Logically a Linux cluster looks something like the following: Compute Nodes. user Head node. network



Similar documents
Cluster Implementation and Management; Scheduling

HPC Update: Engagement Model

Parallel Programming Survey

Sun Constellation System: The Open Petascale Computing Architecture

LS-DYNA Best-Practices: Networking, MPI and Parallel File System Effect on LS-DYNA Performance

Improved LS-DYNA Performance on Sun Servers

A Study on the Scalability of Hybrid LS-DYNA on Multicore Architectures

760 Veterans Circle, Warminster, PA Technical Proposal. Submitted by: ACT/Technico 760 Veterans Circle Warminster, PA

Comparing the performance of the Landmark Nexus reservoir simulator on HP servers

Cisco for SAP HANA Scale-Out Solution on Cisco UCS with NetApp Storage

Purchase of High Performance Computing (HPC) Central Compute Resources by Northwestern Researchers

Thematic Unit of Excellence on Computational Materials Science Solid State and Structural Chemistry Unit, Indian Institute of Science

INDIAN INSTITUTE OF TECHNOLOGY KANPUR Department of Mechanical Engineering

Michael Kagan.

Cray Gemini Interconnect. Technical University of Munich Parallel Programming Class of SS14 Denys Sobchyshak

PCIe Over Cable Provides Greater Performance for Less Cost for High Performance Computing (HPC) Clusters. from One Stop Systems (OSS)

Evaluation of Dell PowerEdge VRTX Shared PERC8 in Failover Scenario

Building a Top500-class Supercomputing Cluster at LNS-BUAP

Hadoop on the Gordon Data Intensive Cluster

Reference Architecture for Dell VIS Self-Service Creator and VMware vsphere 4

Protect SQL Server 2012 AlwaysOn Availability Group with Hitachi Application Protector

Private cloud computing advances

Removing Performance Bottlenecks in Databases with Red Hat Enterprise Linux and Violin Memory Flash Storage Arrays. Red Hat Performance Engineering

How To Build A Cisco Uniden Computing System

Support a New Class of Applications with Cisco UCS M-Series Modular Servers

How To Write An Article On An Hp Appsystem For Spera Hana

Cisco, Citrix, Microsoft, and NetApp Deliver Simplified High-Performance Infrastructure for Virtual Desktops

Architecting High-Speed Data Streaming Systems. Sujit Basu

CUTTING-EDGE SOLUTIONS FOR TODAY AND TOMORROW. Dell PowerEdge M-Series Blade Servers

Cluster Computing at HRI

What s New in Mike Bailey LabVIEW Technical Evangelist. uk.ni.com

Cost-effective, extremely manageable, high-density rack servers September Why Blade Servers? by Mark T. Chapman IBM Server Group

Legal Notices Introduction... 3

Visual UpTime Select Server Specifications

Accelerating Data Compression with Intel Multi-Core Processors

Agenda. HPC Software Stack. HPC Post-Processing Visualization. Case Study National Scientific Center. European HPC Benchmark Center Montpellier PSSC

A Smart Investment for Flexible, Modular and Scalable Blade Architecture Designed for High-Performance Computing.

Microsoft Exchange Server 2007 and Hyper-V high availability configuration on HP ProLiant BL680c G5 server blades

Lecture 1: the anatomy of a supercomputer

IBM BladeCenter H with Cisco VFrame Software A Comparison with HP Virtual Connect

EMC SYMMETRIX VMAX 20K STORAGE SYSTEM

EDUCATION. PCI Express, InfiniBand and Storage Ron Emerick, Sun Microsystems Paul Millard, Xyratex Corporation

THE SUN STORAGE AND ARCHIVE SOLUTION FOR HPC

How To Design A Data Centre

Copyright 2013, Oracle and/or its affiliates. All rights reserved.

Solution Brief July All-Flash Server-Side Storage for Oracle Real Application Clusters (RAC) on Oracle Linux

HP reference configuration for entry-level SAS Grid Manager solutions

Pivot3 Reference Architecture for VMware View Version 1.03

Terms of Reference Microsoft Exchange and Domain Controller/ AD implementation

MESOS CB220. Cluster-in-a-Box. Network Storage Appliance. A Simple and Smart Way to Converged Storage with QCT MESOS CB220

Overview of Requirements and Applications for 40 Gigabit and 100 Gigabit Ethernet

RLX Technologies Server Blades

Multi-Threading Performance on Commodity Multi-Core Processors

Performance Analysis and Tuning in Windows HPC Server Xavier Pillons Program Manager Microsoft Corp.

Cisco MCS 7825-H3 Unified Communications Manager Appliance

Arrow ECS sp. z o.o. Oracle Partner Academy training environment with Oracle Virtualization. Oracle Partner HUB

Oracle Exadata: The World s Fastest Database Machine Exadata Database Machine Architecture

Cray XT3 Supercomputer Scalable by Design CRAY XT3 DATASHEET

HP ProLiant Gen8 vs Gen9 Server Blades on Data Warehouse Workloads

Introduction to Cloud Computing

Managing Data Center Power and Cooling

SYSTEM SETUP FOR SPE PLATFORMS

CMS Tier-3 cluster at NISER. Dr. Tania Moulik

Binary search tree with SIMD bandwidth optimization using SSE

Diablo and VMware TM powering SQL Server TM in Virtual SAN TM. A Diablo Technologies Whitepaper. May 2015

Cisco UCS and Fusion- io take Big Data workloads to extreme performance in a small footprint: A case study with Oracle NoSQL database

Cisco UCS B-Series M2 Blade Servers

Cloud Computing through Virtualization and HPC technologies

ALPS Supercomputing System A Scalable Supercomputer with Flexible Services

HUAWEI Tecal E6000 Blade Server

Can High-Performance Interconnects Benefit Memcached and Hadoop?

