VUG Why POWER8 is the platform of choice for Linux ... - …€¦ · Why POWER8 is the platform of...

© 2015 IBM Corporation

Why POWER8 is the platform of choice for Linux

IBM Competitive Project OfficeProving the Value of IBM Technology

Gary [email protected] 03/26/2015


Competitive Project Office

1. Architecture Matters

2. Best Price / Performance

1. Java Applications

2. Workload density

3. Mixed workloads

4. OLTP

5. Analytics

6. Big Data

POWER8 and Linux Provide the best customer value

Lower Cost

Better Service

Better Performance

Best ValuePurpose Built

2



Power Architecture is Purpose Built

POWER8 design point is for big workloads:

Intel design point is for multiple markets:

Smart Phones, Ultra Books, Desktop, Servers

Mobile

OLTP

POWER8

Big DataAnalytics

Cloud

ERP

Java

Social

3



POWER8 – Significant Improved Technology Leadership that is Ready for Bigger Workloads

More Cores

More Cache

More Threads

More Bandwidth

12 processor cores per socket (50% more than before) that deliver 2X better per core performance

What this meansBetter scale up performance, and more throughput per scale out server node

SMT8 – 8 dynamic threads per core, supporting SMT1, 2, 4, & 8 modes dynamically across VMs

What this meansYou choose – Deploy VM’s in the optimal SMT mode based on application needs

3X the on-chip cache as POWER7 – plus 128MB of new off-chip cache as well

What this meansMemory-intensive applications will perform better as memory latency is reduced

What this meansData-hungry applications (like Big Data & Analytics) will respond twice as fast and scale more efficiently.

3.5X more memory and 2.8X more I/O bandwidth than POWER7

A purposeful balanced design that delivers

new record performance

4



Architecture Matters When You Design A Micro Processor For Emerging Big Workloads

It’s not about the number of transistors,

it is what you do with them to handle Big Workloads

POWER7 to POWER8

45nm to

22nm

4.2 BillionTransistors

650 mm 2


567 mm

Westmere EX to Ivy Bridge EX


541 mm2


513 mm

POWER8 vs. Ivy Bridge EX

- 96 threads/socket vs. 30- 4x Memory Bandwidth- 3x on-die Cache- Cache latency reduced by 50%- 5x I/O Bandwidth- 15 metal layers vs. 9- eDRAM vs SRAM

POWER8 Unique Technology

- CAPI Technology- L4 Cache- Dynamic Overclocking

32nm to

22nm

5



Sandy Bridge EP

E5-x6xx

Ivy Bridge EP

E5-26xx v2

Ivy Bridge EX

E7-88xx v2

Haswell EP

E5-26xx v3

POWER8

Clock rates (GHz)

1.8–3.6 1.7-3.7 1.9-3.4 1.6-3.5 3.0-4.35 GHz

SMT options 1,2* 1, 2* 1, 2* 1, 2* 1, 2, 4, 8

Max Threads / sock

16 24 30 36 96

Max L1 Cache 32KB 32KB* 32KB* 64 KB 64KB

Max L2 Cache 256 KB 256 KB 256 KB 256KB 512 KB

Max L3 Cache 20 MB 30 MB 37.5 MB 45 MB 96 MB

Max L4 Cache 0 0 0 0 128 MB

Memory Bandwidth

31.4-51.2 GB/s

42.6-59.7 GB/s

68-85**

GB/s

51-68

GB/s

230 - 410 GB/sec

POWER8 Is Designed for Superior Performance

* Intel calls this Hyper-Threading Technology (No HT and with HT)*32KB running in “Non-RAS mode”, Only 16KB with ECC Error correction **85GB running in “Non-RAS mode” = dual-device error NOT supported

6



Intel’s Performance per Core is Not Increasing Over Previous Generation

2283

2069 20491921

0

500

1000

1500

2000

2500

RP

E2**

per

Co

re

2 Socket HP Servers

Sandy Bridge EP

2.9 GHz

16 cores

The number shown is best in each category (sockets and number of cores)

**Gartner RPE2 Details:http://www.gartner.com/technology/research/RPE2-methodology-details.jsp

RPE2** numbers are derived from the following six benchmark inputs:

SAP SD Two-Tier, TPC-C, TPC-H, SPECjbb2006 and two SPEC CPU2006 components

Ivy Bridge EP2.7 GHz

24 cores

Ivy Bridge EX2.8 GHz

30 cores

The data on this chart is derived from RPE2 from Gartner, Inc.'s Competitive Profile tool. © 2014 Gartner, Inc. and/or its affiliates. All rights reserved.

