HPC performance applications on Virtual Clusters



Similar documents
Cloud Computing through Virtualization and HPC technologies

Enabling Technologies for Distributed Computing

PES. Batch virtualization and Cloud computing. Part 1: Batch virtualization. Batch virtualization and Cloud computing

Virtualization Technologies and Blackboard: The Future of Blackboard Software on Multi-Core Technologies

Enabling Technologies for Distributed and Cloud Computing

Virtualization. Types of Interfaces

Container-based operating system virtualization: a scalable, high-performance alternative to hypervisors

Cloud Operating Systems for Servers

StACC: St Andrews Cloud Computing Co laboratory. A Performance Comparison of Clouds. Amazon EC2 and Ubuntu Enterprise Cloud

GUEST OPERATING SYSTEM BASED PERFORMANCE COMPARISON OF VMWARE AND XEN HYPERVISOR

BENCHMARKING CLOUD DATABASES CASE STUDY on HBASE, HADOOP and CASSANDRA USING YCSB

Multi-core Programming System Overview

Microkernels, virtualization, exokernels. Tutorial 1 CSC469

Cloud Sure - Virtual Machines

Computing in High- Energy-Physics: How Virtualization meets the Grid

High-Density Network Flow Monitoring

Pros and Cons of HPC Cloud Computing

Multifaceted Resource Management for Dealing with Heterogeneous Workloads in Virtualized Data Centers

Performance tuning Xen

CUDA in the Cloud Enabling HPC Workloads in OpenStack With special thanks to Andrew Younge (Indiana Univ.) and Massimo Bernaschi (IAC-CNR)

Virtual Machine Synchronization for High Availability Clusters

Basics in Energy Information (& Communication) Systems Virtualization / Virtual Machines

CON9577 Performance Optimizations for Cloud Infrastructure as a Service

How To Install Linux Titan

Rackspace Cloud Databases and Container-based Virtualization

Hyper-V vs ESX at the datacenter

Eucalyptus: An Open-source Infrastructure for Cloud Computing. Rich Wolski Eucalyptus Systems Inc.

Best Practices for Virtualised SharePoint

Virtual Machine Monitors. Dr. Marc E. Fiuczynski Research Scholar Princeton University

Full and Para Virtualization

Virtual Machines. COMP 3361: Operating Systems I Winter

ZEN LOAD BALANCER EE v3.02 DATASHEET The Load Balancing made easy

Scalable Data Analysis in R. Lee E. Edlefsen Chief Scientist UserR! 2011

The QEMU/KVM Hypervisor

Efficient Load Balancing using VM Migration by QEMU-KVM

VMware Cloud Environment

The Xen of Virtualization

Xen and the Art of. Virtualization. Ian Pratt

Microsoft Hyper-V chose a Primary Server Virtualization Platform

ServerPronto Cloud User Guide

A general-purpose virtualization service for HPC on cloud computing: an application to GPUs

BlobSeer: Towards efficient data storage management on large-scale, distributed systems

An Experimental Study of Load Balancing of OpenNebula Open-Source Cloud Computing Platform

Architecting for the next generation of Big Data Hortonworks HDP 2.0 on Red Hat Enterprise Linux 6 with OpenJDK 7

Performance Evaluation of NAS Parallel Benchmarks on Intel Xeon Phi

High Performance Computing in CST STUDIO SUITE

<Insert Picture Here> Introducing Oracle VM: Oracle s Virtualization Product Strategy

Basics of Virtualisation

Leveraging Thin Hypervisors for Security on Embedded Systems

Intro to Virtualization

Multi-Threading Performance on Commodity Multi-Core Processors

MODULE 3 VIRTUALIZED DATA CENTER COMPUTE

HPC and Big Data. EPCC The University of Edinburgh. Adrian Jackson Technical Architect

Lecture 2 Cloud Computing & Virtualization. Cloud Application Development (SE808, School of Software, Sun Yat-Sen University) Yabo (Arber) Xu

PARALLELS CLOUD SERVER

Use of Hadoop File System for Nuclear Physics Analyses in STAR

Hadoop Architecture. Part 1

ZEN LOAD BALANCER EE v3.04 DATASHEET The Load Balancing made easy

CPET 581 Cloud Computing: Technologies and Enterprise IT Strategies. Virtualization of Clusters and Data Centers

Unifying Information Security

COLO: COarse-grain LOck-stepping Virtual Machine for Non-stop Service

Deploying Business Virtual Appliances on Open Source Cloud Computing

Xen and XenServer Storage Performance

Cloud Storage. Parallels. Performance Benchmark Results. White Paper.

