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Abstract : Parallel graph processing is central to analytical computer science applications, and GPUs have proven to be an ideal platform for parallel graph pro

Heterogeneous architectures have become popular due to programming flexibility and energy efficiency. Heterogeneous architectures include GPU accelerators, and

Originally developed to support video games, graphics processor units (GPUs) are now increasingly used for general-purpose (non-graphics) applications ranging f

Explore GPU-enabled programmable environment for machine learning, scientific applications, and gaming using PuCUDA, PyOpenGL, and Anaconda Accelerate Key Featu

This book brings together two important trends: graph algorithms and high-performance computing. Efficient and scalable execution of graph processing applicatio