OpenCUDA + MPI A Framework for Heterogeneous GP-GPU Distributed Computing
Kenny Ballou
February 15, 2013
Ballou OpenCUDA + MPI
Introduction Parallel and Distributed Computing
What is GP-GPU Distributed Computing? Parallel: Processing concurrently
Distributed: Processing over many computers, typically in parallel, but not always Local Grid Computing
Ballou OpenCUDA + MPI
Applications of Supercomputing What can we do with Parallel and Distributed Computing?
Solving (Large) Linear Systems LINPACK Benchmarks
Fluid Dynamic Simulations N-Body Simulations Brute-Force Password/Hash Cracking Prime Number Searching Protein Folding Image Analysis / Manipulation ...
Ballou OpenCUDA + MPI
Who Uses Distributed Computing?
Google – Page Indexing Created Map-Reduce
Facebook – Data Mining Universities Many Others
Ballou OpenCUDA + MPI
The Problem(s)
”Distributed Programming” is expensive Specificity of Hardware Data Distribution Volume
Fault Tolerance
Ballou OpenCUDA + MPI
A Framework Solutions
Ease Programming Interface for Highly Parallel Distributed Computing Allow for Diversity in Computing Environment Bring together ideas from both types of distributed computing ”Jungle Computing”
Ballou OpenCUDA + MPI
Plan and Goals
Develop a framework for distributed computing over a heterogeneous cluster Develop several different solutions for vascular extraction from CT angiography scans Profile the different solutions Add Cluster/ Node Configuration and Scheduling Options
Ballou OpenCUDA + MPI
Progress
Progressing more slowly than I anticipated CUDA C/C++ and pyCUDA Cluster/ Node Administration (ongoing) mpi4py – Begin learning the MPI interface and intricacies
Ballou OpenCUDA + MPI
Continuing Progress
Continue Learning mpi4py and pyCUDA Combine mpi4py with pyCUDA ... Begin developing framework
Ballou OpenCUDA + MPI
Acknowledgements
Dr. Alark Joshi – Mentor Graphics and Visualization
Feb 15, 2013 - Who Uses Distributed Computing? Google â Page Indexing. Created Map-Reduce. Facebook â Data Mining. Universities. Many Others. Ballou.
A Framework for Heterogeneous GP-GPU Cluster Computing. Kenny Ballou ... Parallel: Processing concurrently. Distributed: Processing over many computers.
CPUs consist of a small number of cores (microprocessors) that are best at .... sands) of hosts (nodes), and executing application computations in parallel ... the unused CPU and GPU cycles on a computer to do scientific computing [10]. .... Rajagopa
May 3, 2013 - Add process âschedulerâ to best utilize available computing resources. Add Cluster ... Host to Device Memory Copies. Device to Host Memory ...
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There was a problem previewing this document. Retrying... Download. Connect more apps... Try one of the apps below to open or edit this item. MPI by Godse.
Jun 18, 2015 - explicit injection into and projection from first-class core values, accompanied ... lift the function (and potentially a lot of downstream code) to the.
Aug 18, 2003 - design the next generation clusters and servers with high .... Virtual Data Lanes (VLs) in additon to a Dedicated Management Lane (VL15). 5 ...
C.1.4 [Computer System Organization]: Parallel Archi- tectures .... and services can be useful in designing a high performance ..... 4.6 Polling Set Management.
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If an interrupt has been requested, the 8086 processes it by performing the following series of steps: a) Pushes the content of the flag register onto the stack to ...
IBM Loadleveler talks about tasks not processes ... On the IBM all tasks execute the code before MPI_INIT ... useful when doing collective communications.
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