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Applicaon Report Big Data, Big Cluster Interconnects Featuring Analycs Soluon OneConnect Servers Dell Servers Cisco Servers and Networks Where IT percepons are reality Copyright 2012© IT Brand Pulse. All rights reserved. Document # APP2012002 v1 April, 2012

Application Report: Big Data - Big Cluster Interconnects

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As a leading analytics platform that runs on industry-standard hardware and integrates industry-standard database tools and applications, one of ParAccel’s biggest challenges is to architect and test hardware (servers, storage, interconnects) that make their software perform at its peak. In this case, they have achieved their mission to eliminate a cluster bottleneck by implementing 10GbE NICs to provide the bandwidth needed to-day, and well into the future.

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Page 1: Application Report: Big Data - Big Cluster Interconnects

Application Report

Big Data, Big Cluster Interconnects

Featuring

Analytics Solution

OneConnect

Servers

Dell Servers

Cisco Servers and Networks

Where IT perceptions are reality

Copyright 2012© IT Brand Pulse. All rights reserved. Document # APP2012002 v1 April, 2012

Page 2: Application Report: Big Data - Big Cluster Interconnects

About

Company Overview ParAccel: The fastest analytic database + The strongest extensibility framework = The Most Powerful Analytic Platform. For organizations with vast amounts of Big Data, the need for Big Ana-lytics - or both - the ParAccel Analytic Platform provides orders of magnitude better analytic performance compared to traditional data processing platforms. At the core of the platform is a high perfor-mance analytic database, designed specifically for the fastest query performance at any scale. The ParAccel Analytic Platform provides a massively parallel pro-cessing (MPP), shared-nothing analytic database that performs opera-tions such as aggregation and joins against large amounts of unstruc-tured data. ParAccel surrounded its analytic database with an extensibility framework that imbeds over 800 analytic functions and supports the on-demand integration of a variety of structured and unstructured data and ana-lytic results, right at the point of execution. The result is that compared to transaction-oriented databases where operations are optimized to perform single row insertions and deletions, ParAccel dramatically outperforms the competition.

Realizing its Potential with Big Data According to a survey conducted by TDWI Research, Big Data an-alytics requires massive performance and scalability. Common problems voiced by users are that old platforms can’t scale to big data volumes (42%), they load data too slowly (29%), they re-spond to queries too slowly (24%), and they lack processing (CPU) capacity for analytics (17%). As a result, one big challenge for customers is to evaluate and deploy server, storage, and networking hardware which enables them to realize the full performance potential of ParAccel when processing Big Data.

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Evaluate and deploy server, storage, and networking hardware that

enables customers to realize the full performance potential of ParAccel

when processing Big Data.

Goal

ParAccel is the only “pure play” database platform company dedicated to analyzing big data. Customers include industry leaders such as Ceridian, Nielsen and OfficeMax.

ParAccel Analytics Solutions require fast, scalable hardware to deliver full performance.

Document # APP202002 v1, April, 2012

Page 3: Application Report: Big Data - Big Cluster Interconnects

Key Hardware Technologies

Scaling High Performance Computing Clusters is made possible

with high bandwidth, low-latency 10GbE connections between

each compute node.

10GbE

On-going evaluations of hardware to complement ParAccel software often involve new technologies, prod-

ucts, and processes. High Performance Computing Clusters, Sandy Bridge Processors, Solid State Disk (SSD)

and 10Gb Ethernet stand out as technologies that can make a big difference when included in the ParAccel

configurations.

High Performance Computing Clusters (HPCC)

Using industry-standard servers as building

blocks, HPCCs can scale to the supercomputer-

class processing power needed to handle large

data sets. Each node in the cluster crunches

and analyzes data, then pushes it back to the

Leader node to collect and report.

Intel Sandy Bridge Processors (Xeon E5-2600)

The introduction of the new Intel Romley

Platform, including Sandy Bridge processors (also know as Xeon E5-2600) offer up to 80% perfor-

mance improvements over the previous generation Xeon 5600.

Solid State Disk (SSD)

SSDs offer dramatically faster access times than Hard Disk Drives (HDDs), are far

more rugged, and use much less power. The low cost of Flash memory is driving

expanded use of SSD as primary storage (disk array) cache, and as primary stor-

age for frequently accessed data such as database tables, mathematical and sta-

tistical functions, or processing algorithms.

10 Gigabit Ethernet

Scaling High Performance Computing Clusters is made possible with high bandwidth, low-

latency connections between each compute node. The cost of 10 gigabit Ethernet has

plummeted in the last few years, making the use of 10GbE NICs an affordable alternative

to 1GbE NICs for cluster interconnects.

