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    CUDA Application Design and Development

    CUDA Application Design and Development

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    • Format
    • Bog, paperback
    • Engelsk

    Beskrivelse

    As the computer industry retools to leverage massively parallel graphics processing units (GPUs), this book is designed to meet the needs of working software developers who need to understand GPU programming with CUDA and increase efficiency in their projects. CUDA Application Design and Development starts with an introduction to parallel computing concepts for readers with no previous parallel experience, and focuses on issues of immediate importance to working software developers: achieving high performance, maintaining competitiveness, analyzing CUDA benefits versus costs, and determining application lifespan. The book then details the thought behind CUDA and teaches how to create, analyze, and debug CUDA applications. Throughout, the focus is on software engineering issues: how to use CUDA in the context of existing application code, with existing compilers, languages, software tools, and industry-standard API libraries. Using an approach refined in a series of well-received articles at Dr Dobb's Journal, author Rob Farber takes the reader step-by-step from fundamentals to implementation, moving from language theory to practical coding.

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    Java Python Data mining Development Memory Scalability Computer architecture Machine learning Parallel programming (Computer science) Application software Monte-Carlo Libraries OPTIMIZATION Reduction Thrust OpenGL OpenMP DDD Peak performance CUDA Sobel Edge Detection Kernel Shared memory Live-Video Interoperability Task parallelism NLPCA TCP Profiling Functor Phylogenetic trees MPI InfiniBand Data parallelism API MPEG Runtime Rendering Asynchronous Mutual Information Support vector machine (SVM) Neural network PCA Debugging X86 L1 Cache balance ratios Amdhal's law Asynchronous kernel execution cuda-gdb Curse of dimensionality Constant memory data reduction. Curse of dimensionality Execution Model frames per second Facial segmentation Computational universal Global Memory Force directed graph layout gpuDirect Levenburg-Marquardt mapped memory MDS (Multi Dimensional Scaling) ffmpeg Order of magnitude ILP (Instruction-level Parallelism) Principle Components Primitive restart petaflop PGI (the Portland Group) Prefetch register memory Ptx Kiviat SM (Streaming Multiprocessor) texture memory L2 Cache Visual profiler Parallel Nsight MultiGPU Perlin Noise Nelder-Mead UVA (Unified Virtual Address) space top 500 teraflop TLP (Thread-level parallelism)
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