hpc session 7: big data & data center efficiency … data & data center efficiency september...

© 2014 IBM Corporation

HPC Session 7:Big Data & Data Center Efficiency

September 22, 2014

2© 2014 IBM Corporation

Panel Members

Dave Weber, IBM, x86 Global Financial Segment lead

Rama Karedla, Intel, Performance Architect, HPC/Financial Services

Ed Turkel, HP, Group Manager, HPC Marketing

Nick Papadonis, Oracle, Engineering Consultant

Nick Ciarleglio, Arista, Distinguished Engineer


Increase in high profile security breaches

Growth in migration of platforms &applications to cloud service providers

Rise in mobility & Bring Your Own Device(BYOD) increasing data growth and risk

Real-time analysis of huge volumes of data

Enterprise customers assessing ODMs

1 Data from IBM Annual Survey of IT and line-of-business leaders for 20132 Citrix Top Enterprise Mobility Trends, http://blogs.citrix.com/2014/05/06/top-enterprise-mobility-trends/, May 20143 IDC Server Virtualization & Cloud, February 2013

Data center trends

30BConnected devices

by 20203

90%Data on planet created

in last 2 years1

#1Security concern of IT

decision makers & CIOs1

75%IT spend on new cloud

projects by 20172

Security

Cloud

Big Data

Mobility

http://blogs.citrix.com/2014/05/06/top-enterprise-mobility-trends/


NEW System x3650 M5High-performing & versatile 2U2S rack server for

analytics & cloud

Virtual Desktop

SAP / BusinessAnalytics

DataManagement

Cloud /Virtualization

Big Data

NEW System x3550 M5Compact powerful 1U2S rack server

NEW NeXtScale nx360 M5 ServerVersatile, ½ wide 1U2S server for HPC, cloud, and

analytics

NEW NeXtScale System withWater Cool Technology

Efficient, full-wide, dual-node water cooledserver for HPC

NEW x3500 M5 (1Q15)2S Tower or Rack for

business critical workloads

#1 ReliabilityBuilt-in

Rack & Tower Dense Blade

#1 SecurityBuilt-in

EfficiencyBuilt-in

NEW Flex x240 M5No compromise blade serverfor cloud, virtualization andbusiness applications

New System x portfolio for solutions & business productivity

50%1

More Cores& Cache

2X2

MemoryCapacity

131%3

Faster JavaPerformance

59%4

Faster DBPerformance

39%5

GreaterComputationalPerformance

61%6

GreaterVirtualizationPerformance

50%8

IncreasedMemory

Bandwidth

50%9

Memory PowerSavings


Cloud Virtualization

Virtual Desktop

Business Processing

Big Data

Virtualized Storage

Business Continuity

Partnerships with industry leading Independent Software Vendors

https://www.google.com/imgres?imgurl&imgrefurl=http%3A%2F%2Finside-bigdata.com%2F2014%2F04%2F02%2Fmapr-technologies-expands-big-data-search-elasticsearch%2F&h=0&w=0&tbnid=fa5CEDm44J_nmM&zoom=1&tbnh=129&tbnw=389&docid=H4GbgVjay0oWkM&tbm=isch&client=firefox-a&ei=CTLHU4bnCo6kyAT50oGYBQ&ved=0CAIQsCUoAA

https://www.google.com/imgres?imgurl=http%3A%2F%2Fwww.cloudwedge.com%2Fwp-content%2Fuploads%2F2014%2F05%2Fsap-logo.jpg&imgrefurl=http%3A%2F%2Fwww.cloudwedge.com%2F2014-cloud-shakeup-sap-leads-restructuring%2F&docid=TyQD0baH0xcoZM&tbnid=3UUpWdfKzEjunM&w=500&h=500&ei=bjPHU7-dCoqSyASsvYEY&ved=0CAUQxiAwAw&iact=c


IBM / Lenovo Announcement Highlights

Lenovo plans to acquire IBM’s x86 server portfolio and related resources and operationsincluding

– System x, BladeCenter and Flex System blade servers and switches, x86-based Flexintegrated infrastructure systems, NeXtScale and iDataPlex servers and associatedsoftware, blade networking and maintenance operations

– Development, sales and marketing, finance, legal, integrated supply chain, operations, ITand manufacturing

– Service and support (maintenance)

IBM will retain its enterprise systems portfolio, including System z mainframes, PowerSystems, Storage Systems, Power-based Flex servers, and PureApplication and PureDataappliances

