CUDA version 9.2, using multiple P100 server GPUs, you can realize up to 50x performance improvements over CPUs.

OpenMP API specification for parallel programming provides an application programming interface (API) that supports multi-platform shared memory multiprocessing programming in C, C++, and Fortran, on most platforms. It consists of a set of compiler directives, library routines, and environment variables that influence run-time behavior.

The HIPify tool automates much of the conversion work by performing a source-to-source transformation from Cuda to HIP. 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.