Introduction to SDSC systems and data analytics software packages "

Size: px
Start display at page:

Download "Introduction to SDSC systems and data analytics software packages ""

Transcription

1 Introduction to SDSC systems and data analytics software packages " Mahidhar Tatineni SDSC Summer Institute August 05, 2013

2 Getting Started" System Access Logging in Linux/Mac Use available ssh clients." ssh clients for windows Putty, Cygwin" Login hosts for the machines:" gordon.sdsc.edu, trestles.sdsc.edu" For NSF Resources Users can login via the XSEDE user portal: "

3 Access Via Science Gateways (XSEDE) " Community-developed set of tools, applications, and data that are integrated via a portal. Enables researchers of particular communities to use HPC resources through portals without the complication of getting familiar with the hardware and software details. Allows them to focus on the scientific goals. CIPRES gateway hosted by SDSC PIs enables large scale phylogenetic reconstructions using applications such as MrBayes, Raxml, and Garli. Enabled ~200 publications in 2012 and accounts for a significant fraction of the XSEDE users. NSG portal hosted by SDSC PIs enables HPC jobs for neuroscientists.

4 Data Transfer (scp, globus-url-copy)" scp is o.k. to use for simple file transfers and small file sizes (<1GB). Example: $ scp w.txt train40@gordon.sdsc.edu:/home/train40/w.txt 100% 15KB 14.6KB/s 00:00 " globus-url-copy for large scale data transfers between XD resources (and local machines w/ a globus client). Uses your XSEDE-wide username and password " Retrieves your certificate proxies from the central server" Highest performance between XSEDE sites, uses striping across multiple servers and multiple threads on each server." 4

5 Data Transfer globus-url-copy" Step 1: Retrieve certificate proxies: $ module load globus" $ myproxy-logon l xsedeusername" Enter MyProxy pass phrase:" A credential has been received for user xsedeusername in /tmp/ x509up_u " " Step 2: Initiate globus-url-copy: $ globus-url-copy -vb -stripe -tcp-bs 16m -p 4 gsiftp:// gridftp.ranger.tacc.teragrid.org:2811///scratch/00342/username/test.tar gsiftp:// trestles-dm2.sdsc.xsede.org:2811///oasis/scratch/username/temp_project/testgordon.tar" Source: gsiftp://gridftp.ranger.tacc.teragrid.org:2811///scratch/00342/username/" Dest: gsiftp://trestles-dm2.sdsc.xsede.org:2811///oasis/scratch/username/ temp_project/" test.tar -> test-gordon.tar" 5

6 Data Transfer Globus Online" Works from Windows/Linux/Mac via globus online website: Gordon, Trestles, and Triton endpoints already exist. Authentication can be done using XSEDEwide username and password for the NSF resources. Globus Connect application (available for Windows/Linux/Mac can turn your laptop/ 6 desktop into an endpoint.

7 Data Transfer Globus Online" Step 1: Create a globus online account 7

8 Data Transfer Globus Online" 8

9 Data Transfer Globus Online" Step 2: Set up local machine as endpoint using Globus Connect. 9

10 Data Transfer Globus Online" Step 3: Pick Endpoints and Initiate Transfers 10

11 Data Transfer Globus Online" 11

12 SDSC HPC Resources: Running Jobs "

13 Running Batch Jobs" All clusters use the TORQUE/PBS resource manager for running jobs. TORQUE allows the user to submit one or more jobs for execution, using parameters specified in a job script. NSF resources have the Catalina scheduler to control the workload. Copy hands on examples directory from: cp r /home/diag/si2013."

14 Gordon : Filesystems" Lustre filesystems Good for scalable large block I/O Accessible from both native and vsmp nodes." /oasis/scratch/gordon 1.6 PB, peak measured performance ~50GB/s on reads and writes." /oasis/projects 400TB" SSD filesystems /scratch local to each native compute node 300 GB each." /scratch on vsmp node 4.8TB of SSD based filesystem." NFS filesystems (/home) 14

15 Gordon Compiling/Running Jobs" Copy the SI2013 directory: cp r /home/diag/si2013 ~/" "" Change to workshop directory: cd ~/SI2013" Verify modules loaded: $ module li" Currently Loaded Modulefiles:" 1) binutils/2.22 2) intel/2011 3) mvapich2_ib/1.8a1p1" Compile the MPI hello world code: mpif90 -o hello_world hello_mpi.f90" " Verify executable has been created: ls -lt hello_world " -rwxr-xr-x 1 mahidhar hpss May 15 21:22 hello_world"

16 Gordon: Compiling/Running Jobs" Job Queue basics: Gordon uses the TORQUE/PBS Resource Manager with the Catalina scheduler to define and manage job queues." Native/Regular compute (Non-vSMP) nodes accessible via normal queue." vsmp node accessible via vsmp queue." Workshop examples illustrate use of both the native and vsmp nodes. hello_native.cmd script for running hello world example on native nodes (using MPI)." hello_vsmp.cmd script for running hello world example on vsmp nodes (using OpenMP)" Hands on section of tutorial has several scenarios"

17 Gordon: Hello World on native (non-vsmp) nodes" The submit script (located in the workshop directory) is hello_native.cmd #/bin/bash #PBS -q normal #PBS -N hello_native #PBS -l nodes=4:ppn=1:native #PBS -l walltime=0:10:00 #PBS -o hello_native.out #PBS -e hello_native.err #PBS -V ##PBS -M ##PBS -m abe #PBS A gue998 cd $PBS_O_WORKDIR mpirun_rsh -hostfile $PBS_NODEFILE -np 4./hello_world

18 Gordon: Output from Hello World " " Submit job using qsub hello_native.cmd $ qsub hello_native.cmd " gordon-fe2.local" " Output: $ more hello_native.out node 2 : Hello world node 1 : Hello world node 3 : Hello world node 0 : Hello world Nodes: gcn gcn gcn gcn-15-68

19 Compiling OpenMP Example" Change to the SI2013 directory: cd ~/SI2013" " Compile using openmp flag: ifort -o hello_vsmp -openmp hello_vsmp.f90" " Verify executable was created: ls -lt hello_vsmp" -rwxr-xr-x 1 train61 gue May 9 10:31 hello_vsmp"