Lenovo and IBM plans to enter into a strategic collaboration

– Lenovo becomes IBM’s supplier of x86 server technology– Lenovo will license, OEM and resell IBM Storwize and tape storage technologies, General Parallel

File System, SmartCloud Entry, elements of the x86 system software portfolio, and the PlatformComputing portfolio

Until the transaction is completed, the companies will continue to operate independently

The transaction is expected to close later this year, subject to the satisfaction of regulatory requirements, customary closing conditions and anyother needed approvals. Subsequent local closings will occur subject to similar conditions, the information and consultation process, and localagreements in applicable countries. It is expected that once completed Lenovo will assume IBM’s x86 global server business including sales,development, marketing, service and support (maintenance) and related services, finance and certain parts of Integrated Supply Chain (ISC)operations


Who is Lenovo

Lenovo is a $34B company1

Seven different nationalities among its top ten executives The company is publicly traded on the Hong Kong Stock Exchange 60% publicly held, 32% held by Legend Holdings and 7% by it’s CEO

Lenovo is a truly global company 46,000 employees across 60 different countries WW Dual global head quarters Raleigh, NC USA – American executive leadership of it’s US operations Beijing, China

Major research centers in the United States, Japan, and China Manufacturing capabilities in the United States, China, India, and Mexico

Lenovo has experience in incorporating a former IBM business unit – PC Company Nine years post division sale to Lenovo they retain heavy investment WW They have taken #1 share in the PC segment WW

1FY 2013 Revenue Statement


More info:

Dave Weber: [email protected] / [email protected]

System x servers

Lenovo transition

mailto:[email protected]


http://www-03.ibm.com/systems/x/

http://www.lenovo.com/transactions/pdf/lenovo-ibm-x86-acquisition-ppt.pdf

Intel’s Commitment to Big Data Performance

Translating technology benefits into business impact.

The Haswell Processor: Performance with Energy Efficiency, up to 18 cores, many architectural enhancements

• DDR4: Lower power consumption and access latencies, higher frequency, higher B/W

• Use your processor’s capabilities to the fullest..You paid for them !

11

Working with Oracle and vendors to optimize Javafor Big Data. JD8u20, vectorization throughSuperWord

In Memory Analytics: Working with vendors tooptimize memory transformations and layout.Hadoop: 110sec/iterationSpark: 80 secs and then 1 sec per iteration

HDFS optimizations and benefits through Lustre’stransparent replication

Technology ingredients such as Intel® Data Plane Development Kit,Virtualization Enhancements and VMware* ESXi optimizations enable theNetwork Function Virtualization (NFV) vision

Storage & Network Trends• PCIe based storage such as Intel’s P3700 SSDs provide > 6X

performance gains• Just released Intel’s 40GBe NICs are ready for high bandwidth

applications such as network virtualization, trade view servers etc.• AMPS: Integrating In Memory streaming analytics with demanding

storage and networking bandwidth requirements:2X greater performance on HSW-EP versus IVB-EP !!

Intel’s contributions to emerging trends in Big DataSupplementing big cores with many cores.

- A trend to watch

STAC A2 Greeks Benchmark: Intel’s HSW–EP was 30% faster than IVB-EP

STAC A2 Greeks Benchmark: HSW-EP plusone Xeon PHI Coprocessor card was 22%faster than a system with two CPUs and 2GPUs. Demonstrated 46 % higher assetcapacity and 53% increase in higher pathscapacity

Follow on Xeon Phi to be more Big Dataenabled with higher memory capacity.

References:

12

• Today’s Speaker: Rama Karedla, Performance Architect, FSI [email protected]

• https://stacresearch.com//news/2014/09/08/stac-reports-intels-new-haswell-server-chip-and-without-xeon-phi-stac-a2

• BIGS004 - Accelerating Hadoop* Performance on Intel® Architecture BasedPlatforms

www.intel.com/idfsessionsSF

• BIGS001 - In-Memory Low Latency Analytics: Opportunities and ArchitectureTrends


DATS012 - Intel® Data Plane Development Kit: Open Source Foundations andVMware* Usages



https://stacresearch.com/news/2014/09/08/stac-reports-intels-new-haswell-server-chip-and-without-xeon-phi-stac-a2

https://stacresearch.com/news/2014/09/08/stac-reports-intels-new-haswell-server-chip-and-without-xeon-phi-stac-a2

http://www.intel.com/idfsessionsSF



© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

HPC Strategy for FSIEd TurkelGroup Manager, HPC Business DevelopmentHyperscale Business Group, HP Servers

© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.14

Are you ready?

