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High Performance Parallelism Pearls shows how to leverage parallelism on processors and coprocessors with the same programming;
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High Performance Parallelism Pearls Volume 2 offers another set of examples that demonstrate how to leverage parallelism. Similar to;
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High Performance Computing: Programming and Applications presents techniques that address new performance issues in the programming of high;
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High Performance Computing: Programming and Applications presents techniques that address new performance issues in the programming of high;
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of parallel query processing, presents an important opportunity to understand and utilize high-performance parallel database processing within a major;
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organized in topical sections on JIT compilation and code generation, program analysis, reversible computing and interpreters, parallelism and high;
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support tools and environments; performance and power modeling, prediction and evaluation; scheduling and load balancing; high performance;
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, held in Grenoble, France, in August 2016. The 47 revised full papers presented together with 2 invited papers and one industrial paper;
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Parallelism in Bioinformatics) - PELGA (Second Workshop on Performance Engineering for Large-Scale Graph Analytics) - REPPAR (Third International;
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named: applications, locality, task parallelism, extensions, tools, accelerator programming, and performance evaluations and optimization.;
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algorithms to find solutions. The book is divided into three parts: Part One: Introduction to Metaheuristics and Parallelism, including an;
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Evaluation; Extended Parallelism Models: Performance Analysis and Tools; and Advanced Data Management with OpenMP.;
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As Moore's Law and Dennard scaling trends have slowed, the challenges of building high-performance computer architectures while maintaining;
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in topical sections entitled: resilience; accelerators; performance; memory systems; parallelism and many-core; scheduling; power/energy.;
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of achieving parallelism as the key to unlocking the power of multiple processor architectures. Additionally, the new edition has expanded and updated;
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-point format, parallel patterns, and dynamic parallelism are covered in depth. This best-selling guide to CUDA and GPU parallel programming has;
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* Explore the benefits of lazy evaluation, compiler features, and tools and libraries designed for high performance * Write fast programs at;
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, prediction and evaluation; scheduling and load balancing; high performance architectures and compilers; data management, analytics and deep learning;
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parallelism. Furthermore, support for it was already included in many commodity processors. However, in the past decade, SIMD execution has seen a;
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. Superscalar architecture can execute more than one instruction per each cycle. The amount of instruction level parallelism will become more and more;
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As Moore's Law and Dennard scaling trends have slowed, the challenges of building high-performance computer architectures while maintaining;
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selected in this volume cover various aspects of high performance logic and circuits for high-speed electronic systems.;
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As particle accelerators strive forever increasing performance, high intensity particle beams become one of the critical demands requested;
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get faster: performance is no longer an issue, we'll let hardware do the work. But if you're looking at this book, you're not one of them;
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Written by high performance computing (HPC) experts, Introduction to High Performance Computing for Scientists and Engineers provides a;
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hybrid parallelism in new HPC systems; workshop on power and energy aspects of computations (PEAC 2019); special session on tools for energy;
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written by experts in the field. In addition, it also covers applications for emerging technologies in High-Speed Electronics.In summary, topics;
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