20 Hello World on vsmp node (using OpenMP)" hello_vsmp.cmd #/bin/bash" #PBS -q vsmp" #PBS -N hello_vsmp" #PBS -l nodes=1:ppn=16:vsmp" #PBS -l walltime=0:10:00" #PBS -o hello_vsmp.out" #PBS -e hello_vsmp.err" #PBS -V" ##PBS -M ##PBS -m abe" #PBS -A gue998" cd $PBS_O_WORKDIR" export LD_PRELOAD=/opt/ScaleMP/libvsmpclib/0.1/lib64/libvsmpclib.so" export PATH="/opt/ScaleMP/numabind/bin:$PATH"" export KMP_AFFINITY=compact,verbose,0,`numabind --offset 8`" export OMP_NUM_THREADS=8"./hello_vsmp"

21 Hello World on vsmp node (using OpenMP)" Code written using OpenMP PROGRAM OMPHELLO" INTEGER TNUMBER" INTEGER OMP_GET_THREAD_NUM " " $OMP PARALLEL DEFAULT(PRIVATE)" TNUMBER = OMP_GET_THREAD_NUM()" PRINT *, 'HELLO FROM THREAD NUMBER = ', TNUMBER" $OMP END PARALLEL " " STOP" END "

22 vsmp OpenMP binding info (from hello_vsmp.err file)" " " " OMP: Info #147: KMP_AFFINITY: Internal thread 0 bound to OS proc set {504}" OMP: Info #147: KMP_AFFINITY: Internal thread 1 bound to OS proc set {505}" OMP: Info #147: KMP_AFFINITY: Internal thread 2 bound to OS proc set {506}" OMP: Info #147: KMP_AFFINITY: Internal thread 3 bound to OS proc set {507}" OMP: Info #147: KMP_AFFINITY: Internal thread 4 bound to OS proc set {508}" OMP: Info #147: KMP_AFFINITY: Internal thread 5 bound to OS proc set {509}" OMP: Info #147: KMP_AFFINITY: Internal thread 7 bound to OS proc set {511}" OMP: Info #147: KMP_AFFINITY: Internal thread 6 bound to OS proc set {510}"

23 Hello World (OpenMP version) Output" HELLO FROM THREAD NUMBER = 1 HELLO FROM THREAD NUMBER = 6 HELLO FROM THREAD NUMBER = 5 HELLO FROM THREAD NUMBER = 4 HELLO FROM THREAD NUMBER = 3 HELLO FROM THREAD NUMBER = 2 HELLO FROM THREAD NUMBER = 0 HELLO FROM THREAD NUMBER = 7 Nodes: gcn

24 Running on vsmp nodes - Guidelines" Identify type of job serial (large memory), threaded (pthreads, openmp), or MPI Workshop directory has examples for the different scenarios. Hands on section will walk through different types. Use affinity in conjunction with automatic process placement utility (numabind). Optimized MPI (mpich2 tuned for vsmp) is available.

25 vsmp Guidelines for Threaded Codes" 25

26 OpenMP Matrix Multiply Example" #/bin/bash" #PBS -q vsmp" #PBS -N openmp_mm_vsmp" #PBS -l nodes=1:ppn=16:vsmp" #PBS -l walltime=0:10:00" #PBS -o openmp_mm_vsmp.out" #PBS -e openmp_mm_vsmp.err" #PBS -V" ##PBS -M ##PBS -m abe" #PBS -A gue998" cd $PBS_O_WORKDIR" # Setting stacksize to unlimited." ulimit -s unlimited" # ScaleMP preload library that throttles down unnecessary system calls." export LD_PRELOAD=/opt/ScaleMP/libvsmpclib/0.1/lib64/libvsmpclib.so" source./intel.sh" export MKL_VSMP=1" # Path to NUMABIND." export PATH=/opt/ScaleMP/numabind/bin:$PATH" np=8" tag=`date +%s`" # Dynamic binding of OpenMP threads using numabind." export KMP_AFFINITY=compact,verbose,0,`numabind --offset $np`" export OMP_NUM_THREADS=$np" /usr/bin/time./openmp-mm > log-openmp-nbind-$np-$tag.txt 2>&1 " " 26

27 Using SSD Scratch (Native Nodes)" #/bin/bash #PBS -q normal #PBS -N ior_native #PBS -l nodes=1:ppn=16:native #PBS -l walltime=00:25:00 #PBS -o ior_scratch_native.out #PBS -e ior_scratch_native.err #PBS -V ##PBS -M ##PBS -m abe #PBS -A gue998 cd /scratch/$user/$pbs_jobid mpirun_rsh -hostfile $PBS_NODEFILE -np 4 $HOME/SI2013/IOR-gordon -i 1 -F b 16g -t 1m -v -v > IOR_native_scratch.log cp /scratch/$user/$pbs_jobid/ior_native_scratch.log $PBS_O_WORKDIR/

28 Using SSD Scratch (Native Nodes)" Snapshot on the node during the run: $ pwd" /scratch/mahidhar/72251.gordon-fe2.local" $ ls -lt" total " -rw-r--r-- 1 mahidhar hpss May 15 23:48 testfile " -rw-r--r-- 1 mahidhar hpss May 15 23:48 testfile " -rw-r--r-- 1 mahidhar hpss May 15 23:48 testfile " -rw-r--r-- 1 mahidhar hpss May 15 23:48 testfile " -rw-r--r-- 1 mahidhar hpss 1101 May 15 23:48 IOR_native_scratch.log" Performance from single node (in log file copied back): Max Write: MiB/sec ( MB/sec)" Max Read: MiB/sec ( MB/sec)" 28

29 Running Jobs on Trestles" All nodes on Trestles are identical. However, nodes have 32 cores and can be shared." Scheduler is again PBS + Catalina. " Two options" normal Exclusive access to compute nodes. Allocation charged for 32 cores / node." shared Shared access. Allocation charged based on number of cores requested."

30 Data Intensive Computing & Viz Stack" Gordon was designed to enable data intensive computing (details in following slides). Additionally, some of the Triton nodes have large memory (up to 512 GB) to aid in such processing. All clusters have access to the high speed lustre filesystem (Data Oasis: details in separate presentation) with an aggregated peak measured data rate of 100GB/s. Several libraries and packages have been installed to enable data intensive computing and visualization: R Software environment for statistical computing and graphics." Weka Tools for data analysis and predictive modeling" RapidMiner Environment for machine learning, data mining, text mining, and predictive analytics" Octave" Matlab " VisIt" Paraview" The myhadoop infrastructure was developed to enable use Hadoop for distributed data intensive analysis.

31 Hands On Example - Hadoop" Examples in /home/diag/si2013/hadoop Simple benchmark examples: TestDFS_2.cmd TestDFS example to benchmark HDFS performance." TeraSort_2.cmd Sorting performance benchmark."