Accelerating pace of change requires a newstyle of IT

Advancing technologies

Cloud

MobilitySecurity

Big Data

Escalating demands

By 202030 billiondevices

40 trillion GBdata 10 million

mobile apps

8 billionpeople

…for

Changingconsumptionmodels

Evolvingecosystem

of ITproviders

IT requires moreperformance,

efficiency,sustainability


Global support and services | Best-in-class partnerships | Converged solutions

Convergence to accelerate IT servicedelivery

For virtualized and cloud workloads

HP BladeSystem HP OneView

Availability to function in real-time

For mission-critical environments

HP ProLiantscale-up

HP IntegrityNonStop

“DragonHawk” HP Integrity blades& Superdome

Intelligence to increase productivity

For core business applications

HP ProLiant ML HP ProLiant DLHP MicroServer

Density and efficiency to scale rapidly

For Big Data, HPC, and web scalability

Workload-optimized portfolio for better business outcomes

Commonmodularcompute

architectureHP ProLiant SL HP Moonshot HP Apollo


Delivering a complete HPC solution

Cloud

ServersCompute

StorageBig Data

AcceleratorsCompute, Viz

Network

Services

Power &Cooling

Management

ClientSystems


HAVEn – Big Data platform

HAVEn

Social media IT/OT ImagesAudioVideoTransactional

dataMobile Search engineEmail Texts

Catalog massivevolumes ofdistributed data

Hadoop/HDFS

Process andindex allinformation

AutonomyIDOL

Analyze atextreme scalein real-time

Vertica

Collect & unifymachine data

EnterpriseSecurity

PoweringHP Software+ your apps

nApps

Documents

hp.com/haven


Reinventing HPC todayto accelerate the world of tomorrow

HP Apollo familyOptimizing rack-scale computing for HPC

Acceleratingperformanceto speed up answers

Maximizingefficiencyfor sustainability and savings

UnleashingHPCto enterprises of any size

4x teraflops

per square foot

4x density per

rack per dollar

Years to daysfor new innovations

© Copyright 2012 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Thank you

20 Copyright © 2012, Oracle and/or its affiliates. All rights reserved.

Oracle’s Big Data Platform

OracleExalytics

InfiniBand

OracleReal-TimeDecisions

OracleBig DataAppliance

OracleExadata

InfiniBand

OEP

DataWarehouse

HadoopOracle Big Data

Connectors

Oracle R dist

Oracle NoSQLDatabase

Oracle DataIntegrator

OracleAdvanced

Analytics(ORE/ODM)

OracleDatabase

Stream AcquireOrganize /Discover

AnalyzeVisualize /

Decide

Oracles DataIntegrator

Endeca/OBIEE

Flume

DataReservoir

ExternalData

Sources

Internal DataSources

Copyright © 2014, Oracle and/or its affiliates. All rights reserved. |

Oracle’s NoSQL on YCSB (Yahoo Cloud Serving Benchmark)

• SPARC T5-8 Flexible implementation deployment strategies– Use larger server with virtualization example above using Solaris Zones (1 zone/chip)– Use multiple T5-2 servers– Use Multiple-large servers

Oracle Confidential – Highly Restricted 21

SPARC also very efficient at Big Data: Oracle’s NoSQL

YCSB chip core Processor Ops/sOps/s

per chipOracle per chip

Advantage

Oracle T5-8 8 zones 8 128 3.6 SPARC T5 1,198,918 149.9k 3.5x

Cisco C240 M312node

24 192 2.9 E5-2690 1,028,868 42.9K 1.0

Oracle T5-8 4 zones 4 64 3.6 SPARC T5 636,765 159.2K

Cisco C240 M3 3node 6 48 2.9 E5-2690 302,153 50.4k


Oracle’s Graph (Big Data Analytics)SPARC also very efficient at Big Data: Graph Algorithm

• SPARC 1.5x faster than E7 v2 per chip, great scalability– Graph is dependent delivered memory bandwidth

– BTE/s = Billion Traversed Edges per Second

Oracle Confidential – Highly Restricted 22

Graph chip Processor Problem Size2^30 & 2^31

PerfBTE/s

SPARC per chipAdvantage

Oracle T5-8 8 3.6 SPARC T5 31 1.67

Oracle T5-8 8 3.6 SPARC T5 30 1.73 1.6x faster than x86 E7 v2

X4-8 8 2.8 E7 v2 31 0.67

X4-4 4 2.8 E7 v2 30 0.54 Baseline


SPARC: Leads in Uniform System Bandwidth

• SPARC fully-connected SMP, uniform memory bandwidth

• NUMA: local memory fast, but much slower bandwidth to other memory

– Non-local memory is slow chip-to-chip, often with multiple hops

23

IBM Power8/7+

Inter-chip bandwidth lines to scale

SPARC T5-8 x86 E7


SPARC M7 Processor

• 32 SPARC Cores– 4th Generation CMT Core (S4)

