#define cudaMemcpyDeviceToHost hipMemcpyDeviceToHost #define cudaMemcpyHostToDevice hipMemcpyHostToDevice For example, a simple vector addition code might use the following header file: #include "hip/hip_runtime.h" The new piece of information I'd like to contribute is that if someone doesn't want to hipify their existing CUDA code (i.e., change all CUDA API calls to HIP API calls), there is another option that can be used simply add (and include) a header file that redefines the CUDA calls as HIP calls. Then the HIP code can be compiled and run on either NVIDIA (CUDA backend) or AMD (ROCm backend) GPUs. As also stated, existing CUDA code could be hipify-ed, which essentially runs a sed script that changes known CUDA API calls to HIP API calls. You can now leverage Apple’s tensorflow-metal PluggableDevice in TensorFlow v2.5 for accelerated training on Mac GPUs directly with Metal.Īs others have already stated, CUDA can only be directly run on NVIDIA GPUs. Testing conducted by Apple in October and November 2020 using a production 3.2GHz 16-core Intel Xeon W-based Mac Pro system with 32GB of RAM, AMD Radeon Pro Vega II Duo graphics with 64GB of HBM2, and 256GB SSD. This support for macOS 12.0+( as per their claim ) HIP code can run on AMD hardware (through the HCC compiler) or NVIDIA hardware (through the NVCC compiler) with no performance loss compared with the original CUDA code. The HIPify tool automates much of the conversion work by performing a source-to-source transformation from CUDA to HIP.
The C++ interface can use templates and classes across the host/kernel boundary. It provides a C-style API and a C++ kernel language.
OPENGL NVIDIA CUDA TOOLKIT 9 WINDOWS 10 PORTABLE
Heterogeneous-Computing Interface for Portability (HIP) is a C++ dialect designed to ease conversion of CUDA applications to portable C++ code.
It seems the support is only for Linux systems.( ) ROCm supports the major ML frameworks like TensorFlow and PyTorch with ongoing development to enhance and optimize workload acceleration. These are some basic details I could find.
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