32 TestDFS Example" PBS variables part: #/bin/bash #PBS -q normal #PBS -N hadoop_job #PBS -l nodes=2:ppn=1 #PBS -o hadoop_dfstest_2.out #PBS -e hadoop_dfstest_2.err #PBS -V

33 TestDFS example" Set up Hadoop environment variables: # Set this to location of myhadoop on gordon export MY_HADOOP_HOME="/opt/hadoop/contrib/myHadoop" # Set this to the location of Hadoop on gordon export HADOOP_HOME="/opt/hadoop" #### Set this to the directory where Hadoop configs should be generated # Don't change the name of this variable (HADOOP_CONF_DIR) as it is # required by Hadoop - all config files will be picked up from here # # Make sure that this is accessible to all nodes export HADOOP_CONF_DIR="/home/$USER/config"

34 TestDFS Example" #### Set up the configuration # Make sure number of nodes is the same as what you have requested from PBS # usage: $MY_HADOOP_HOME/bin/configure.sh -h echo "Set up the configurations for myhadoop" ### Create a hadoop hosts file, change to ibnet0 interfaces - DO NOT REMOVE - sed 's/$/.ibnet0/' $PBS_NODEFILE > $PBS_O_WORKDIR/hadoophosts.txt export PBS_NODEFILEZ=$PBS_O_WORKDIR/hadoophosts.txt ### Copy over configuration files $MY_HADOOP_HOME/bin/configure.sh -n 2 -c $HADOOP_CONF_DIR ### Point hadoop temporary files to local scratch - DO NOT REMOVE - sed -i 's@haddtemp@'$pbs_jobid'@g' $HADOOP_CONF_DIR/hadoopenv.sh

35 TestDFS Example" #### Format HDFS, if this is the first time or not a persistent instance echo "Format HDFS" $HADOOP_HOME/bin/hadoop --config $HADOOP_CONF_DIR namenode -format echo sleep 1m #### Start the Hadoop cluster echo "Start all Hadoop daemons" $HADOOP_HOME/bin/start-all.sh #$HADOOP_HOME/bin/hadoop dfsadmin -safemode leave echo

36 TestDFS Example" #### Run your jobs here echo "Run some test Hadoop jobs" $HADOOP_HOME/bin/hadoop jar $HADOOP_HOME/hadooptest jar TestDFSIO -write -nrfiles 8 -filesize buffersize sleep 30s $HADOOP_HOME/bin/hadoop jar $HADOOP_HOME/hadooptest jar TestDFSIO -read - nrfiles 8 -filesize buffersize echo #### Stop the Hadoop cluster echo "Stop all Hadoop daemons" $HADOOP_HOME/bin/stop-all.sh echo

37 Running the TestDFS example" Submit the job: qsub TestDFS_2.cmd " " Check the job is running (qstat) Once the job is running the hadoophosts.txt file is created. For example on a sample run: $ more hadoophosts.txt " gcn ibnet0" gcn ibnet0" "

38 Summary, Q/A " Access options ssh clients, XSEDE User Portal Data Transfer options scp, globus-url-copy (gridftp), globus online, and XSEDE User Portal File Manager. Two queues normal (native, non-vsmp) and vsmp. Follow guidelines for serial, OpenMP, Pthreads, MPI jobs on the vsmp nodes. Use SSD local scratch where possible. Excellent for codes like Gaussian, Abaqus. 38

Introduction to Hadoop on the SDSC Gordon Data Intensive Cluster"

Introduction to Hadoop on the SDSC Gordon Data Intensive Cluster Introduction to Hadoop on the SDSC Gordon Data Intensive Cluster" Mahidhar Tatineni SDSC Summer Institute August 06, 2013 Overview "" Hadoop framework extensively used for scalable distributed processing

More information

Hadoop Deployment and Performance on Gordon Data Intensive Supercomputer!

Hadoop Deployment and Performance on Gordon Data Intensive Supercomputer! Hadoop Deployment and Performance on Gordon Data Intensive Supercomputer! Mahidhar Tatineni, Rick Wagner, Eva Hocks, Christopher Irving, and Jerry Greenberg! SDSC! XSEDE13, July 22-25, 2013! Overview!!

More information

Introduction to Running Hadoop on the High Performance Clusters at the Center for Computational Research

Introduction to Running Hadoop on the High Performance Clusters at the Center for Computational Research Introduction to Running Hadoop on the High Performance Clusters at the Center for Computational Research Cynthia Cornelius Center for Computational Research University at Buffalo, SUNY 701 Ellicott St

More information

Hadoop on the Gordon Data Intensive Cluster

Hadoop on the Gordon Data Intensive Cluster Hadoop on the Gordon Data Intensive Cluster Amit Majumdar, Scientific Computing Applications Mahidhar Tatineni, HPC User Services San Diego Supercomputer Center University of California San Diego Dec 18,

More information

NEC HPC-Linux-Cluster

NEC HPC-Linux-Cluster NEC HPC-Linux-Cluster Hardware configuration: 4 Front-end servers: each with SandyBridge-EP processors: 16 cores per node 128 GB memory 134 compute nodes: 112 nodes with SandyBridge-EP processors (16 cores

More information

The Maui High Performance Computing Center Department of Defense Supercomputing Resource Center (MHPCC DSRC) Hadoop Implementation on Riptide - -

The Maui High Performance Computing Center Department of Defense Supercomputing Resource Center (MHPCC DSRC) Hadoop Implementation on Riptide - - The Maui High Performance Computing Center Department of Defense Supercomputing Resource Center (MHPCC DSRC) Hadoop Implementation on Riptide - - Hadoop Implementation on Riptide 2 Table of Contents Executive

More information

Work Environment. David Tur HPC Expert. HPC Users Training September, 18th 2015

Work Environment. David Tur HPC Expert. HPC Users Training September, 18th 2015 Work Environment David Tur HPC Expert HPC Users Training September, 18th 2015 1. Atlas Cluster: Accessing and using resources 2. Software Overview 3. Job Scheduler 1. Accessing Resources DIPC technicians

More information

HPC at IU Overview. Abhinav Thota Research Technologies Indiana University

HPC at IU Overview. Abhinav Thota Research Technologies Indiana University HPC at IU Overview Abhinav Thota Research Technologies Indiana University What is HPC/cyberinfrastructure? Why should you care? Data sizes are growing Need to get to the solution faster Compute power is

More information

Using WestGrid. Patrick Mann, Manager, Technical Operations Jan.15, 2014

Using WestGrid. Patrick Mann, Manager, Technical Operations Jan.15, 2014 Using WestGrid Patrick Mann, Manager, Technical Operations Jan.15, 2014 Winter 2014 Seminar Series Date Speaker Topic 5 February Gino DiLabio Molecular Modelling Using HPC and Gaussian 26 February Jonathan

More information

Introduction to Supercomputing with Janus

Introduction to Supercomputing with Janus Introduction to Supercomputing with Janus Shelley Knuth shelley.knuth@colorado.edu Peter Ruprecht peter.ruprecht@colorado.edu www.rc.colorado.edu Outline Who is CU Research Computing? What is a supercomputer?