Haswell EP2.3 GHz

36 cores

7



POWER8 per Core Performance is Increasing!

0

500

1000

1500

2000

2500

3000

3500

PO

WE

R7

PO

WE

R7+

PO

WE

R8

RP

E2

** p

er

co

re

7303.55 GHz16 cores2 sockets

730+4.20 GHz16 cores2 sockets

S8243.52 GHz24 cores2 sockets

**Gartner RPE2 Details:http://www.gartner.com/technology/research/RPE2-methodology-details.jsp

RPE2** numbers are derived from the following six benchmark inputs:SAP SD Two-Tier, TPC-C, TPC-H, SPECjbb2006 and two SPEC CPU2006 components

The data on this chart is derived from RPE2 from Gartner, Inc.'s Competitive Profile tool. © 2014 Gartner, Inc. and/or its affiliates. All rights reserved.

The number shown is best in each category (sockets and number of cores)

This was a POWER8 Design Goal

8



Why Is This Important?

- More threads, cache- More memory bandwidth - More I/O bandwidth

- Fastest performance for all workloads- Ready to address new Big Data and Analytic workloads

Higher Performance per core- Lower Software costs and TCA- Fewer servers, lower support costs

CAPI - New Accelerator technologies

POWER8 Design Focus and Results

- More sockets per server- More cores per server

- Faster overall SERVER performance

Performance per core remains the same or is less

- Overall solution cost is higher

Intel Design Focus and Results

9



10






2. Workload density

3. Mixed workloads

4. OLTP

5. Analytics

6. Big Data


Lower Cost

Better Service

Better Performance


11



Test Harness Setup: POWER8 vs. Intel Ivy Bridge Using Friendly Bank WAS Application

RPT Workbench

1. Friendly Bank home page2. Logon3. Check account balances4. Transfer funds (2)5. View transaction history6. View profile 7. Logoff

DB2

System Under TestThese user

interactions are repeated by thousands of

simulated users

RPT AgentRPT Agent

RPT AgentRPT Agent

RPT AgentRPT Agent

RPT Agent

NE

TW

OR

K

Client Tier

Deploy

Server Tier

WebSphere

FriendlyBank

Application

WebSphere

FriendlyBank

Application

WebSphere

FriendlyBank

Application

WebSphere

FriendlyBank

Application

WebSphere

FriendlyBank

Application

WebSphere

FriendlyBank

Application

WebSphere

FriendlyBank

Application

Virtual Machines

PowerVM

VMware ESXi

Database Tier

DB2 DB2 DB2

Drive Application

Stats

DB2 DB2 DB2 DB2

12



POWER8 SMT delivers more performance per core than Intel Ivy Bridge

SMT1

SMT2

SMT4

SMT8

Intel Ivy Bridge EP (Hyper-Threading – Maximum)

2.1 – 2.3x

Time in Seconds

Th

rou

gh

pu

t p

er

Co

re

This is an IBM internal study designed to replicate a typical IBM customer workload usage in the marketplace. It consists of a POWER8 S824 with 24 cores, 3.52 GHz, 256GB Memory, AIX 7.1 TL3 SP3, WAS 8.5.5.1, DB2 9.7, JDK 7.0 FP1 compared to an Ivy Bridge EP 24 cores 2.7 GHz, 256 GB Memory, RHEL 6.5, WAS 8.5.5.1, DB2 9.7, JDK 7.0 FP1. The results were obtained under laboratory conditions, and not in an actual customer environment. IBM's internal workload studies are not benchmark applications, nor are they based on any benchmark standard. As such, customer applications, differences in the stack deployed, and other systems variations or testing conditions may produce different results and may vary based on actual configuration, applications, specific queries and other variables in a production environment.

