Tracked topic
… The NVIDIA Nsight Systems tool helped identify the performance regression in SYCL binary running on an NVIDIA GPU. By fixing this regression, the SYCL binary running on an NVIDIA A100 GPU roughly matched the performance of CUDA binary running on an NVIDIA A100 GPU. …
… 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… …
… SeisAcoMod2D is developed in C to efficiently use the multicore CPU architecture and in CUDA C to make use of NVIDIA GPU architecture. The existing CUDA C program cannot run on Intel GPUs nor any other vendor GPUs, for that matter . …
… This demonstrated that our oneAPI ports perform comparably to the original CUDA implementations. As such, we expect that running on Intel GPUs that are more powerful than the integrated graphics Intel® HD Graphics P630 will yield comparable performance to CUDA on NVIDIA GPUs. …
… S5BV-MB LBG-1G , 2S Intel Xeon Platinum 8280L processor 384 GB 12 x 32 GB DDR4 2933 MT/s , ucode: 0x400320a, NVIDIA Tesla V100-PCIE-32GB, CUDA 12.2, Rocky Linux 9.0, Kernel: 5.14.0-70.13.1.el9 0.x86 64, BIOS 3B19.Q104, Intel oneAPI Base Toolkit 2023.1, oneAPI DPC++ Compiler for LLVM nvptx64-nvidia-… …
… Without any performance optimization yet, for simulations of urban flooding in a large city, the SYCL code can be over 10% faster 1 than the original CUDA code on the same NVIDIA A100 GPUs. …
… Additional Resources Academic oneAPI Centers of Excellence Essentials of SYCL CUDA to SYCL Catalog Migrate from CUDA to C++ with SYCL Workflow for a CUDA to SYCL Migration An Awesome List of oneAPI Projects SYCLomatic 1
… The application performance improved by 1.75x on Intel® Data Center GPU Max Series 1550 when compared to an NVIDIA A100 GPU. …
… 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… …
… The Poisson equation code is developed in CUDA , limiting its execution to vendor-specific GPUs. …