More information

Getting Started with HPC

Getting Started with HPC Getting Started with HPC An Introduction to the Minerva High Performance Computing Resource 17 Sep 2013 Outline of Topics Introduction HPC Accounts Logging onto the HPC Clusters Common Linux Commands Storage

More information

The CNMS Computer Cluster

The CNMS Computer Cluster The CNMS Computer Cluster This page describes the CNMS Computational Cluster, how to access it, and how to use it. Introduction (2014) The latest block of the CNMS Cluster (2010) Previous blocks of the

More information

Batch Scripts for RA & Mio

Batch Scripts for RA & Mio Batch Scripts for RA & Mio Timothy H. Kaiser, Ph.D. tkaiser@mines.edu 1 Jobs are Run via a Batch System Ra and Mio are shared resources Purpose: Give fair access to all users Have control over where jobs

More information

Hodor and Bran - Job Scheduling and PBS Scripts

Hodor and Bran - Job Scheduling and PBS Scripts Hodor and Bran - Job Scheduling and PBS Scripts UND Computational Research Center Now that you have your program compiled and your input file ready for processing, it s time to run your job on the cluster.

More information

SLURM: Resource Management and Job Scheduling Software. Advanced Computing Center for Research and Education www.accre.vanderbilt.

SLURM: Resource Management and Job Scheduling Software. Advanced Computing Center for Research and Education www.accre.vanderbilt. SLURM: Resource Management and Job Scheduling Software Advanced Computing Center for Research and Education www.accre.vanderbilt.edu Simple Linux Utility for Resource Management But it s also a job scheduler!

More information

Tutorial: Using WestGrid. Drew Leske Compute Canada/WestGrid Site Lead University of Victoria

Tutorial: Using WestGrid. Drew Leske Compute Canada/WestGrid Site Lead University of Victoria Tutorial: Using WestGrid Drew Leske Compute Canada/WestGrid Site Lead University of Victoria Fall 2013 Seminar Series Date Speaker Topic 23 September Lindsay Sill Introduction to WestGrid 9 October Drew

More information

RA MPI Compilers Debuggers Profiling. March 25, 2009

RA MPI Compilers Debuggers Profiling. March 25, 2009 RA MPI Compilers Debuggers Profiling March 25, 2009 Examples and Slides To download examples on RA 1. mkdir class 2. cd class 3. wget http://geco.mines.edu/workshop/class2/examples/examples.tgz 4. tar

More information

Quick Tutorial for Portable Batch System (PBS)

Quick Tutorial for Portable Batch System (PBS) Quick Tutorial for Portable Batch System (PBS) The Portable Batch System (PBS) system is designed to manage the distribution of batch jobs and interactive sessions across the available nodes in the cluster.

More information

SLURM Workload Manager

SLURM Workload Manager SLURM Workload Manager What is SLURM? SLURM (Simple Linux Utility for Resource Management) is the native scheduler software that runs on ASTI's HPC cluster. Free and open-source job scheduler for the Linux

More information

Miami University RedHawk Cluster Working with batch jobs on the Cluster

Miami University RedHawk Cluster Working with batch jobs on the Cluster Miami University RedHawk Cluster Working with batch jobs on the Cluster The RedHawk cluster is a general purpose research computing resource available to support the research community at Miami University.

More information

Research Technologies Data Storage for HPC

Research Technologies Data Storage for HPC Research Technologies Data Storage for HPC Supercomputing for Everyone February 17-18, 2014 Research Technologies High Performance File Systems hpfs-admin@iu.edu Indiana University Intro to HPC on Big

More information

How To Run A Tompouce Cluster On An Ipra (Inria) 2.5.5 (Sun) 2 (Sun Geserade) 2-5.4 (Sun-Ge) 2/5.2 (

How To Run A Tompouce Cluster On An Ipra (Inria) 2.5.5 (Sun) 2 (Sun Geserade) 2-5.4 (Sun-Ge) 2/5.2 ( Running Hadoop and Stratosphere jobs on TomPouce cluster 16 October 2013 TomPouce cluster TomPouce is a cluster of 20 calcula@on nodes = 240 cores Located in the Inria Turing building (École Polytechnique)

More information

Using the Yale HPC Clusters

Using the Yale HPC Clusters Using the Yale HPC Clusters Stephen Weston Robert Bjornson Yale Center for Research Computing Yale University Oct 2015 To get help Send an email to: hpc@yale.edu Read documentation at: http://research.computing.yale.edu/hpc-support

More information

Introduction to Linux and Cluster Basics for the CCR General Computing Cluster

Introduction to Linux and Cluster Basics for the CCR General Computing Cluster Introduction to Linux and Cluster Basics for the CCR General Computing Cluster Cynthia Cornelius Center for Computational Research University at Buffalo, SUNY 701 Ellicott St Buffalo, NY 14203 Phone: 716-881-8959

More information

Grid 101. Grid 101. Josh Hegie. grid@unr.edu http://hpc.unr.edu

Grid 101. Grid 101. Josh Hegie. grid@unr.edu http://hpc.unr.edu Grid 101 Josh Hegie grid@unr.edu http://hpc.unr.edu Accessing the Grid Outline 1 Accessing the Grid 2 Working on the Grid 3 Submitting Jobs with SGE 4 Compiling 5 MPI 6 Questions? Accessing the Grid Logging

More information

Parallel Debugging with DDT

Parallel Debugging with DDT Parallel Debugging with DDT Nate Woody 3/10/2009 www.cac.cornell.edu 1 Debugging Debugging is a methodical process of finding and reducing the number of bugs, or defects, in a computer program or a piece

More information

Parallel Computing using MATLAB Distributed Compute Server ZORRO HPC

Parallel Computing using MATLAB Distributed Compute Server ZORRO HPC Parallel Computing using MATLAB Distributed Compute Server ZORRO HPC Goals of the session Overview of parallel MATLAB Why parallel MATLAB? Multiprocessing in MATLAB Parallel MATLAB using the Parallel Computing

More information

Parallel Options for R

Parallel Options for R Parallel Options for R Glenn K. Lockwood SDSC User Services glock@sdsc.edu Motivation "I just ran an intensive R script [on the supercomputer]. It's not much faster than my own machine." Motivation "I

More information

SLURM: Resource Management and Job Scheduling Software. Advanced Computing Center for Research and Education www.accre.vanderbilt.