– Dynamic, 8 Threads Per Core

• New Cache Organizations– Shared Level 2 Caches

– 64MB Shared Level 3 Cache

• DDR4 DRAM– +2TB Memory per Processor

– 2x-3x Memory Bandwidth

• 1 to 32 Processors SMP

• Technology: 20nm, 13ML

2.5x to 3.5x Performance of SPARC M6

4 cores 4 cores 4 cores 4 cores

4 cores 4 cores 4 cores 4 cores

SPARC M7

Fully-Connected 8 Processor SMP> 1 TB/s Delivered Bisection Bandwidth

[email protected]/solutions/big-data/


My NETWORKTrading

SYSTEMIs BETTER

THANYOURS

Trends driving innovation

● Switches silicon latencies are minimal and normalized

● Intelligence @ those expected latencies is now key

● Active feedback and intelligent control can reduce

trading platform latency, increase predictability and

profit

● Multi-tenancy economics are becoming more important

● Removal of dedicated security devices is a viable option

now

Multi tenancy: Why?

● Efficient use of costly infrastructure and real estate

● No-compromise virtualization of resources

● Removal of application or business silos

● Standardized operations and automation

● More performance, more redundancy, less

downtime due to human error

Multi tenancy: What technologies?

• VRF, NAT – virtualize the network, provide

isolation and security

• Programatic L2-4 control via API’s

• Application insight via in band and OOB system

monitoring

• Arista EOS: DANZ, LANZ, Burst Monitor, eAPI

Burst Monitor

Millisecond level reporting on interface burst activity with configurable intervals,

thresholds, and real time alerts. Provides application behavior insight and early

detection of burst based loss.

● Leverages high resolution ASIC counters

to provide real time burst detection

● Available on every port, RX and TX

● Provides burst insight without expensive

overlay infrastructure

● EOS provides programmable actions on

alerts

EOS BurstMonitor

Local logsSyslog

Trigger localor remote

action

Burst Monitor - Prototype in actionapl-7150S-24-1@12:09:35(config)#burstmonitor --help

Usage: burstmonitor [options] <interface number>

Options:

-h, --help show this help message and exit

-d, --debug print debug info

-r RXTOLERANCE, --rx-tolerance=RXTOLERANCE

RX burst size (% of bandwidth) which triggers syslog

messages (default=80)

-t TXTOLERANCE, --tx-tolerance=TXTOLERANCE

TX burst size (% of bandwidth) which triggers syslog

messages (default=80)

apl-7150S-24-1@12:06:24#show log | tail

Aug 15 12:06:28 apl-7150S-24-1 ibm-21: %INTERFACE-4-RX_BURST_DETECTED: RX burst (254688B/1892us) detected on port 21










Security innovations - Why

• Many organizations still use firewall classdevices for some transaction flows

• NAT and deep inspection drive “intelligence” atthe exchange edge

• Replacement of these devices reduces latencyand increases capacity, but hard to meet“compliance” with security teams

Security innovations - What

Intelligent Bypass and NAT - bypass firewalls orapplication aware appliances to reduce latency,appliance cost, and pps constraints. Applicationhealth checking and dynamic NAT configuration.

Application Inspection - Dig deeper into theapplication layer to make intelligent decisionsbeyond the network header

Firewalls: Intelligent Bypass

● Direct flows based on applications, users, devices, content, threats, and

more

● Reduce end to end latency and accelerate trusted flows without

compromising security

● Protect firewall and server resources from oversubscription or attack

● Leverage firewalls in low latency environments to scrutinize suspicious traffic

● Size firewall resources for baseline traffic levels, letting the switch handle the

bulk or burst flows during traffic peaks

● Leverage L2-4 filtering and dynamic NAT with state sync* to bypass

firewalls completely where appropriate

*coming soon

Application Inspection● Inspect beyond the network header for decision

making and security

● Steer traffic based on a flexible fixed offset parser

● Make intelligent decisions on the application or data

type

○ Route financial data on content

○ Forward messaging layer/middleware on topic

tags

○ Selectively permit/filter/redirect any interesting

data up to 112 bytes

● Dynamically configure DPI intelligence via eAPI

● All done @ wire rate with standard forwarding

latency