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Hands-On GPU Computing with Python | 7. Working with ROCm and PyOpenCL
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Hands-On GPU Computing with Python is available from:
This is the “Code in Action” video for chapter 7 of Hands-On GPU Computing with Python by Avimanyu Bandyopadhyay, published by Packt. It includes the following topics:
00:11 Converting CUDA code to cross-platform HIP code with hipify
01:10 Understanding how ROCm-C/C++ works with HIP
05:36 Understanding how OpenCL works
08:08 How computing in PyOpenCL works on Python
09:26 Writing your first PyOpenCL programs to compute a general-purpose solution
GPU technologies are the paradigm shift in modern computing. This book will take you through architecting your GPU-based systems to deploying the computational models on GPUs for faster processing. You will learn to program your GPUs to build a GPU-accelerated environment for accelerating machine learning models and other data-intensive processing
Connect with Packt:
Video created by Avimanyu Bandyopadhyay
This is the “Code in Action” video for chapter 7 of Hands-On GPU Computing with Python by Avimanyu Bandyopadhyay, published by Packt. It includes the following topics:
00:11 Converting CUDA code to cross-platform HIP code with hipify
01:10 Understanding how ROCm-C/C++ works with HIP
05:36 Understanding how OpenCL works
08:08 How computing in PyOpenCL works on Python
09:26 Writing your first PyOpenCL programs to compute a general-purpose solution
GPU technologies are the paradigm shift in modern computing. This book will take you through architecting your GPU-based systems to deploying the computational models on GPUs for faster processing. You will learn to program your GPUs to build a GPU-accelerated environment for accelerating machine learning models and other data-intensive processing
Connect with Packt:
Video created by Avimanyu Bandyopadhyay
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