High Performance Parallelism Pearls: Multicore and Many-core Programming Approaches
- 9h 33m
- James Reinders, Jim Jeffers
- Elsevier Science and Technology Books, Inc.
- 2015
High Performance Parallelism Pearls shows how to leverage parallelism on processors and coprocessors with the same programming - illustrating the most effective ways to better tap the computational potential of systems with Intel Xeon Phi coprocessors and Intel Xeon processors or other multicore processors. The book includes examples of successful programming efforts, drawn from across industries and domains such as chemistry, engineering, and environmental science. Each chapter in this edited work includes detailed explanations of the programming techniques used, while showing high performance results on both Intel Xeon Phi coprocessors and multicore processors. Learn from dozens of new examples and case studies illustrating "success stories" demonstrating not just the features of these powerful systems, but also how to leverage parallelism across these heterogeneous systems.
- Promotes consistent standards-based programming, showing in detail how to code for high performance on multicore processors and Intel Xeon PhiT
- Examples from multiple vertical domains illustrating parallel optimizations to modernize real-world codes
- Source code available for download to facilitate further exploration
In this Book
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Introduction
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From "Correct" to "Correct & Efficient": A Hydro2D Case Study with Godunov's Scheme
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Better Concurrency and SIMD on HBM
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Optimizing for Reacting Navier-Stokes Equations
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Plesiochronous Phasing Barriers
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Parallel Evaluation of Fault Tree Expressions
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Deep-Learning Numerical Optimization
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Optimizing Gather/Scatter Patterns
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A Many-Core Implementation of the Direct N-Body Problem
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N-Body Methods
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Dynamic Load Balancing Using OpenMP 4.0
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Concurrent Kernel Offloading
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Heterogeneous Computing with MPI
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Power Analysis on the Intel Xeon PHI Coprocessor
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Integrating Intel Xeon Phi Coprocessors into a Cluster Environment
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Supporting Cluster File Systems on Intel Xeon Phi Coprocessors
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Nwchem Quantum Chemistry Simulations at Scale
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Efficient Nested Parallelism on Large-Scale Systems
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Performance Optimization of Black-Scholes Pricing
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Data Transfer Using the Intel Coi Library
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High-Performance Ray Tracing
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Portable Performance with Opencl
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Characterization and Optimization Methodology Applied to Stencil Computations
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Profiling-Guided Optimization
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Heterogeneous MPI Application Optimization with Itac
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Scalable out-of-Core Solvers on a Cluster
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Sparse Matrix-Vector Multiplication: Parallelization and Vectorization
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Morton Order Improves Performance
