Data Parallel C++ : : Mastering DPC++ for Programming of Heterogeneous Systems using C++ and SYCL / / by James Reinders, Ben Ashbaugh, James Brodman, Michael Kinsner, John Pennycook, Xinmin Tian.
Learn how to accelerate C++ programs using data parallelism. Data parallelism in C++ enables access to parallel resources in a modern heterogeneous system, freeing you from being locked into any particular computing device. Now a single C++ application can use any combination of devices—including GP...
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| Place / Publishing House: | Berkeley, CA : : Apress :, Imprint: Apress,, 2021. |
| Year of Publication: | 2021 |
| Edition: | 1st ed. 2021. |
| Language: | English |
| Physical Description: | 1 online resource (XXVI, 548 p. 338 illus., 280 illus. in color.) |
| Notes: | Includes index. |
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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: USM in detail
- Chapter 7: Buffers in detail
- Chapter 8: DAG scheduling in detail
- Chapter 9: Local memory and work-group barriers
- Chapter 10: Defining kernels
- Chapter 11: Vectors
- Chapter 12: Device-specific extension mechanism
- Chapter 13: Programming for GPUs
- Chapter 14: Programming for CPUs
- Chapter 15: Programming for FPGAs
- Chapter 16: Address spaces and multi_ptr
- Chapter 17: Using libraries
- Chapter 18: Working with OpenCL
- Chapter 19: Memory model and atomics.