push into FS and the Enterprise

September 11, 2018

Container technology is hardly new but it has undergone rapid evolution in the HPC space in recent years to accommodate traditional science workloads and HPC systems requirements. While Docker containers continue to dominate in the enterprise, other variants are becoming important and one alternative with distinctly HPC roots – Singularity – is making an enterprise push targeting advanced scale workload inclusive of HPC. Read more…

By John Russell

At HPC on Wall Street: AI-as-a-Service Accelerates AI Journeys

September 10, 2018

AIaaS – artificial intelligence-as-a-service – is the technology discipline that eases enterprise entry into the mysteries of the AI journey while lowering Read more…

By Doug Black

No Go for GloFo at 7nm; and the Fujitsu A64FX post-K CPU

September 5, 2018

It’s been a news worthy couple of weeks in the semiconductor and HPC industry. There were several HPC relevant disclosures at Hot Chips 2018 to whet appetites Read more…

By Dairsie Latimer

TACC Wins Next NSF-funded Major Supercomputer

July 30, 2018

The Texas Advanced Computing Center (TACC) has won the next NSF-funded big supercomputer beating out rivals including the National Center for Supercomputing Ap Read more…

By John Russell

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

Requiem for a Phi: Knights Landing Discontinued

July 25, 2018

On Monday, Intel made public its end of life strategy for the Knights Landing "KNL" Phi product set. The announcement makes official what has already been wide Read more…

By Tiffany Trader

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

ORNL Summit Supercomputer Is Officially Here

June 8, 2018

Oak Ridge National Laboratory (ORNL) together with IBM and Nvidia celebrated the official unveiling of the Department of Energy (DOE) Summit supercomputer toda Read more…

By Tiffany Trader

New Deep Learning Algorithm Solves Rubik’s Cube

July 25, 2018

Solving (and attempting to solve) Rubik’s Cube has delighted millions of puzzle lovers since 1974 when the cube was invented by Hungarian sculptor and archite Read more…

By John Russell

AMD’s EPYC Road to Redemption in Six Slides

June 21, 2018

A year ago AMD returned to the server market with its EPYC processor line. The earth didn’t tremble but folks took notice. People remember the Opteron fondly Read more…

By John Russell

MLPerf – Will New Machine Learning Benchmark Help Propel AI Forward?

May 2, 2018

Let the AI benchmarking wars begin. Today, a diverse group from academia and industry – Google, Baidu, Intel, AMD, Harvard, and Stanford among them – releas Read more…

By John Russell

Leading Solution Providers

SC17 Booth Video Tours Playlist

Altair @ SC17

Altair

AMD @ SC17

AMD

ASRock Rack @ SC17

ASRock Rack

CEJN @ SC17

CEJN

DDN Storage @ SC17

DDN Storage

Huawei @ SC17

Huawei

IBM @ SC17

IBM

IBM Power Systems @ SC17

IBM Power Systems

Intel @ SC17

Intel

Lenovo @ SC17

Lenovo

Mellanox Technologies @ SC17

Mellanox Technologies

Microsoft @ SC17

Microsoft

Penguin Computing @ SC17

Penguin Computing

Pure Storage @ SC17

Pure Storage

Supericro @ SC17

Supericro

Tyan @ SC17

Tyan

Univa @ SC17

Univa

Pattern Computer – Startup Claims Breakthrough in ‘Pattern Discovery’ Technology

May 23, 2018

If it weren’t for the heavy-hitter technology team behind start-up Pattern Computer, which emerged from stealth today in a live-streamed event from San Franci Read more…

By John Russell

Sandia to Take Delivery of World’s Largest Arm System

June 18, 2018

While the enterprise remains circumspect on prospects for Arm servers in the datacenter, the leadership HPC community is taking a bolder, brighter view of the x86 server CPU alternative. Amongst current and planned Arm HPC installations – i.e., the innovative Mont-Blanc project, led by Bull/Atos, the 'Isambard’ Cray XC50 going into the University of Bristol, and commitments from both Japan and France among others -- HPE is announcing that it will be supply the United States National Nuclear Security Administration (NNSA) with a 2.3 petaflops peak Arm-based system, named Astra. Read more…

By Tiffany Trader

D-Wave Breaks New Ground in Quantum Simulation

July 16, 2018

Last Friday D-Wave scientists and colleagues published work in Science which they say represents the first fulfillment of Richard Feynman’s 1982 notion that Read more…

By John Russell

Intel Pledges First Commercial Nervana Product ‘Spring Crest’ in 2019

May 24, 2018

At its AI developer conference in San Francisco yesterday, Intel embraced a holistic approach to AI and showed off a broad AI portfolio that includes Xeon processors, Movidius technologies, FPGAs and Intel’s Nervana Neural Network Processors (NNPs), based on the technology it acquired in 2016. Read more…

By Tiffany Trader

Intel Announces Cooper Lake, Advances AI Strategy

August 9, 2018

Intel's chief datacenter exec Navin Shenoy kicked off the company's Data-Centric Innovation Summit Wednesday, the day-long program devoted to Intel's datacenter Read more…

By Tiffany Trader

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

GPUs Power Five of World’s Top Seven Supercomputers

June 25, 2018

The top 10 echelon of the newly minted Top500 list boasts three powerful new systems with one common engine: the Nvidia Volta V100 general-purpose graphics proc Read more…

By Tiffany Trader

The Machine Learning Hype Cycle and HPC

June 14, 2018

Like many other HPC professionals I’m following the hype cycle around machine learning/deep learning with interest. I subscribe to the view that we’re probably approaching the ‘peak of inflated expectation’ but not quite yet starting the descent into the ‘trough of disillusionment. This still raises the probability that... Read more…

By Dairsie Latimer

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