SLURM: Resource Management and Job Scheduling Software. Advanced Computing Center for Research and Education www.accre.vanderbilt. SLURM: Resource Management and Job Scheduling Software Advanced Computing Center for Research and Education www.accre.vanderbilt.edu Simple Linux Utility for Resource Management But it s also a job scheduler!

More information

An Introduction to High Performance Computing in the Department

An Introduction to High Performance Computing in the Department An Introduction to High Performance Computing in the Department Ashley Ford & Chris Jewell Department of Statistics University of Warwick October 30, 2012 1 Some Background 2 How is Buster used? 3 Software

More information

Linux für bwgrid. Sabine Richling, Heinz Kredel. Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim. 27.

Linux für bwgrid. Sabine Richling, Heinz Kredel. Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim. 27. Linux für bwgrid Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 27. June 2011 Richling/Kredel (URZ/RUM) Linux für bwgrid FS 2011 1 / 33 Introduction

More information

Streamline Computing Linux Cluster User Training. ( Nottingham University)

Streamline Computing Linux Cluster User Training. ( Nottingham University) 1 Streamline Computing Linux Cluster User Training ( Nottingham University) 3 User Training Agenda System Overview System Access Description of Cluster Environment Code Development Job Schedulers Running

More information

Cluster@WU User s Manual

Cluster@WU User s Manual Cluster@WU User s Manual Stefan Theußl Martin Pacala September 29, 2014 1 Introduction and scope At the WU Wirtschaftsuniversität Wien the Research Institute for Computational Methods (Forschungsinstitut

More information

Installing and running COMSOL on a Linux cluster

Installing and running COMSOL on a Linux cluster Installing and running COMSOL on a Linux cluster Introduction This quick guide explains how to install and operate COMSOL Multiphysics 5.0 on a Linux cluster. It is a complement to the COMSOL Installation

More information

Introduction to the SGE/OGS batch-queuing system

Introduction to the SGE/OGS batch-queuing system Grid Computing Competence Center Introduction to the SGE/OGS batch-queuing system Riccardo Murri Grid Computing Competence Center, Organisch-Chemisches Institut, University of Zurich Oct. 6, 2011 The basic

More information

Grid Engine Basics. Table of Contents. Grid Engine Basics Version 1. (Formerly: Sun Grid Engine)

Grid Engine Basics. Table of Contents. Grid Engine Basics Version 1. (Formerly: Sun Grid Engine) Grid Engine Basics (Formerly: Sun Grid Engine) Table of Contents Table of Contents Document Text Style Associations Prerequisites Terminology What is the Grid Engine (SGE)? Loading the SGE Module on Turing

More information

Manual for using Super Computing Resources

Manual for using Super Computing Resources Manual for using Super Computing Resources Super Computing Research and Education Centre at Research Centre for Modeling and Simulation National University of Science and Technology H-12 Campus, Islamabad

More information

bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 20.

bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 20. bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 20. October 2010 Richling/Kredel (URZ/RUM) bwgrid Treff WS 2010/2011 1 / 27 Course

More information

JUROPA Linux Cluster An Overview. 19 May 2014 Ulrich Detert

JUROPA Linux Cluster An Overview. 19 May 2014 Ulrich Detert Mitglied der Helmholtz-Gemeinschaft JUROPA Linux Cluster An Overview 19 May 2014 Ulrich Detert JuRoPA JuRoPA Jülich Research on Petaflop Architectures Bull, Sun, ParTec, Intel, Mellanox, Novell, FZJ JUROPA

More information

Agenda. Using HPC Wales 2

Agenda. Using HPC Wales 2 Using HPC Wales Agenda Infrastructure : An Overview of our Infrastructure Logging in : Command Line Interface and File Transfer Linux Basics : Commands and Text Editors Using Modules : Managing Software

More information

Amazon-Free Big Data Analysis. Michael R. Crusoe the GED Lab @ MSU @JKhedron #NGS2013 2013-06- 18

Amazon-Free Big Data Analysis. Michael R. Crusoe the GED Lab @ MSU @JKhedron #NGS2013 2013-06- 18 Amazon-Free Big Data Analysis Michael R. Crusoe the GED Lab @ MSU @JKhedron #NGS2013 2013-06- 18 Overview Dedicated vs Shared computing Evaluating Computing Resources XSEDE Mason Lonestar Stampede Blacklight

More information

1.0. User Manual For HPC Cluster at GIKI. Volume. Ghulam Ishaq Khan Institute of Engineering Sciences & Technology

1.0. User Manual For HPC Cluster at GIKI. Volume. Ghulam Ishaq Khan Institute of Engineering Sciences & Technology Volume 1.0 FACULTY OF CUMPUTER SCIENCE & ENGINEERING Ghulam Ishaq Khan Institute of Engineering Sciences & Technology User Manual For HPC Cluster at GIKI Designed and prepared by Faculty of Computer Science

More information

Introduction to Running Computations on the High Performance Clusters at the Center for Computational Research

Introduction to Running Computations on the High Performance Clusters at the Center for Computational Research ! Introduction to Running Computations on the High Performance Clusters at the Center for Computational Research! Cynthia Cornelius! Center for Computational Research University at Buffalo, SUNY! cdc at

More information

A Crash course to (The) Bighouse

A Crash course to (The) Bighouse A Crash course to (The) Bighouse Brock Palen brockp@umich.edu SVTI Users meeting Sep 20th Outline 1 Resources Configuration Hardware 2 Architecture ccnuma Altix 4700 Brick 3 Software Packaged Software

More information

bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 24.

bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 24. bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 24. November 2010 Richling/Kredel (URZ/RUM) bwgrid Treff WS 2010/2011 1 / 17 Course

More information

XSEDE Science Gateway Use Cases

XSEDE Science Gateway Use Cases 25th October 2012 Version 0.4 Page 1 Table of Contents A. Document History B. Document Scope C. Science Gateway Use Cases D. Foundational (general XSEDE) use case that is a prerequisite for one of the

More information

PBS Tutorial. Fangrui Ma Universit of Nebraska-Lincoln. October 26th, 2007

PBS Tutorial. Fangrui Ma Universit of Nebraska-Lincoln. October 26th, 2007 PBS Tutorial Fangrui Ma Universit of Nebraska-Lincoln October 26th, 2007 Abstract In this tutorial we gave a brief introduction to using PBS Pro. We gave examples on how to write control script, and submit

