1 / 8

CIS 6930: Chip Multiprocessor: GPU Architecture and Programming

Fall 2010 Jih-Kwon Peir Computer Information Science Engineering University of Florida. CIS 6930: Chip Multiprocessor: GPU Architecture and Programming. Tutorial: How to Use the HPC environment for this course. How to Apply the HPC account Login to HPC account Setup CUDA environment

vbarth
Download Presentation

CIS 6930: Chip Multiprocessor: GPU Architecture and Programming

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Fall 2010 • Jih-Kwon Peir • Computer Information Science Engineering • University of Florida CIS 6930: Chip Multiprocessor: GPU Architecture and Programming

  2. Tutorial: How to Use the HPC environment for this course • How to Apply the HPC account • Login to HPC account • Setup CUDA environment • devicequery: the first CUDA application • MultrixAdd: the sample code

  3. Apply HPC account • Go to http://hpc.ufl.edu/ • Click “Support” • Click “Account Requests” • Login with your gatorlink • When Applying • Input Dr Peir as your Sponsor • Input GPU Course as Type of research • Input CIS6930 in Comments • Remember to active your Bugzilla account when you receive the email.

  4. Access the HPC environment • Use SSH tool as putty etc; • Host name: • submit.hpc.ufl.edu • You may be on either submit1.hpc.ufl.edu or submit2.hpc.ufl.edu • Submit is only to submit jobs or do simple tasks; • You need ssh to test01/test02/test03/test04/test05 to do time-consuming jobs;

  5. Build the CUDA • The CUDA-SDK directory on HPC is • /opt/cuda-sdk • You may download the cuda_test.tar.gz from the course website. • The source directory is …/mycuda/myproject/ in the cuda_test.tar.gz; • The binary files are in …/bin/ or …/mycuda/bin/linux/release/ • You can also build your own workspace.

  6. Qsub • You need first use the Qsub to get the tesla machine. The command is as follows: • qsub -I -l nodes=1,walltime=01:00:00,gres=gpu -q tesla • You will be login into one of the tesla machines.

  7. Compile and Run • Run the deviceQuery • >cd …/cuda_test/mycude/myproject/deviceQuery • >make • > ../../bin/linux/release/deviceQuery

  8. Another Example • Matrix Add: • See the matrixAdd.2 and matrixAdd.3 code in the cuda_test

More Related