HP ProLiant SL270s Gen8 Server. Evaluation Report

PCI Express Impact on Storage Architectures and Future Data Centers. Ron Emerick, Oracle Corporation

The Future of Computing Cisco Unified Computing System. Markus Kunstmann Channels Systems Engineer

Building Clusters for Gromacs and other HPC applications

PRIMERGY server-based High Performance Computing solutions

Parallel Computing with MATLAB

COSC 6374 Parallel Computation. Parallel I/O (I) I/O basics. Concept of a clusters

SummitStack in the Data Center

SAS Business Analytics. Base SAS for SAS 9.2

Enabling Technologies for Distributed and Cloud Computing

Comparison of Novell, Polyserve, and Microsoft s Clustering Performance

Running Native Lustre* Client inside Intel Xeon Phi coprocessor

SUN HARDWARE FROM ORACLE: PRICING FOR EDUCATION

Out-of-box comparison between Dell and HP blade servers

High Performance Computing in CST STUDIO SUITE

The Asterope compute cluster

The Advantages of Multi-Port Network Adapters in an SWsoft Virtual Environment

Transcription:

A typical Linux cluster consists of a group of compute nodes for executing parallel jobs and a head node to which users connect to build and launch their jobs. Often the compute nodes are connected to the head node by one network and to the other compute nodes by a second network. The second network is often used solely for communication between parallel program tasks and in some implementations may be a special low-latency, high-bandwidth network such as yrinet. Logically a Linux cluster looks something like the following: user Head node network Compute Nodes

NC State has implemented a Linux cluster using IB Blade Center hardware. The following pages describe the Blade Center in more detail focusing on the features of the Blade Center architecture that may impact the performance of parallel applications running on the university Linux cluster.

Blade Center has two major components: blades, which are dual-processor computers built from server grade parts; and chassis which provide power, cooling, management, and connectivity for fourteen blades. To the right is a cartoon of the major parts which make up a typical Blade Center blade. ual Gigabit Ethernet Blade ual rocessors 4 emory Slots 2 isk rive Bays ual Gigabit Ethernet All power, cooling, and connectivity supplied by chassis

NC State began purchasing blades more than a year ago. As with other computer systems, processor speeds on blades have increased steadily during the year. To date the university Linux cluster contains blades with Xeon processors running at three different clock speeds. 400 Hz 3.2 GB/s Total 3.2 GB/s Two metrics are shown for the various blades in the university cluster: the peak speed, taken to be the peak rate that the chip can perform floating point operations (expressed as Giga Floating oint Operations per Second GFLOS); and the peak memory bandwidth divided by the peak speed (expressed as Bytes/floating point operation). ual Gigabit Ethernet 2.4 GHz ual Xeon Blade 3 GB memory ual 40 GB disk eak Speed 4.8 GFLOS per processor eak Bytes/FLO 0.33

400 Hz 3.2 GB/s The initial NC State high performance computing (HC) cluster had 64 of these 2.8 GHz dual-xeon blades. Total 3.2 GB/s Two of the 2.4 GHz blades are available for code development and debugging. ual Gigabit Ethernet 2.8 GHz ual Xeon Blade 4 GB memory 40 GB disk eak Speed 5.6 GFLOS per processor eak Bytes/FLO 0.28 However, note that Bytes/FLO (B/F) for the 2.4 GHz blades is better (0.33) than for the 2.8 GHz blades (0.28). Compute intensive applications may need B/F=8 to run unimpeded by memory bandwidth limitations.

By June 2004 the university Linux cluster included 32 of the 3.06 GHz dual-xeon blades. Note that the system bus speed increased on these blades from 400 to 533 Hz. The resulting memory bandwidth improvement produced an improved B/F (0.35). 533 Hz 4.3 GB/s ual Gigabit Ethernet 3.06 GHz ual Xeon Blade 4 GB memory 40 GB disk eak Speed 6.12 GFLOS per processor eak Bytes/FLO 0.35

Chassis Redundant ower supplies Redundant Blowers anagement module ual GigE switches Space for 14 blades 533 Hz 4.3 GB/s Communication between blades in same chassis uses internal GigE switch fairly low latency communication full non-blocking blade to blade bandwidth ual Gigabit Ethernet orts (4) 14 blade slots 533 Hz 4.3 GB/s orts (4) ual Gigabit Ethernet

533 Hz 4.3 GB/s ual Gigabit Ethernet Communication between blades in different chassis pass through 2 additional switches longer latency communication reduced bandwidth 14 blades share 4 GigE connections 533 Hz 4.3 GB/s orts (4) Aggregated 533 Hz 4.3 GB/s ual Gigabit Ethernet orts (4) Switch ual Gigabit Ethernet 533 Hz 4.3 GB/s orts (4) Aggregated ual Gigabit Ethernet orts (4)

533 Hz 4.3 GB/s User access to blades is through a queuing system (LSF) controlled by a Linux head node (henry2) Interactive logins are supported only to henry2 not to individual blades NC State Campus Network ual Gigabit Ethernet 533 Hz 4.3 GB/s 533 Hz 4.3 GB/s henry2 ual Gigabit Ethernet 533 Hz 4.3 GB/s ual Gigabit Ethernet GigE Switch GigE Switch ual Gigabit Ethernet

storage4 /share storage5 /share3 /home henry2 /usr/local Storage available from cluster Shared network attached storage available from blades /home /usr/local (read only) /share /share3 Network attached storage available from henry2 /ncsu/volume1 /ncsu/volume2 NC State Campus Network T o t a t l 4. 3 G B / s T o t a l GigE Switch GigE Switch storage2 /ncsu/volume1 GigE Switch 4. 3 G B / s /ncsu/volume2