Tracked topic
… Configurations/Solution Ingredients: For porting code from CUDA to SYCL: • Windows 10 Enterprise • Microsoft Visual Studio 2019 • Intel® DPC++ Compatibility Tool as part of oneAPI 2024.0.1 For testing on HPC hardware: • On NVIDIA machine Baskerville HPC : 16 or 32 NVIDIA A100 GPUs, Intel® Xeon® Pla… …
… Convert Python Bindings to Enable Calling Custom Kernels To call the kernel from the Python code, the bindings were adapted to use the PyTorch XPU CPP extension DPCPPExtension , which allowed the migrated kernels to be installed into the deployment environment by using a setup.py script: Original C… …
… Expanding Code Portability with SYCL and Intel Traditionally, creating portable code that can run across heterogeneous processors required compiling unique kernels for each hardware type—CUDA kernels for NVIDIA GPUs, HIP kernels for AMD GPUs, and C/C++ for x86 and RISC CPUs. …