13



90,760

131,696

171,920

188,184

0

20000

40000

60000

80000

100000

120000

140000

160000

180000

200000

SMT 1 SMT 2 SMT 4 SMT 8

Throughput on 24-core serversPOWER8 with RHEL

POWER8 and Linux demonstrate SMT throughput improvement compared to Ivy Bridge

SMT = Simultaneous Multi-Threading

2.1X

This is an IBM internal study designed to replicate a typical IBM customer workload usage in the marketplace. It consists of a POWER8 S824 with 24 cores, 256GB Memory, 3.52 GHz, RHEL 7.0, WAS 8.5.5.2, DB2 9.7, JDK 7.0 FP1 compared to an Ivy Bridge EP 24 cores, 256GB Memory, 2.7 GHz, RHEL 6.5, WAS 8.5.5.1, DB2 9.7, JDK 7.0 FP1. The results were obtained under laboratory conditions, and not in an actual customer environment. IBM's internal workload studies are not benchmark applications, nor are they based on any benchmark standard. As such, customer applications, differences in the stack deployed, and other systems variations or testing conditions may produce different results and may vary based on actual configuration, applications, specific queries and other variables in a production environment. Prices, where applicable, are based on published US list prices for both IBM and competitor, and the Total Cost of Acquisition (TCA) includes the list HW and SW prices and 3 years of service & support which is then divided by the number of transactions to get $ per user interaction per second.14



Linux on POWER8 with WAS Delivers Over TWICE the Throughput Compared to Ivy Bridge at 49% Lower Cost

188,184 User Interactions per second

WebSphere on platformDatabase off platform

$3.15 per UI per sec

DB2

Power S824

RHEL

WAS

2S/24 Core POWER8 (3.52 GHz)

PowerVM

4 VMs

RHEL

WAS

RHEL

WAS

RHEL

WASLinux …..

2.2xFaster

49%Lower cost per UI per sec

Web Application

Online Banking Workload v3.6

15






2. Workload density

3. Mixed workloads

4. OLTP

5. Analytics

6. Big Data


Lower Cost

Better Service

Better Performance


16



How many virtual machines can you run on a single server? It depends……

High Variability

Low Variability

Frequency of Occurrence

Perf

orm

ance

Small

Inte

ractions

per

second

Large

Workload

1. Size of the Workload 3. Variance of the Workload

2. Size of the Server

Number of cores

16 cores

24 cores

48 cores

Workload Density

Hypervisor

… 4. Workload ManagementMixed Workloads

High Priority

Low Priority

17



82

10

0

10

20

30

40

50

60

70

80

90

Nu

mb

er

of V

Ms p

er

se

rve

r

Workload Size – User Interactions per second

Online Banking Workload

Ivy Bridge-EP(24-cores 2.7 GHz) & Competitive Hypervisor

POWER8(24-cores 3.52 GHz) & PowerVM

2.3x

POWER8 Packs Up To 2.3x More Virtual Machines Than Intel On Same Number Of Cores

1.6x

2.1x

PowerVM / RHEL vs. Competitive Hypervisor / RHEL

728 1960 3920

36 23

116

This is an IBM internal study designed to replicate a typical IBM customer workload usage in the marketplace. It consists of a POWER8 S824 with 24 cores, 3.52 GHz, RHEL 6.5, WAS 8.5.5.1, DB2 9.7, JDK 7.0 FP1. compared to an Ivy Bridge EP 24 cores 2.7 GHz, RHEL 6.5, WAS 8.5.5.1, DB2 9.7, JDK 7.0 FP1 and a Competitive hypervisor. The results were obtained under laboratory conditions, and not in an actual customer environment. IBM's internal workload studies are not benchmark applications, nor are they based on any benchmark standard. As such, customer applications, differences in the stack deployed, and other systems variations or testing conditions may produce different results and may vary based on actual configuration, applications, specific queries and other variables in a production environment.18



82 Workloads

$7,218 per Workload

DB2

Power S824

RHEL

WAS

2S/24 Core POWER8 (3.52 GHz)

PowerVM

WebSphere on platform, Database off platform for both tests

RHEL

WAS

RHEL

WAS

RHEL

WAS…..

Online Banking Workloads each running

728 User Interactions/Sec

82 VMs

POWER8 with PowerVM Supports 2.3x More Large Workloads Than Ivy Bridge with Competitive Hypervisor

2.3xMore

Workloads

50%Lower cost per Workload

Web Application

Linux

19






2. Workload density

3. Mixed workloads

4. OLTP

5. Analytics

6. Big Data


Lower Cost

Better Service

Better Performance


20



Workload Prioritization Test Configuration –Apply a Constant and Variable Workload

60 Cores Intel Ivy Bridge EX - 2.80 GHz

WAS DB2

VMWare ESXi 5.5

. . . . . . .VMsIntel Ivy Bridge EXWAS DB2

40 Cores POWER E870 - 4.19 GHz

POWER8 E870WAS DB2

PowerVM

. . . . . . . WAS DB2

PowerVM

LPARs

High Priorities

RHEL 7 RHEL 7

This is an IBM internal study of a on-line banking workload in a controlled laboratory environment. The IBM system consists of one POWER8 E870 with 40 cores @ 4.19 GHz and 1 TB memory running RHEL 7.0, WAS ND 8.5.5.3, JDK 7.1 and DB2 v10.5 FP3. The Intel-based system consists of one Ivy Bridge EX (E7-4890 v2) with 60 cores @ 2.8 GHz and 1 TB memory running RHEL 7.0, WAS ND 8.5.5.3, JDK 7.1, and DB2 v10.5 FP3. Customer applications, differences in the systems deployed and other system variations or testing conditions may produce different results.

