Programming Massively Parallel Processors: A Hands-On Approach (Paperback, 3)

1. Introduction 2. Data parallel computing 3. Scalable parallel execution 4. Memory and data locality 5. Performance considerations 6. Numerical considerations 7. Parallel patterns: convolution: An introduction to stencil computation 8. Parallel patterns: prefix sum: An introduction to work efficiency in parallel algorithms 9. Parallel patterns-parallel histogram computation: An introduction to atomic operations and privatization 10. Parallel patterns: sparse matrix computation: An introduction to data compression and regularization 11. Parallel patterns: merge sort: An introduction to tiling with dynamic input data identification 12. Parallel patterns: graph search 13. CUDA dynamic parallelism 14. Application case study-non-Cartesian magnetic resonance imaging: An introduction to statistical estimation methods 15. Application case study-molecular visualization and analysis 16. Application case study-machine learning 17. Parallel programming and computational thinking 18. Programming a heterogeneous computing cluster 19. Parallel programming with OpenACC 20. More on CUDA and graphics processing unit computing 21. Conclusion and outlook