Data Parallel C++ : Programming Accelerated Systems Using C++ and SYCL / / by James Reinders, Ben Ashbaugh, James Brodman, Michael Kinsner, John Pennycook, Xinmin Tian.
"This book, now in is second edition, is the premier resource to learn SYCL 2020 and is the ONLY book you need to become part of this community." Erik Lindahl, GROMACS and Stockholm University Learn how to accelerate C++ programs using data parallelism and SYCL. This open access book enabl...
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| Place / Publishing House: | Berkeley, CA : : Apress :, Imprint: Apress,, 2023. |
| Year of Publication: | 2023 |
| Edition: | 2nd ed. 2023. |
| Language: | English |
| Physical Description: | 1 online resource (XXX, 630 p. 329 illus., 294 illus. in color.) |
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Table of Contents:
- Chapter 1: Introduction
- Chapter 2: Where Code Executes
- Chapter 3: Data Management and Ordering the Uses of Data
- Chapter 4: Expressing Parallelism
- Chapter 5: Error Handling
- Chapter 6: Unified Shared Memory
- Chapter 7: Buffers
- Chapter 8: Scheduling Kernels and Data Movement
- Chapter 9: Local Memory and Work-group Barriers
- Chapter 10: Defining Kernels
- Chapter 11: Vector and Math Arrays
- Chapter 12: Device Information and Kernel Specialization
- Chapter 13: Practical Tips
- Chapter 14: Common Parallel Patterns
- Chapter 15: Programming for GPUs
- Chapter 16: Programming for CPUs
- Chapter 17: Programming for FFGAs
- Chapter 18: Libraries
- Chapter 19: Memory Model and Atomics
- Chapter 20: Backend Interoperability
- Chapter 21: Migrating CUDA Code
- Epilogue.