Low Priorities

High Priorities Low Priorities

4.75 Entitlement5 VPs

0.25 Entitlement5 VPs

950,000 Shares10 vCPUs

50,000 Shares10 vCPUs

RHEL 7 RHEL 7

21



High Priority Web Workload Running Standalone – Constant Load

High Priority throughput:98.16 Million transactions / 60 min

2.1x more

POWER8 transactions

vs. Intel

E870 40 coresConstant Load

22



High Priority Workload on E870 has Minimal Degradation when Low Priority Workload Added

5.8x More

Efficient

98.16M �� 87.36M (High Priority)

2.04M (Low Priority)

E870 40 cores

High Priority Workload

- 6.0% throughput reductiondue to workload mixing

- 5.0% given up for low priority workload entitlements

This is an IBM internal study of a on-line banking workload in a controlled laboratory environment. The IBM system consists of one POWER8 E870 with 40 cores @ 4.19 GHz and 1 TB memory running ARHEL 7.0, WAS ND 8.5.5.3, JDK 7.1 and DB2 v10.5 FP3. The Intel-based system consists of one Ivy Bridge EX (E7-4890 v2) with 60 cores @ 2.8 GHz and 1 TB memory running RHEL 7.0, WAS ND 8.5.5.3, JDK 7.1, and DB2 v10.5 FP3. Customer applications, differences in the systems deployed and other system variations or testing conditions may produce different results.

Constant Load

23



Comparison to determine which platform provides the lowest TCA over 3 yearswith variable loads

� IBM WebSphere ND 8.5

� IBM DB2 10 ESE

RHEL on Power E870

40 Cores

High Priority workloads

62.78M Txn/hr

High PriorityLPARs

62.78MTxn

Low PriorityLPARs

17.78MTxn

Low priority workloads

17.78M Txn/hr

73% lower cost

High priority online banking workloads driving a total of 62.78 M

transactions per hour and low priority discretionary workloads

34.77MTxn

17.78MTxn

Low PriorityWorkload

Run Mixed Workloads on the Same Server to Simplify and Save Money – Variable Load

28.01MTxn

High PriorityWorkloads

This is an IBM internal study of a on-line banking workload in a controlled laboratory environment. The IBM system consists of one POWER8 E870 with 40 cores @ 4.19 GHz and 1 TB memory running RHEL 7.0, WAS ND 8.5.5.3, JDK 7.1 and DB2 v10.5 FP3. The Intel-based system consists of one Ivy Bridge EX (E7-4890 v2) with 60 cores @ 2.8 GHz) and 1 TB memory running RHEL 7.0, WAS ND 8.5.5.3, JDK 7.1, and DB2 v10.5 FP3. Customer applications, differences in the systems deployed and other system variations or testing conditions may produce different results. Cost analysis based on 3 year total cost of acquisition of hardware, software and support services over a 3 year period. Prices for both IBM and competitor systems based on US list prices valid as of December 2014.

3 Year TCA: $3.49M

POWER8 E870 with RHEL 7.0

24






2. Workload density

3. Mixed workloads

4. OLTP

5. Analytics

6. Big Data


Lower Cost

Better Service

Better Performance


25



High level overview of OLTP brokerage workload used in this test

� Meant to be a more realistic OLTP workload, models a financial/stock brokerage system

– Sub-second response times

– Multiple access streams

� Data Application Architecture

– Multiple tables, indexes, and data types

– Requires referential integrity

– Complex transactions

– Multiple interacting subsystems

� Two Metrics can be used

1. Transactions per second (tps) measures total

transactions per sec

2. Completed Trades per second measures fully completed transactions

26



2.1xFaster

44%Lower cost per Completed

Trade/sec

27

988 Completed Trades per second

$3,326per Completed Trade/sec

Power S824with 24 cores512 GB RAMAIX 7.1, 64-bitFlashSystem 840

IBM Power S824 with Database Competitor

Competitor DB

600GB Brokerage Workload

Competitor DB on Power S824 is 2.1x Faster than Pre-Integrated Database Competitor at 44% Lower Cost

