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  1. Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units (GPGPU-3)
  2. Implementing the PGI Accelerator model
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Toward exascale computational science with heterogeneous processing
Parallel multiclass classification using SVMs on GPUs
Compiling Python to a hybrid execution environment
GPGPU role within a 500 TFLOPS heterogeneous cluster
The Scalable Heterogeneous Computing (SHOC) benchmark suite
Best-effort semantic document search on GPUs
Cortical architectures on a GPGPU
Modeling GPU-CPU workloads and systems
Accelerating MATLAB Image Processing Toolbox functions on GPUs
Accelerating SQL database operations on a GPU with CUDA
Implementing the PGI Accelerator model
Accelerating the local outlier factor algorithm on a GPU for intrusion detection systems
A mapping path for multi-GPGPU accelerated computers from a portable high level programming abstraction
Iterative induced dipoles computation for molecular mechanics on GPUs

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Implementing the PGI Accelerator model

Content Provider ACM Digital Library
Author Wolfe, Michael
Abstract The PGI Accelerator model is a high-level programming model for accelerators, such as GPUs, similar in design and scope to the widely-used OpenMP directives. This paper presents some details of the design of the compiler that implements the model, focusing on the Planner, the element that maps the program parallelism onto the hardware parallelism.
Starting Page 43
Ending Page 50
Page Count 8
File Format PDF
ISBN 9781605589350
DOI 10.1145/1735688.1735697
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2010-03-14
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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