More information

Juropa. Batch Usage Introduction. May 2014 Chrysovalantis Paschoulas c.paschoulas@fz-juelich.de

Juropa. Batch Usage Introduction. May 2014 Chrysovalantis Paschoulas c.paschoulas@fz-juelich.de Juropa Batch Usage Introduction May 2014 Chrysovalantis Paschoulas c.paschoulas@fz-juelich.de Batch System Usage Model A Batch System: monitors and controls the resources on the system manages and schedules

More information

Data Movement and Storage. Drew Dolgert and previous contributors

Data Movement and Storage. Drew Dolgert and previous contributors Data Movement and Storage Drew Dolgert and previous contributors Data Intensive Computing Location Viewing Manipulation Storage Movement Sharing Interpretation $HOME $WORK $SCRATCH 72 is a Lot, Right?

More information

CSE 344 Introduction to Data Management. Section 9: AWS, Hadoop, Pig Latin TA: Yi-Shu Wei

CSE 344 Introduction to Data Management. Section 9: AWS, Hadoop, Pig Latin TA: Yi-Shu Wei CSE 344 Introduction to Data Management Section 9: AWS, Hadoop, Pig Latin TA: Yi-Shu Wei Homework 8 Big Data analysis on billion triple dataset using Amazon Web Service (AWS) Billion Triple Set: contains

More information

Hadoop (pseudo-distributed) installation and configuration

Hadoop (pseudo-distributed) installation and configuration Hadoop (pseudo-distributed) installation and configuration 1. Operating systems. Linux-based systems are preferred, e.g., Ubuntu or Mac OS X. 2. Install Java. For Linux, you should download JDK 8 under

More information

Debugging and Profiling Lab. Carlos Rosales, Kent Milfeld and Yaakoub Y. El Kharma carlos@tacc.utexas.edu

Debugging and Profiling Lab. Carlos Rosales, Kent Milfeld and Yaakoub Y. El Kharma carlos@tacc.utexas.edu Debugging and Profiling Lab Carlos Rosales, Kent Milfeld and Yaakoub Y. El Kharma carlos@tacc.utexas.edu Setup Login to Ranger: - ssh -X username@ranger.tacc.utexas.edu Make sure you can export graphics

More information

XSEDE Service Provider Software and Services Baseline. September 24, 2015 Version 1.2

XSEDE Service Provider Software and Services Baseline. September 24, 2015 Version 1.2 XSEDE Service Provider Software and Services Baseline September 24, 2015 Version 1.2 i TABLE OF CONTENTS XSEDE Production Baseline: Service Provider Software and Services... i A. Document History... A-

More information

The Asterope compute cluster

The Asterope compute cluster The Asterope compute cluster ÅA has a small cluster named asterope.abo.fi with 8 compute nodes Each node has 2 Intel Xeon X5650 processors (6-core) with a total of 24 GB RAM 2 NVIDIA Tesla M2050 GPGPU

More information

Ra - Batch Scripts. Timothy H. Kaiser, Ph.D. tkaiser@mines.edu

Ra - Batch Scripts. Timothy H. Kaiser, Ph.D. tkaiser@mines.edu Ra - Batch Scripts Timothy H. Kaiser, Ph.D. tkaiser@mines.edu Jobs on Ra are Run via a Batch System Ra is a shared resource Purpose: Give fair access to all users Have control over where jobs are run Set

More information

Sriram Krishnan, Ph.D. sriram@sdsc.edu

Sriram Krishnan, Ph.D. sriram@sdsc.edu Sriram Krishnan, Ph.D. sriram@sdsc.edu (Re-)Introduction to cloud computing Introduction to the MapReduce and Hadoop Distributed File System Programming model Examples of MapReduce Where/how to run MapReduce

More information

Caltech Center for Advanced Computing Research System Guide: MRI2 Cluster (zwicky) January 2014

Caltech Center for Advanced Computing Research System Guide: MRI2 Cluster (zwicky) January 2014 1. How to Get An Account CACR Accounts 2. How to Access the Machine Connect to the front end, zwicky.cacr.caltech.edu: ssh -l username zwicky.cacr.caltech.edu or ssh username@zwicky.cacr.caltech.edu Edits,

More information

Using Parallel Computing to Run Multiple Jobs

Using Parallel Computing to Run Multiple Jobs Beowulf Training Using Parallel Computing to Run Multiple Jobs Jeff Linderoth August 5, 2003 August 5, 2003 Beowulf Training Running Multiple Jobs Slide 1 Outline Introduction to Scheduling Software The

More information

Application and Micro-benchmark Performance using MVAPICH2-X on SDSC Gordon Cluster

Application and Micro-benchmark Performance using MVAPICH2-X on SDSC Gordon Cluster Application and Micro-benchmark Performance using MVAPICH2-X on SDSC Gordon Cluster Mahidhar Tatineni (mahidhar@sdsc.edu) MVAPICH User Group Meeting August 27, 2014 NSF grants: OCI #0910847 Gordon: A Data

More information

HDFS Installation and Shell

HDFS Installation and Shell 2012 coreservlets.com and Dima May HDFS Installation and Shell Originals of slides and source code for examples: http://www.coreservlets.com/hadoop-tutorial/ Also see the customized Hadoop training courses

More information

Overview of HPC Resources at Vanderbilt

Overview of HPC Resources at Vanderbilt Overview of HPC Resources at Vanderbilt Will French Senior Application Developer and Research Computing Liaison Advanced Computing Center for Research and Education June 10, 2015 2 Computing Resources

More information

GPN - What is theGPFS HSI HTAR ISH?