12c






2. Workload density

3. Mixed workloads

4. OLTP

5. Analytics

6. Big Data


Lower Cost

Better Service

Better Performance


28



3 Users doingcomplex reports

15 Users doingintermediate Reports

The business intelligence concurrent throughput test used in this study

42 Users doingsimple reports

42 Connections15 Connections

Each reportexecutes oneor more SQL queries(or statements)

Data Server

CR8 CR13CR9 IR1 IR2 IR3 IR6IR4 IR7 IR14IR12 SR5 SR15SR10 SR16

1 User

CR8 CR13CR9 IR1 IR2 IR3 IR6IR4 IR7 IR14IR12CR8 CR13CR9 IR1 IR2 IR3 IR6IR4 IR7 IR14IR12CR8 CR13CR9 IR1 IR2 IR3 IR6IR4 IR7 IR14IR12CR8 CR13CR9 IR1 IR2 IR3 IR6IR4 IR7 IR14IR12

Each userexecutes its ownversion of agiven report in afixed duration of2 hours

10 Users8 Users12 Users3 Users1 User 1 User 1 User2 Users2 Users2 Users1 User 2 Users2 Users 12 Users

3 Connections

29



Examples of Simple and Complex Queries

Example of a typical simple query: 2-3 parameters compared

Example of a typical complex query: 100-150 parameters compared

- QUERY 2A Simple_GoBusinessView_Dashboard select distinct "Product_forecast"."YEAR" "Year1" from "GOSL"."PRODUCT_FORECAST" "Product_forecast"

-- QUERY 3A Complex_TPA_PDFwith "Order_method_dimension14" as (select "Order_method_dimension"."ORDER_METHOD_KEY" "ORDER_METHOD_KEY" , min("Order_method_dimension"."ORDER_METHOD_EN") "Order_method" from "GOSLDW"."ORDER_METHOD_DIMENSION" "Order_method_dimension"group by "Order_method_dimension"."ORDER_METHOD_KEY"), "Product_line15" as (select "Product_line"."PRODUCT_LINE_CODE" "PRODUCT_LINE_CODE" , min("Product_line"."PRODUCT_LINE_EN") "Product_line" from "GOSLDW"."PRODUCT_LINE" "Product_line"group by "Product_line"."PRODUCT_LINE_CODE"), "Sales_territory_dimension12" as (select "Sales_territory_dimension"."COUNTRY_KEY" "COUNTRY_KEY" , "Sales_territory_dimension"."COUNTRY_CODE" "COUNTRY_CODE" , "Sales_territory_dimension"."SALES_TERRITORY_KEY" "SALES_TERRITORY_KEY" , "Sales_territory_dimension"."SALES_TERRITORY_CODE" "SALES_TERRITORY_CODE" , "Sales_territory_dimension"."COUNTRY_EN" "COUNTRY_EN" , "Sales_territory_dimension"."FLAG_IMAGE" "FLAG_IMAGE31" , "Sales_territory_dimension"."SALES_TERRITORY_EN" "SALES_TERRITORY_EN" from "GOSLDW"."SALES_TERRITORY_DIMENSION" "Sales_territory_dimension"), "Gender_lookup13" as (select "Gender_lookup"."GENDER_CODE" "GENDER_CODE" , min("Gender_lookup"."GENDER") "GENDER" from "GOSLDW"."GENDER_LOOKUP" "Gender_lookup"where "Gender_lookup"."LANGUAGE" = 'EN'group by "Gender_lookup"."GENDER_CODE"), "Retailer__model_" as (select "Retailer_dimension11"."RETAILER_SITE_KEY" "Retailer_site_key" , "Sales_territory_dimension12"."SALES_TERRITORY_KEY" "Sales_territory_key" , "Sales_territory_dimension12"."SALES_TERRITORY_EN" "Sales_territory" from "GOSLDW"."RETAILER_DIMENSION" "Retailer_dimension11", "Sales_territory_dimension12", "Gender_lookup13"where "Retailer_dimension11"."GENDER_CODE" = "Gender_lookup13"."GENDER_CODE" and "Retailer_dimension11"."COUNTRY_KEY" = "Sales_territory_dimension12"."COUNTRY_KEY") select "Order_method_dimension14"."ORDER_METHOD_KEY" "Order_method0key" , "Order_method_dimension14"."Order_method" "Order_method1" , "Product_line15"."PRODUCT_LINE_CODE" "Product_linekey" , "Product_line15"."Product_line" "Product_line0" , "Retailer__model_"."Sales_territory_key" "Retailer_territorykey" , "Retailer__model_"."Sales_territory" "Sales_territory" , cast("Time_dimension17"."CURRENT_YEAR" as char(4)) "Yearkey" , cast("Time_dimension17"."QUARTER_KEY" as char(6)) "Quarterkey" , cast("Time_dimension17"."MONTH_KEY" as char(6)) "Monthkey" , sum("Sales_fact18"."GROSS_PROFIT") "Gross_profit“ from "Order_method_dimension14", "Product_line15", "Retailer__model_", "GOSLDW"."TIME_DIMENSION" "Time_dimension17", "GOSLDW"."SALES_FACT" "Sales_fact18", "GOSLDW"."PRODUCT_TYPE" "Product_type19", "GOSLDW"."PRODUCT_DIMENSION" "Product_dimension20"where "Order_method_dimension14"."ORDER_METHOD_KEY" = "Sales_fact18"."ORDER_METHOD_KEY" and "Product_dimension20"."PRODUCT_KEY" = "Sales_fact18"."PRODUCT_KEY" and "Product_type19"."PRODUCT_TYPE_CODE" = "Product_dimension20"."PRODUCT_TYPE_CODE" and "Product_line15"."PRODUCT_LINE_CODE" = "Product_type19"."PRODUCT_LINE_CODE" and "Time_dimension17"."DAY_KEY" = "Sales_fact18"."ORDER_DAY_KEY" and "Retailer__model_"."Retailer_site_key" = "Sales_fact18"."RETAILER_SITE_KEY"group by "Order_method_dimension14"."ORDER_METHOD_KEY", "Order_method_dimension14"."Order_method", "Product_line15"."PRODUCT_LINE_CODE", "Product_line15"."Product_line", "Retailer__model_"."Sales_territory_key", "Retailer__model_"."Sales_territory", cast("Time_dimension17"."CURRENT_YEAR" as char(4)), cast("Time_dimension17"."QUARTER_KEY" as char(6)), cast("Time_dimension17"."MONTH_KEY" as char(6))

