- Virtual functions, indirect functions and try/catch
-`__prof_trigger`
- PTX assembly
- See the [HIP Kernel Language](hip_kernel_language.md) for more information.
### How does HIP compare with OpenCL?
Both AMD and Nvidia support OpenCL 1.2 on their devices, so developers can write portable code.
HIP offers several benefits over OpenCL:
- Developers can code in C++ as well as mix host and device C++ code in their source files. HIP C++ code can use templates, lambdas, classes and so on.
- HIP uses the best available development tools on each platform: on Nvidia GPUs, HIP code compiles using NVCC and can employ the nSight profiler and debugger (unlike OpenCL on Nvidia GPUs).
- HIP provides pointers and host-side pointer arithmetic.
- HIP provides device-level control over memory allocation and placement.
NVCC is Nvidia's compiler driver for compiling "CUDA C++" code into PTX or device code for Nvidia GPUs. It's a closed-source binary product that comes with CUDA SDKs.
HCC is AMD's compiler driver which compiles "heterogenous C++" code into HSAIL or GCN device code for AMD GPUs. HCC is an open-source compiler based on recent versions of CLANG/LLVM.
Developers who code to the HIP API can be assured there code will remain portable across Nvidia and AMD platforms.
In addition, HIP defines portable mechanisms to query architectural features, and supports a larger 64-bit wavesize which expands the return type for cross-lane functions like ballot and shuffle from 32-bit ints to 64-bit ints.
Yes! HIP's CUDA path only exposes the APIs and functionality that work on both NVCC and HCC back-ends.
"Extra" APIs, parameters, and features which exist in CUDA but not in HCC will typically result in compile-time or run-time errors.
Developers need to use the HIP API for most accelerator code, and bracket any CUDA-specific code with appropriate ifdefs.
Developers concerned about portability should of course run on both platforms, and should expect to tune for performance.
In some cases CUDA has a richer set of modes for some APIs, and some C++ capabilities such as virtual functions - see the HIP @API documentation for more details.
### Can I develop HIP code on an AMD HCC platform?
Yes! HIP's HCC path only exposes the APIs and functions that work on both NVCC and HCC back ends. "Extra" APIs, parameters and features that appear in HCC but not CUDA will typically cause compile- or run-time errors. Developers must use the HIP API for most accelerator code and bracket any HCC-specific code with appropriate ifdefs. Those concerned about portability should, of course, test their code on both platforms and should tune it for performance. Typically, HCC supports a more modern set of C++11/C++14/C++17 features, so HIP developers who want portability should be careful when using advanced C++ features on the hc path.
HIP is a source-portable language that can be compiled to run on either the HCC or NVCC platform. HIP tools don't create a "fat binary" that can run on either platform, however.
HIP is a portable C++ language that supports a strong subset of the CUDA run-time APIs and device-kernel language. It's designed to simplify CUDA conversion to portable C++. HIP provides a C-compatible run-time API, C-compatible kernel-launch mechanism, C++ kernel language and pointer-based memory management.
A C++ dialect, hc is supported by the AMD HCC compiler. It provides C++ run time, C++ kernel-launch APIs (parallel_for_each), C++ kernel language, and several memory-management options, including pointers, arrays and array_view (with implicit data synchronization). It's intended to be a leading indicator of the ISO C++ standard.