GPN - What is theGPFS HSI HTAR ISH? 1/10 Storage Capacity Expansion Plan (initial) Storage Budget: $ $ $ (5PB) Back in 2009 GPFS (scratch + project) 2010-2011 2012-2013 GPFS (add 20-50%) GPFS (add 50-100%) Rationale: * the longer we wait,

More information

An introduction to Fyrkat

An introduction to Fyrkat Cluster Computing May 25, 2011 How to get an account https://fyrkat.grid.aau.dk/useraccount How to get help https://fyrkat.grid.aau.dk/wiki What is a Cluster Anyway It is NOT something that does any of

More information

Using the Windows Cluster

Using the Windows Cluster Using the Windows Cluster Christian Terboven terboven@rz.rwth aachen.de Center for Computing and Communication RWTH Aachen University Windows HPC 2008 (II) September 17, RWTH Aachen Agenda o Windows Cluster

More information

Storage Capacity Expansion Plan (initial)

Storage Capacity Expansion Plan (initial) 1/14 Storage Capacity Expansion Plan (initial) Storage Budget: $ $ $ (5PB) Back in 2009 GPFS scratch + project 2010-2011 2012-2013 GPFS (add 20-50%) GPFS (add 50-100%) Rationale: * the longer we wait,

More information

Stanford HPC Conference. Panasas Storage System Integration into a Cluster

Stanford HPC Conference. Panasas Storage System Integration into a Cluster Stanford HPC Conference Panasas Storage System Integration into a Cluster David Yu Industry Verticals Panasas Inc. Steve Jones Technology Operations Manager Institute for Computational and Mathematical

More information

Berkeley Research Computing. Town Hall Meeting Savio Overview

Berkeley Research Computing. Town Hall Meeting Savio Overview Berkeley Research Computing Town Hall Meeting Savio Overview SAVIO - The Need Has Been Stated Inception and design was based on a specific need articulated by Eliot Quataert and nine other faculty: Dear

More information

Parallel Processing using the LOTUS cluster

Parallel Processing using the LOTUS cluster Parallel Processing using the LOTUS cluster Alison Pamment / Cristina del Cano Novales JASMIN/CEMS Workshop February 2015 Overview Parallelising data analysis LOTUS HPC Cluster Job submission on LOTUS

More information

Running applications on the Cray XC30 4/12/2015

Running applications on the Cray XC30 4/12/2015 Running applications on the Cray XC30 4/12/2015 1 Running on compute nodes By default, users do not log in and run applications on the compute nodes directly. Instead they launch jobs on compute nodes

More information

Using Google Compute Engine

Using Google Compute Engine Using Google Compute Engine Chris Paciorek January 30, 2014 WARNING: This document is now out-of-date (January 2014) as Google has updated various aspects of Google Compute Engine. But it may still be

More information

Integration of Virtualized Workernodes in Batch Queueing Systems The ViBatch Concept

Integration of Virtualized Workernodes in Batch Queueing Systems The ViBatch Concept Integration of Virtualized Workernodes in Batch Queueing Systems, Dr. Armin Scheurer, Oliver Oberst, Prof. Günter Quast INSTITUT FÜR EXPERIMENTELLE KERNPHYSIK FAKULTÄT FÜR PHYSIK KIT University of the

More information

High Performance Computing Facility Specifications, Policies and Usage. Supercomputer Project. Bibliotheca Alexandrina

High Performance Computing Facility Specifications, Policies and Usage. Supercomputer Project. Bibliotheca Alexandrina High Performance Computing Facility Specifications, Policies and Usage Supercomputer Project Bibliotheca Alexandrina Bibliotheca Alexandrina 1/16 Topics Specifications Overview Site Policies Intel Compilers

More information

Current Status of FEFS for the K computer

Current Status of FEFS for the K computer Current Status of FEFS for the K computer Shinji Sumimoto Fujitsu Limited Apr.24 2012 LUG2012@Austin Outline RIKEN and Fujitsu are jointly developing the K computer * Development continues with system

More information

The XSEDE Global Federated File System (GFFS) - Breaking Down Barriers to Secure Resource Sharing

The XSEDE Global Federated File System (GFFS) - Breaking Down Barriers to Secure Resource Sharing December 19, 2013 The XSEDE Global Federated File System (GFFS) - Breaking Down Barriers to Secure Resource Sharing Andrew Grimshaw, University of Virginia Co-architect XSEDE The complexity of software

More information

Data Management. Network transfers

Data Management. Network transfers Data Management Network transfers Network data transfers Not everyone needs to transfer large amounts of data on and off a HPC service Sometimes data is created and consumed on the same service. If you

More information

Advanced Techniques with Newton. Gerald Ragghianti Advanced Newton workshop Sept. 22, 2011

Advanced Techniques with Newton. Gerald Ragghianti Advanced Newton workshop Sept. 22, 2011 Advanced Techniques with Newton Gerald Ragghianti Advanced Newton workshop Sept. 22, 2011 Workshop Goals Gain independence Executing your work Finding Information Fixing Problems Optimizing Effectiveness

More information

Hadoop MapReduce over Lustre* High Performance Data Division Omkar Kulkarni April 16, 2013

Hadoop MapReduce over Lustre* High Performance Data Division Omkar Kulkarni April 16, 2013 Hadoop MapReduce over Lustre* High Performance Data Division Omkar Kulkarni April 16, 2013 * Other names and brands may be claimed as the property of others. Agenda Hadoop Intro Why run Hadoop on Lustre?

More information

Running on Blue Gene/Q at Argonne Leadership Computing Facility (ALCF)

Running on Blue Gene/Q at Argonne Leadership Computing Facility (ALCF) Running on Blue Gene/Q at Argonne Leadership Computing Facility (ALCF) ALCF Resources: Machines & Storage Mira (Production) IBM Blue Gene/Q 49,152 nodes / 786,432 cores 768 TB of memory Peak flop rate:

More information

bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 19.

bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 19. bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 19. January 2011 Richling/Kredel (URZ/RUM) bwgrid Treff WS 2010/2011 1 / 33 Course

More information

Automating Big Data Benchmarking for Different Architectures with ALOJA

Automating Big Data Benchmarking for Different Architectures with ALOJA www.bsc.es Jan 2016 Automating Big Data Benchmarking for Different Architectures with ALOJA Nicolas Poggi, Postdoc Researcher Agenda 1. Intro on Hadoop performance 1. Current scenario and problematic 2.