Virtualization for Cloud Computing

Dheeraj K. Rathore 1, Dr. Vibhakar Pathak 2

Group Based Load Balancing Algorithm in Cloud Computing Virtualization

ACANO SOLUTION VIRTUALIZED DEPLOYMENTS. White Paper. Simon Evans, Acano Chief Scientist

Run-time Resource Management in SOA Virtualized Environments. Danilo Ardagna, Raffaela Mirandola, Marco Trubian, Li Zhang

PERFORMANCE ANALYSIS OF KERNEL-BASED VIRTUAL MACHINE

Hardware/Software Guidelines

COS 318: Operating Systems. Virtual Machine Monitors

SURFsara HPC Cloud Workshop

Chapter 14 Virtual Machines

Beyond the Hypervisor

Benchmarking Hadoop & HBase on Violin

Investigation of storage options for scientific computing on Grid and Cloud facilities

Virtualization with Windows

Virtualised MikroTik

CS423 Spring 2015 MP4: Dynamic Load Balancer Due April 27 th at 9:00 am 2015

Best Practices for Monitoring Databases on VMware. Dean Richards Senior DBA, Confio Software

A Cost-Evaluation of MapReduce Applications in the Cloud

Leveraging BlobSeer to boost up the deployment and execution of Hadoop applications in Nimbus cloud environments on Grid 5000

Installation Guide for Citrix XenServer 5.5

IOS110. Virtualization 5/27/2014 1

Performance of the Cloud-Based Commodity Cluster. School of Computer Science and Engineering, International University, Hochiminh City 70000, Vietnam

Cloud Computing. Alex Crawford Ben Johnstone

PERFORMANCE ENHANCEMENTS IN TreeAge Pro 2014 R1.0

HAVmS: Highly Available Virtual machine Computer System Fault Tolerant with Automatic Failback and close to zero downtime

Learning Objectives. Chapter 1: Networking with Microsoft Windows 2000 Server. Basic Network Concepts. Learning Objectives (continued)

Hyper-V R2: What's New?

An Introduction to Service Containers

Virtual Switching Without a Hypervisor for a More Secure Cloud

nanohub.org An Overview of Virtualization Techniques

Transcription:

Panagiotis Kritikakos EPCC, School of Physics & Astronomy, University of Edinburgh, Scotland - UK pkritika@epcc.ed.ac.uk 4 th IC-SCCE, Athens 7 th July 2010

This work investigates the performance of (Java) multi-threaded applications that execute on multi-core virtual machines that can perform as virtual clusters. Our investigation and comparison is carried across individual physical and virtual machines nodes with identical hardware configuration. The work presents an evaluation of various virtualisation configuration capabilities that we applied during the experimental process. The project was supported by EPCC at The University of Edinburgh and was carried out as an Honours (final year) Project in the undergraduate degree of BEng Internet Computing of the Edinburgh Napier University.

Until recently... Slowly increasing computational power Expensive multi-core systems Performance penalty of virtualisation HPC applications on large scale Grid computing...from today to the future... Emerging computational power Multi-core systems as a standard Virtualisation support by default HPC applications on various scales Cloud computing http://www.karmapsychicboutique.com/page/_files/past_life_regression_hypnosis_health_info%5b1%5d.jpg

Technical specifications 16 CPUs 16GB RAM SCSI storage Xen Hypervisor Scientific Linux Java Grande Benchmarking Suite Multi-threading disk I/O and networking benchmarks Virtual Clusters setup 4 x VMs (4 cores, 3.5GB RAM) 2 x VMs (8 cores, 7.5GB RAM) 4 x VMs (16 cores, 3.8GB RAM) http://www.dominie.com.sg/i/technical_img.jpg Experiments and statistics 10 execution loops starting from 10 threads and finishing with 100 threads Comparing results against physical system with Linux SMP kernel Used of the α > 0.95 significance level with Student's t-test

Software specifications Java Grande Benchmarking Suite - http://www2.epcc.ed.ac.uk/computing/research_activities/java_grande/threads/contents.html Thread synchronisation RayTracer Moldyn Multi-threaded disk I/O Multi-threaded TCP I/O Multi-threaded UDP I/O Operating System VM Benchmark Linux VM Benchmark Linux Virtual Machine Monitor Scientific Linux 5 x86_64 Virtualisation platform Xen Hypervisor Xen Hypervisor Physical hardware (CPU, Memory, Storage, Network)

Thread syncronisation (computationally intensive) Syncs performance on range of cores Significant difference in favour of the virtual machines P-value = 1.55 (10 threads)

Thread syncronisation (computationally intensive) Syncs performance on shared cores No statistical significant difference

Series (computationally intensive) No statistical significant difference

Sparse (memory intensive) No statistical significant difference up to 40 threads. From 50 -> 100, P-values = 1.71, 9.24, 6.82, 8.29, 4.44

RayTracer (memory and computationally intensive) Statistical significant difference in favour of the physical machine P-value = 1.46 (10 threads)

Moldyn (computationally intensive) Statistical significant difference only at 100 threads P-value = 2.61

Disk I/O Statistical significant difference in favour of the virtual machine P-value = 8.46 (100 threads)

Disk I/O Statistical significant difference in favour of the physical machine P-value = 9.87 (30 threads)

TCP I/O Statistical significant difference in favour of the physical machine P-value = 7.90 (10 threads)

UDP I/O No statistical significant difference

Some conclusions... Range of CPUs performance = Dedicated CPUs performance Rage of/dedicated CPUs performance > Shared CPUs performance Improved memory algorithms Memory chunks size play major role on performance Well performing disk I/O scheduling algorithm = Fast writes Poor I/O buffer rings = Slow reads Network handshaking and integrity checking overhead (TCP) Improved performance on connection-less network protocols (UDP)

Why using virtualisation? Reliability / Availability / Fault tolerance Portability Productivity / Development Management and some more Security Economical Greener The wide virtualisation support in modern commodity hardware shows great promise for virtualisation to become one of the default ICT infrastructure technologies of the future.

?Thank you Presentation http://www.epcc.ed.ac.uk/~pkritika/4thicscce.pdf