Description: Concurrent NumPy in Python by Jason Brownlee Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Concurrency in NumPy is not an afterthoughtDiscover matrix multiplication that is 2.7x faster.Discover array initialization that is up to 3.2x faster.Discover sharing copied arrays that is up to 516.91x faster.NumPy is how we represent arrays of numbers in Python. An entire ecosystem of third-party libraries has been developed around NumPy arrays, from machine learning and deep learning to image and computer vision and more. Given the wide use of NumPy, it is essential we know how to get the most out of our system when using it. We cannot afford to have CPU cores sit idle when performing mathematical operations on arrays. Therefore we must know how to correctly harness concurrency in NumPy, such as: NumPy has multithreaded algorithms and functions built-in (using BLAS).NumPy will release the infamous GIL so Python threads can run in parallel.NumPy arrays can be shared efficiently between Python processes using shared memory.The problem is, no one is talking about how. Introducing: "Concurrent NumPy in Python". A new book designed to teach you how to bring concurrency to your NumPy programs in Python, super fast! You will get fast-paced tutorials showing you how to bring concurrency to the most common NumPy tasks. Including: Parallel array multiplication, common math functions, matrix solvers, and decompositions.Parallel array filling and parallel creation of arrays of random numbers.Parallel element-wise array arithmetic and common array math functionsParallel programs for working with many NumPy arrays with thread and process pools.Efficiently share arrays directly, and copies of arrays between Python processes.Dont worry if you are new to NumPy programming or concurrency, you will also get primers on the background required to get the most out of this book, including: The importance of concurrency when using NumPy and the cost of approaching it naively.How to perform common NumPy operations and math functions.How to install, query, and configure BLAS libraries for built-in multithreaded NumPy functions.How to use Python concurrency APIs including threading, multiprocessing, and pools of workers.Each tutorial is carefully designed to teach one critical aspect of how to bring concurrency to your NumPy projects. Learn Python concurrency correctly, step-by-step. Details ISBN-13 9798862038057 Title Concurrent NumPy in Python Author Jason Brownlee Format Paperback Year 2023 Pages 476 Publisher Independently Published GE_Item_ID:151238244; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
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ISBN-13: 9798862038057
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Book Title: Concurrent NumPy in Python
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