{"product_id":"9781788993913-hands-on-gpu-programming-wpyt","title":"Hands-On GPU Programming with Python and CUDA","description":"\u003cmeta content=\"text\/html; charset=utf-8\" http-equiv=\"Content-Type\"\u003e\u003cp\u003e\u003cspan\u003eExplore high-performance parallel computing with CUDA. GPUs are designed for maximum throughput, but are subject to low-level subtleties. In contrast, Python is a high-level language that favours ease of use over speed. In this book, we will combine the power of both Python and CUDA to help you create high performing Python applications by using open-source libraries such as PyCUDA and SciKit-CUDA. \u003cp\u003e\u003cb\u003eBuild real-world applications with Python 2.7, CUDA 9, and CUDA 10. We suggest the use of Python 2.7 over Python 3.x, since Python 2.7 has stable support across all the libraries we use in this book.\u003c\/b\u003e\u003c\/p\u003eKey Features\u003cul\u003e\n\u003cli\u003eExpand your background in GPU programming—PyCUDA, scikit-cuda, and Nsight\u003c\/li\u003e\n\u003cli\u003eEffectively use CUDA libraries such as cuBLAS, cuFFT, and cuSolver\u003c\/li\u003e\n\u003cli\u003eApply GPU programming to modern data science applications\u003c\/li\u003e\n\u003c\/ul\u003eBook Description\u003cp\u003eHands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler to identify bottlenecks in your Python code, and set up an appropriate GPU programming environment. You’ll then see how to “query” the GPU’s features and copy arrays of data to and from the GPU’s own memory.\u003c\/p\u003e\n\u003cp\u003eAs you make your way through the book, you’ll launch code directly onto the GPU and write full blown GPU kernels and device functions in CUDA C. You’ll get to grips with profiling GPU code effectively and fully test and debug your code using Nsight IDE. Next, you’ll explore some of the more well-known NVIDIA libraries, such as cuFFT and cuBLAS.\u003c\/p\u003e\n\u003cp\u003eWith a solid background in place, you will now apply your new-found knowledge to develop your very own GPU-based deep neural network from scratch. You’ll then explore advanced topics, such as warp shuffling, dynamic parallelism, and PTX assembly. In the final chapter, you’ll see some topics and applications related to GPU programming that you may wish to pursue, including AI, graphics, and blockchain.\u003c\/p\u003e\n\u003cp\u003eBy the end of this book, you will be able to apply GPU programming to problems related to data science and high-performance computing.\u003c\/p\u003eWhat you will learn\u003cul\u003e\n\u003cli\u003eLaunch GPU code directly from Python\u003c\/li\u003e\n\u003cli\u003eWrite effective and efficient GPU kernels and device functions\u003c\/li\u003e\n\u003cli\u003eUse libraries such as cuFFT, cuBLAS, and cuSolver\u003c\/li\u003e\n\u003cli\u003eDebug and profile your code with Nsight and Visual Profiler\u003c\/li\u003e\n\u003cli\u003eApply GPU programming to datascience problems\u003c\/li\u003e\n\u003cli\u003eBuild a GPU-based deep neuralnetwork from scratch\u003c\/li\u003e\n\u003cli\u003eExplore advanced GPU hardware features, such as warp shuffling\u003c\/li\u003e\n\u003c\/ul\u003eWho this book is for\u003cp\u003eHands-On GPU Programming with Python and CUDA is for developers and data scientists who want to learn the basics of effective GPU programming to improve performance using Python code. You should have an understanding of first-year college or university-level engineering mathematics and physics, and have some experience with Python as well as in any C-based programming language such as C, C++, Go, or Java.\u003c\/p\u003e\n\u003cbr\u003e\u003c\/span\u003e\u003c\/p\u003e","brand":"Rarewaves","offers":[{"title":"Default Title","offer_id":41049613598817,"sku":"9781788993913","price":44.58,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0092\/7504\/8033\/files\/28b5873d3b76eab7dbbcf4f258d7294e.png?v=1700715842","url":"https:\/\/www.rarewaves.com\/products\/9781788993913-hands-on-gpu-programming-wpyt","provider":"Rarewaves.com","version":"1.0","type":"link"}