More information

INF-110. GPFS Installation

INF-110. GPFS Installation INF-110 GPFS Installation Overview Plan the installation Before installing any software, it is important to plan the GPFS installation by choosing the hardware, deciding which kind of disk connectivity

More information

Wrangler: A New Generation of Data-intensive Supercomputing. Christopher Jordan, Siva Kulasekaran, Niall Gaffney

Wrangler: A New Generation of Data-intensive Supercomputing. Christopher Jordan, Siva Kulasekaran, Niall Gaffney Wrangler: A New Generation of Data-intensive Supercomputing Christopher Jordan, Siva Kulasekaran, Niall Gaffney Project Partners Academic partners: TACC Primary system design, deployment, and operations

More information

Lustre * Filesystem for Cloud and Hadoop *

Lustre * Filesystem for Cloud and Hadoop * OpenFabrics Software User Group Workshop Lustre * Filesystem for Cloud and Hadoop * Robert Read, Intel Lustre * for Cloud and Hadoop * Brief Lustre History and Overview Using Lustre with Hadoop Intel Cloud

More information

MapReduce. Tushar B. Kute, http://tusharkute.com

MapReduce. Tushar B. Kute, http://tusharkute.com MapReduce Tushar B. Kute, http://tusharkute.com What is MapReduce? MapReduce is a framework using which we can write applications to process huge amounts of data, in parallel, on large clusters of commodity

More information

Data Management Best Practices

Data Management Best Practices December 4, 2013 Data Management Best Practices Ryan Mokos Outline Overview of Nearline system (HPSS) Hardware File system structure Data transfer on Blue Waters Globus Online (GO) interface Web GUI Command-Line

More information

Using the Millipede cluster - I

Using the Millipede cluster - I Using the Millipede cluster - I Fokke Dijkstra, Bob Dröge High Performance Computing and Visualisation group Donald Smits Centre for Information Technology General introduction Course aimed at beginners

More information

MapReduce Evaluator: User Guide

MapReduce Evaluator: User Guide University of A Coruña Computer Architecture Group MapReduce Evaluator: User Guide Authors: Jorge Veiga, Roberto R. Expósito, Guillermo L. Taboada and Juan Touriño December 9, 2014 Contents 1 Overview

More information

New High-performance computing cluster: PAULI. Sascha Frick Institute for Physical Chemistry

New High-performance computing cluster: PAULI. Sascha Frick Institute for Physical Chemistry New High-performance computing cluster: PAULI Sascha Frick Institute for Physical Chemistry 02/05/2012 Sascha Frick (PHC) HPC cluster pauli 02/05/2012 1 / 24 Outline 1 About this seminar 2 New Hardware

More information

Introduction to ACENET Accelerating Discovery with Computational Research May, 2015

Introduction to ACENET Accelerating Discovery with Computational Research May, 2015 Introduction to ACENET Accelerating Discovery with Computational Research May, 2015 What is ACENET? What is ACENET? Shared regional resource for... high-performance computing (HPC) remote collaboration

More information

Introduction to the CRAY XE6(Lindgren) environment at PDC. Dr. Lilit Axner (PDC, Sweden)

Introduction to the CRAY XE6(Lindgren) environment at PDC. Dr. Lilit Axner (PDC, Sweden) Introduction to the CRAY XE6(Lindgren) environment at PDC Dr. Lilit Axner (PDC, Sweden) Lindgren System used after the summer school! Cray XE6 8 interactive nodes 1516 dedicated nodes (queue needed!) 24

More information

Quick Introduction to HPSS at NERSC

Quick Introduction to HPSS at NERSC Quick Introduction to HPSS at NERSC Nick Balthaser NERSC Storage Systems Group nabalthaser@lbl.gov Joint Genome Institute, Walnut Creek, CA Feb 10, 2011 Agenda NERSC Archive Technologies Overview Use Cases

More information

OpenMP & MPI CISC 879. Tristan Vanderbruggen & John Cavazos Dept of Computer & Information Sciences University of Delaware

OpenMP & MPI CISC 879. Tristan Vanderbruggen & John Cavazos Dept of Computer & Information Sciences University of Delaware OpenMP & MPI CISC 879 Tristan Vanderbruggen & John Cavazos Dept of Computer & Information Sciences University of Delaware 1 Lecture Overview Introduction OpenMP MPI Model Language extension: directives-based

More information

Deploy Apache Hadoop with Emulex OneConnect OCe14000 Ethernet Network Adapters

Deploy Apache Hadoop with Emulex OneConnect OCe14000 Ethernet Network Adapters CONNECT - Lab Guide Deploy Apache Hadoop with Emulex OneConnect OCe14000 Ethernet Network Adapters Hardware, software and configuration steps needed to deploy Apache Hadoop 2.4.1 with the Emulex family

More information

Magellan A Test Bed to Explore Cloud Computing for Science Shane Canon and Lavanya Ramakrishnan Cray XE6 Training February 8, 2011

Magellan A Test Bed to Explore Cloud Computing for Science Shane Canon and Lavanya Ramakrishnan Cray XE6 Training February 8, 2011 Magellan A Test Bed to Explore Cloud Computing for Science Shane Canon and Lavanya Ramakrishnan Cray XE6 Training February 8, 2011 Magellan Exploring Cloud Computing Co-located at two DOE-SC Facilities

More information

bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 29.

bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 29. bwgrid Treff MA/HD Sabine Richling, Heinz Kredel Universitätsrechenzentrum Heidelberg Rechenzentrum Universität Mannheim 29. September 2010 Richling/Kredel (URZ/RUM) bwgrid Treff WS 2010/2011 1 / 25 Course

More information

CactoScale Guide User Guide. Athanasios Tsitsipas (UULM), Papazachos Zafeirios (QUB), Sakil Barbhuiya (QUB)

CactoScale Guide User Guide. Athanasios Tsitsipas (UULM), Papazachos Zafeirios (QUB), Sakil Barbhuiya (QUB) CactoScale Guide User Guide Athanasios Tsitsipas (UULM), Papazachos Zafeirios (QUB), Sakil Barbhuiya (QUB) Version History Version Date Change Author 0.1 12/10/2014 Initial version Athanasios Tsitsipas(UULM)

More information

File Transfer Best Practices

File Transfer Best Practices File Transfer Best Practices David Turner User Services Group NERSC User Group Meeting October 2, 2008 Overview Available tools ftp, scp, bbcp, GridFTP, hsi/htar Examples and Performance LAN WAN Reliability

More information

Parallel Programming for Multi-Core, Distributed Systems, and GPUs Exercises

Parallel Programming for Multi-Core, Distributed Systems, and GPUs Exercises Parallel Programming for Multi-Core, Distributed Systems, and GPUs Exercises Pierre-Yves Taunay Research Computing and Cyberinfrastructure 224A Computer Building The Pennsylvania State University University

More information

Documentation for hanythingondemand

Documentation for hanythingondemand Documentation for hanythingondemand Release 20151120.01 Ghent University Thu, 07 Jan 2016 12:53:15 Contents 1 Introductory topics 3 1.1 What is hanythingondemand?.................................... 3

More information

IMPLEMENTING GREEN IT

IMPLEMENTING GREEN IT Saint Petersburg State University of Information Technologies, Mechanics and Optics Department of Telecommunication Systems IMPLEMENTING GREEN IT APPROACH FOR TRANSFERRING BIG DATA OVER PARALLEL DATA LINK

More information