Studying Hardware and Software Trade-Offs for a Real-Life Web 2.0 Workload

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AUTHORS: STIJN POLFLIET ET. AL. BY: ALI NIKRAVESH Studying Hardware and Software Trade-Offs for a Real-Life Web 2.0 Workload

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Studying Hardware and Software Trade-Offs for a Real-Life Web 2.0 Workload. Authors: Stijn Polfliet et. al. By: Ali Nikravesh. Agenda. Introduction - What is the research question? What is authors’ approach to address the problem? Results. Introduction. Online Social Networking - PowerPoint PPT Presentation

Transcript of Studying Hardware and Software Trade-Offs for a Real-Life Web 2.0 Workload

Page 1: Studying Hardware and Software Trade-Offs for a Real-Life Web 2.0 Workload

AUTHORS:STIJN POLFLIET ET. AL.

BY:ALI NIKRAVESH

Studying Hardware and Software Trade-Offs for a

Real-Life Web 2.0 Workload

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Agenda

Introduction - What is the research question?What is authors’ approach to address the

problem?Results

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Introduction

Online Social Networking Facebook Twitter LinkedIn Netlog

Large number of users designing the servers and data centres to support social networking is challenging

Large scale data centres very much cost driven

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Introduction (contd.)

Factors that affect the cost of data centre: Hardware infrastructure Power and cooling infrastructure Operating expenditure Real estate

Increase performance increase cost Reduce cost reduce performance RESULT optimize performance per dollar

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Introduction (contd.)

So, which server should be bought? Depends on workload (interactive, batch, memory

intensive,…)

Idea: different workloads run on different hardware Correct hardware for correct task

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Introduction (contd.)

Research Question:

Scope: Social networking

Can we come up with a way of guiding service operators and owners of data centre to what hardware to purchase

for a given workload?

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Analysis

Social networking workload Multiple services run on multiple servers in a

distributed way in a data center

Fundamental difficulty performance of the ensemble can only be measured by modeling and evaluating the ensemble

Authors’ approach: A case study to evaluate how hardware choices affect end-user experience

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Case study

Netlog Is a social network available in 40 languages

Architecture WS 54% MC 16% DB 30%

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Experimental Setup

10 dual AMD Opteron 6168 servers12 cores per CPU64 GB of main memoryHDD & SSD

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Web Server Results

Three CPU frequency 1.9 GHz 1.3 GHz 800 Mhz

Frequency has a significant impact on response time.

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Web Server Results (contd.)

Number of cores per node Four-socket system is typically more than twice as

expensive as a two-socket system. As long as the total number of cores is constant, CPU

node is not affected much by node and core count

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Database Server

Database server: HDD versus SDDAlthough this is a significant reduction in the

longest response times observed, it may not justify the significantly higher cost of SSD versus HDD

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Memcached Server

Average CPU load for memcached server is typically below 5%

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Usecase

Hardware Purchasing Hardware vendor suggestion:

Web server: Intel Xeon X3480, 8 GB RAM, typical HDD ($1795)

Memcached server: Intel Xeon X3480, 16GB RAM, typical HDD ($2015)

Database server: Intel Xeon X3480, 16GB RAM, SSD ($2915) Total: $18615

Suggestion Web server the same as above. Memcached the same as Web

server but lower CPU frequency. DB the same as memcached but not SSD (Total: $15015 – 18.9% reduction)

Performance Evaluation: 50% of all requests will not experience any extra latency For other 50%, increase from 11% to 39%

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Thanks

Questions?

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Les important diagrams 1

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Comparing simulation response with actual response packets

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Les important diagrams 2

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Sampling in time

Traffic classified by its type

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Les important diagrams 3

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Warm-up

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Les important diagrams 4

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CPU load as a function of clock frequency

CPU load as a func of cores