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Clusters scale cost-effectively to supercomputer-class power by adding compute nodes consisting of industry standard servers.

Solid State Disk (SSD) speeds access to frequently used data.

10GbE NICs functioning as cluster interconnects are required to scale large clusters with powerful new servers based on Sandy Bridge processors.

Document # APP2012002 v1, April, 2012

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Killer App

High Performance Cluster Interconnects Emerge as a Killer App for 10GbE Until recently, the reference hardware tested

and qualified for a ParAccel Cluster included

an inter-processor communications (IPC) fab-

ric based on 1GbE technology. Each compute

node was configured with four 1GbE NIC

ports bonded together to form a single clus-

ter interconnect totaling 4Gb of bandwidth.

However, on-going testing by ParAccel with

bigger data, more powerful servers, and fast-

er storage showed the 4Gb cluster intercon-

nect had emerged as a performance bottle-

neck.

ParAccel investigated higher performance interconnects and found that 10GbE server adapter technology

was embedded on many new servers and affordable in an adapter card form-factor. They also found that

each port on a dual-port 10GbE server adapter provides bi-directional bandwidth of 20Gb, and a total band-

width of 40Gb.

Having already qualified Emulex Fibre Channel

HBAs for their SAN option, ParAccel looked to

Emulex for OneConnect 10Gb NICs. Once in-

stalled, the ParAccel team measured 5Gb of

bandwidth being used on each link, giving

them plenty of headroom for scaling perfor-

mance in the future. Reference designs with

10GbE technology also reduced the amount of

cabling required in the 1GbE communications

fabric by 75%.

Each port on a dual-port 10GbE server adapter provides bi-directional

bandwidth of 20Gb, and a total bandwidth of 40Gb. 40Gb

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Each server configured with one 10GbE NIC port for Inter Processor Communica-tions (IPC). New more powerful servers and software are expected to consume more than 5Gb of bandwidth used today.

Reference Hardware Configuration

using 1GbE Cluster Interconnect

Reference Hardware Configuration

using 10GbE Cluster Interconnect

Each server configured with four 1GbE NIC ports for Inter Processor Communica-tions (IPC). This 4Gb interconnect emerged as a cluster bottleneck.

Document # APP2012002 v1, April, 2012

Page 5: Application Report: Big Data - Big Cluster Interconnects

Results & Lessons Learned

Mission Accomplished As a leading analytics platform that runs on industry-standard hardware and integrates industry-standard da-

tabase tools and applications, one of ParAccel’s biggest challenges is to architect and test hardware (servers,

storage, interconnects) that make their software perform at its peak. In this case, they have achieved their

mission to eliminate a cluster bottleneck by implementing 10GbE NICs to provide the bandwidth needed to-

day, and well into the future.

But their mission is only partially accomplished. The ParAccel team believes they can achieve a higher level of

performance with a lower latency cluster interconnect. However, the company is waiting for more affordable

low latency 10Gb NIC products to become available before qualifying them for ParAccel clusters.

Lessons Learned The following are a few lessons the ParAccel staff want to share with their peers:

The bandwidth and latency of the communications fabric is key to scaling the performance of a cluster.

A holistic approach to I/O and processing bottleneck is required for best performance.

Network capacity/bandwidth becomes even more critical as the number of nodes in your cluster increas-

es.

10GbE can enable companies to continue to scale linearly even as their clusters approach 100 nodes or

more.

To take proper advantage of the network, analytic workloads require a custom protocol (rather than rely

on the common TCP/IP standard).

Results

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A bandwidth bottleneck in the communications fabric is eliminated

with 10GbE. A lower latency interconnect could also improve perfor-

mance, but is not yet affordable.

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Resources

Related Links To learn more about the companies, technologies and products mentioned in this report, visit the following web pages: Intel— Sandy Bridge Technology Intel— Romley Platform Roadmap Fusion IO (Solid State Disk) Emulex OneConnect IT Brand Pulse ParAccel Analytic Platform

About the Author

Frank Berry is founder and senior analyst for IT Brand Pulse, a trusted source of data and analysis about IT infrastructure, including servers, storage and networking. As for-mer vice president of product marketing and corporate marketing for QLogic, and vice president of worldwide marketing for the automated tape library (ATL) division of Quan-tum, Mr. Berry has over 30 years experience in the development and marketing of IT infrastructure. If you have any questions or comments about this report, contact [email protected].

Page 6 of 6 Document # APP2012002 v1, April, 2012