30



DB2 BLU & Cognos on POWER8 delivers analytics reports faster than Ivy Bridge

40xFaster

Intermediate Reports

747x Faster

Complex Reports

3.0x LowerPrice

BLU Lightening Test (Telecom Analytics workload)

System Cost$263,730

DB2 BLU & Cognos on POWER8

7,758 Intermediate Reports per Hour

212 Complex Reports per Hour

185 Intermediate Reports per Hour

0.27 Complex Reports per Hour

S824, 3.52 GHz24-cores

S822L, 3.4 GHz16-cores active

18xFaster

Simple Reports

43,944 Simple Reports per Hour

2,267Simple Reports per Hour

31






2. Workload density

3. Mixed workloads

4. OLTP

5. Analytics

6. Big Data


Lower Cost

Better Service

Better Performance


32



BigInsights on POWER8 beats the competition with TeraSort benchmark

0.670.73

0

0.2

0.4

0.6

0.8

1

1.2

1.4

GB

/co

re/m

in

Normalized PerformanceGB / Core / Min

1.7X

HP Ivy Bridge EP with

Cloudera

CiscoSandy Bridge

EP with Apache Hadoop

POWER8 with

BigInsights

1.27

0.75

SGIIvy Bridge EP with

Cloudera

Cisco Paper - http://www.cisco.com/c/dam/en/us/solutions/collateral/borderless-networks/advanced-services/le_tera.pdfSGI Paper - http://www.sgi.com/pdfs/4440.pdfHP Ivy Bridge with Cloudera and POWER8 with BigInsights were tested in IBM laboratories

Xeon E5-266516 nodes256 cores

10 TB

Xeon E5-2630v224 nodes288 cores

10 TB

Xeon E5-2697v28 nodes

192 cores1 TB

S822L8 nodes

192 cores10 TB

33



IBM BigInsights with Big SQL delivers Big Data queries faster than Ivy Bridge

4.4x LowerPrice

Performance

Modern Business Intelligent workload queries

BigInsights v3.0 on 8 S822L data nodes

S822L, 3.3 GHz24 cores 256 GB MemoryRHEL 6.5

11.2xFaster Time to complete queries

in 7 concurrent streams

8 hours 40 min

34



POWER8 and Linux – The Best Value




2. Workload density

3. Mixed workloads

4. OLTP

5. Analytics

6. Big Data

Lower Cost

Better Service

Better Performance


35

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