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Execution Model Overview
Thread Mapping and GPU Occupancy
Kernels
Using Libraries for GPU Offload
Host/Device Memory, Buffer and USM
Host/Device Coordination
Using Multiple Heterogeneous Devices
Compilation
OpenMP Offloading Tuning Guide
Multi-GPU, Multi-Stack and Multi-C-Slice Architecture and Programming
Level Zero
Performance Profiling and Analysis
Configuring GPU Device
Sub-Groups and SIMD Vectorization
Removing Conditional Checks
Registerization and Avoiding Register Spills
Small Register Mode vs. Large Register Mode
Shared Local Memory
Pointer Aliasing and the Restrict Directive
Synchronization among Threads in a Kernel
Considerations for Selecting Work-Group Size
Prefetch
Reduction
Kernel Launch
Executing Multiple Kernels on the Device at the Same Time
Submitting Kernels to Multiple Queues
Avoiding Redundant Queue Constructions
Programming Intel® XMX Using SYCL Joint Matrix Extension
Doing I/O in the Kernel
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Using Libraries for GPU Offload
Several libraries are available with oneAPI toolkits that can simplify the programming process by providing specialized APIs for use in optimized applications. This section provides steps on using the libraries, including code samples, for application accelerations. Detailed information about each library, including the available APIs, is available in the main documentation for the specific library.