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Hands-On GPU Computing with Python. Explore the capabilities of GPUs for solving high performance computational problems

Język publikacji: angielskim
Hands-On GPU Computing with Python. Explore the capabilities of GPUs for solving high performance computational problems Avimanyu Bandyopadhyay - okladka książki

Hands-On GPU Computing with Python. Explore the capabilities of GPUs for solving high performance computational problems Avimanyu Bandyopadhyay - okladka książki

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GPUs are proving to be excellent general purpose-parallel computing solutions for high-performance tasks such as deep learning and scientific computing.
This book will be your guide to getting started with GPU computing. It begins by introducing GPU computing and explaining the GPU architecture and programming models. You will learn, by example, how to perform GPU programming with Python, and look at using integrations such as PyCUDA, PyOpenCL, CuPy, and Numba with Anaconda for various tasks such as machine learning and data mining. In addition to this, you will get to grips with GPU workflows, management, and deployment using modern containerization solutions. Toward the end of the book, you will get familiar with the principles of distributed computing for training machine learning models and enhancing efficiency and performance.
By the end of this book, you will be able to set up a GPU ecosystem for running complex applications and data models that demand great processing capabilities, and be able to efficiently manage memory to compute your application effectively and quickly.
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O autorze książki

Avimanyu Bandyopadhyay is currently pursuing a PhD degree in Bioinformatics based on applied GPU computing in Computational Biology at Heritage Institute of Technology, Kolkata, India. Since 2014, he developed a keen interest in GPU computing, and used CUDA for his master's thesis. He has experience as a systems administrator as well, particularly on the Linux platform. Avimanyu is also a scientific writer, technology communicator, and a passionate gamer. He has published technical writing on open source computing and has actively participated in NVIDIA's GPU computing conferences since 2016. A big-time Linux fan, he strongly believes in the significance of Linux and an open source approach in scientific research. Deep learning with GPUs is his new passion!

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