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The AASPI Software Computational Environment Tim Kwiatkowski

The AASPI Software Computational Environment Tim Kwiatkowski. Welcome Consortium Members December 9, 2011. Overview. Hardware Clusters Multiprocessor / Multi-core Software Computational Environment Compilers Libraries Graphics Software Design Directory Layout The Future.

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The AASPI Software Computational Environment Tim Kwiatkowski

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  1. The AASPI Software Computational Environment Tim Kwiatkowski Welcome Consortium Members December 9, 2011

  2. Overview • Hardware • Clusters • Multiprocessor / Multi-core • Software • Computational Environment • Compilers • Libraries • Graphics • Software Design • Directory Layout • The Future

  3. Hardware Clusters The AASPI Software was originally designed to run on U**X/Linux clusters using MPI (Message Passing Interface). Large Granularity No need for expensive interconnects. Gigabit Ethernet is sufficient. Depending on the size of the cluster, can be difficult to administer.

  4. Hardware Multiprocessor / Multi-core • Newer multi-core processors have • become available • Currently no explicit multi-threading. • MPI using “Loopback” Communication • Simpler to administer • Can be grown into a cluster

  5. Hardware Our Current Resources • Older Resources • diamond - Sun Enterprise 450 • fluorite- Dual CPU 2.4GHz Xeon 5.2 TB storage (offline) • Newer Resources • Opal – Dual Quad-core 3.0GHz Xeon 16 GB, 15 TB storage • Ruby – Quad Quad-core 1.6 GHz Xeon 32 GB, 11 TB storage • Jade – Dual Quad-core 2.8 GHz Xeon 48 GB, 5 TB storage • Hematite – Dual Quad-core 3.46 GHz Xeon 48 GB, 5 TB storage • Tripolite – Dual Six-core 3.46 GHz Xeon 48 GB, 5 TB storage • Corundum – Dual Quad-core 2.33GHz Xeon 32 GB, 10 TB -file server • 22 Windows XP/Windows 7 64bit PC/Workstations.

  6. Tape Reading Ability Our Current Resources • Older Resources • 8mm Exabyte • DLT-8000 • IBM 3590B • Newer Resources • LTO-4

  7. Hardware Our Current Resources – Cluster Resources • OSCER(Oklahoma Supercomputing Center for Education & Research) • As a whole: 536 User Accessible Nodes, 8800 GB aggregate RAM, 100TB Usable Fast scratch storage, 34450 GFlop peak, 28030 GFlop sustained. • Our own dedicated OSCER nodes / storage • Dual Quad core (3 ea. 2.33 GHz, 3ea. 2.66 GHz) 16GB RAM • Storage node - Dual Quad core 2.33GHz, 16GB RAM, 18TB disk storage. • www.oscer.ou.edu • Muntu • 1 management node, 1 head node, 14 compute nodes. • Each node: 3.06 GHz Dual processor , 4GB RAM. • Total disk storage: ~2TB

  8. Hardware Recommendations What type of hardware do I need to run the AASPI software? The short answer: It depends. Entry level suggestion: Dual socket with Dual, Quad or Six-core CPU 2.5GHz+ 2GB /core >2 TB disk capacity

  9. Software Environment − OS • Operating System • As shipped, we have chosen to pre-compile the AASPI software. This should work on most Redhat 4 Release 4 and higher installations. • Some needed packages • blas, lapack, libf2c, bzip2-libs,zlib, X11 packages for running the GUI, Mesa-libGL, Mesa-libGLU

  10. Software Environment − 64 vs. 32 bit We are finally moving away from SEPlib! • The majority of the AASPI code has been converted over to the aaspi_io framework which is compatible with the SEP files. • SEPLib limited us to 32 bit code. We are still compiling most of our code as 32bit, but we have begun to release both 32bit and 64bit compiled binaries. • Certain codes like the SOM code require more memory, 32bit codes are limited to 2 GB per process. • However, we are still using SEP utilities for display.

  11. Software Environment − Compilers We have chosen to pre-compile the AASPI software to make your life easier. However, IF you are compiling on your own… Required:A good Fortran90 compiler such as the Portland Group Fortran compiler or the Intel Fortran 90/95 compiler. We use the Intel Fortran compiler. Required:A good C/C++ compiler. GCC is fine. Required:Patience! Most of the compiling issues come from the 3rd party packages!

  12. Software Environment − Libraries • The software depends on several external libraries: • Seismic Unix (Center for Wave Phenomena - Colorado School of Mines) • SEPlib (Stanford Exploration Project) • SEPlib utilities are primarily used for display – most of the AASPI code no longer requires SEPlib (or SU) • SEG-Y import/export uses aaspi_io and does not require SU or SEPlib. • OpenMPI (We have used MPICH in the past) • FFTW (mostly Version 2 at the present time migrating to version 3) • Lapack & BLAS (The Intel Math Kernel Library could be used as a substitute) • The FOX Toolkit (GUI interface and seismic data display)

  13. Software Environment − Graphics • Now we have a GUI interface. • Based on the FOX Toolkit. • For Linux this means X-Windows based. • How do we use it? • Some Solutions • Use a desktop Linux workstation. • Use a Mac • ThinAnywhere • VNC • Hummingbird Exceed • Xming • Cygwin

  14. Software Design Practices/Goals • Use modern programming languages • Fortran 90/95 • C/C++ • Modular Design • Maximize code re-use • Use Fortran 90/95 modules/interfaces • Use C++ classes/template programming • Libraries • Organize processes/functions into logical, reusable libraries

  15. Software Layout Precompiled binaries – 32bit Precompiled binaries – 64bit Non-AASPI package compiled libraries Non-AASPI RPMS Non-AASPI packages - source AASPI include files (along with others) AASPI include files (64 bit Fortran module files) AASPI libraries & other shared libraries AASPI libraries – 64bit AASPI man pages AASPI source code Scripts – program wrappers and utilities

  16. The Future Replacing the rest of the SEPlib dependencies – We hope do develop some display tools of our own as we move away from the SEP framework. At this point, we have most of our code converted to our own API. However, we are still shaking out some of the bugs introduced by the conversion. MS Windows? – Perhaps… All of our core code should be multiplatform. MPI is available on Windows platforms via cluster services.

  17. Future Computing GPU Research -- Still on our Radar We are experimenting with the newest generation of equipment – GPUs (Graphics Processing Units) We were working with CUDA (Compute Unified Device Architecture from nVidia). OpenCL looks like a more promising road for code portability. The software development target for GPU processing will be the desktop PC most likely as plug-ins for Petrel. However, OSCER does have a GPU cluster which we have not tested. Certain codes may lend themselves more naturally to GPU processing than others.

  18. AASPI Software Computational Environment Tim Kwiatkowski Thank You! Questions?

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