Data Parallel C++

kernels-Choosing a parallelism/coding style
Chapter 5: Error handlingSYCL uses C++-style error handling. This is different/more modern than people using OpenCL and CUDA are used to. This chapter must frame the differences, and provide samples from which readers can manage exceptions easily in their code.-Exception-based-Synchronous and asynchronous exceptions-Strategies for error management-Fallback queue mechanism
Chapter 6: USM in detailUSM is a key usability feature when porting code, from C++ for example. When mixed with differing hardware capabilities, the USM landscape isn't trivial to understand. This key chapter must leave the reader with an understanding of USM on different hardware capabilities, what is guaranteed at each level, and how to write code with USM features.-Usability-Device capability levels-Allocating memory-Use of data in kernels-Sharing of data between host and devices-Data ownership and migration-USM as a usability feature-USM as a performance feature-Relation to OpenCL SVM
Chapter 7: Buffers in detailBuffers will be available on all hardware, and are an important feature for people writing code that doesn't have pointer-based data structures, particularly when implicit dependence management is desired. This chapter must cover the more complex aspects of buffers in an accessible waym, including when data movement is triggered, sub-buffer dependencies, and advanced host/buffer synchronization (mutexes).-Buffer construction-Access modes (e.g. discard_write) and set_final_data-Device accessors-Host accessors-Sub-buffers for finer grained DAG dependencies-Explicit data motion-Advanced buffer data sharing between device and host
Chapter 8: DAG scheduling in detailMust describe the DAG mechanism from a high level, which the spec does not do. Must describe the in-order simplifications, and common gotchas that people hit with the DAG (e.g. read data before buffer destruction and therefore kernel execution).-Queues-Common gotchas with DAGs-Synchronizing with the host program-Manual dependency management
Chapter 9: Local memory and work-group barriers-"Local" memory-Managing "local" memory-Work-group barriers
Chapter 10: Defining kernels-Lambdas-Functors-OpenCL interop objects
Chapter 11: Vectors-Vector data types-Swizzles-Mapping to hardware
Chapter 12: Device-specific extension mechanism-TBD
Chapter 13: Programming for GPUs-Use of sub-groups-Device partitioning-Data movement-Images and samplers-TBD
Chapter 14: Programming for CPUs-Loop vectorization-Use of sub-groups-TBD
Chapter 15: Programming for FPGAs-Pipes-Memory controls-Loop controls
Chapter 16: Address spaces and multi_ptr-Address spaces-The multi_ptr class-Intefacing with external code
Chapter 17: Using libraries-Linking to external code-Exchanging data with libraries
Chapter 18: Working with OpenCL-Interoperability-Program objects-Build options-Using SPIR-V kernels
Chapter 19: Memory model and atomics-The memory model-Fences-Buffer atomics-USM atomics