SKU/Artículo: AMZ-B0DNWLL5PR
Parallel Sorting and Searching Algorithms on Multi-Dimensional Grids With CUDA (GPU Mastery Series: Unlocking CUDA's Power using pyCUDA)
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0.67 kg
0.67 kg
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Amazon
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USA
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- Embark on a journey through the forefront of parallel computing with this comprehensive guide to advanced sorting and searching algorithms optimized for GPU execution using pyCUDA. This authoritative resource delves deep into the design, implementation, and optimization of algorithms tailored for multi-dimensional grids, presenting innovative methodologies that push the boundaries of current knowledge.Structured into 99 meticulously crafted chapters, each dedicated to a specific, cutting-edge algorithm, the book offers an in-depth exploration of techniques that address the complexities of multi-dimensional data structures on modern GPU architectures. Readers will discover a wealth of original theoretical frameworks, groundbreaking ideas, and the latest research breakthroughs in the field.Key Features:Adaptive Parallel QuickSort Techniques: Explore advanced pivot selection methods that enhance load balancing and minimize thread divergence in multi-dimensional data sorting.Optimized Bitonic Sorting for High Dimensions: Delve into extended bitonic sorting algorithms that exploit GPU memory hierarchies for efficient high-dimensional sorting.K-Dimensional Range Search Acceleration: Learn about GPU-accelerated search algorithms that leverage efficient data structures like K-d trees for rapid multi-dimensional querying.Multi-Dimensional Radix and Histogram Sorting: Discover novel key decomposition techniques and histogram-based sorting methods optimized for parallel execution.Hypercube and Space-Filling Curve Algorithms: Understand how to map multi-dimensional data onto hypercube topologies and space-filling curves to exploit inherent parallelism and data locality.Distributed Multi-GPU Sorting Strategies: Gain insights into algorithms that coordinate sorting operations across multiple GPUs, addressing challenges like inter-device communication and load balancing.Tensor-Based Sorting Innovations: Engage with pioneering methods that utilize tensor computations and higher-order singular value decomposition for complex data sorting.Hybrid CPU-GPU Algorithm Design: Investigate strategies that leverage both CPU and GPU resources to manage dynamic multi-dimensional data structures efficiently.Parallel K-Nearest Neighbors Search: Examine high-performance implementations of K-NN algorithms optimized for the challenges of high-dimensional spaces.Advanced Data Structures and Indexing: Study the implementation of efficient multi-dimensional data structures like B-trees, tries, and hash tables on GPU architectures.Whether you are a researcher, advanced practitioner, or graduate student specializing in parallel computing, GPU programming, or high-performance algorithms, this comprehensive volume serves as an indispensable reference. It not only provides detailed explanations and code implementations but also inspires readers to explore uncharted territories in algorithm design and optimization.Equip yourself with the knowledge and tools to harness the full power of GPU acceleration for multi-dimensional data processing, and join the vanguard of computational innovation.
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AR$131.687
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AR$67.532
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