- Use symbol value as the qeury key. Compared to the symbol name, the
symbol value is more robust as developers may use unqualified or
qualified identifiers. It also removes the mangling and/or demangling
requirement for the runtime API.
Change-Id: I9d4259f3842612c7cc98551269fc2092d8b5c19e
[ROCm/hip commit: b72196613a]
This is cherry-picked from PR#1947 that was committed to the
github repo. It allows printf to work with hip-clang and HCC
runtime.
Change-Id: I754753250ea1e694cf3441722e2d4c9d25fa75bc
[ROCm/hip commit: 9a0c5d0653]
This also adds declarations of all the missing texture APIs.
hipTexRefSet*() functions need to take a textureReference as a ptr for type erasure to work. Runtime has been modified to accomodate this.
This change only applies to VDI.
Change-Id: Icf43cc5bd44dfc2c39084b7fe56d5a793bf7319f
[ROCm/hip commit: 2028b6eb29]
* Fix cooperative launch APIs to set hipGetLastError
Previously, the cooperative launch APIs did not properly log their
errors in the global hipGetLastError variable before returning back
to the user. As such, the APIs would leave hipSuccess in the
last error, which would break some use cases.
This fixes that problem by making a trampoline function that does
the HIP_INIT_API and ihipLogStatus.
* Add missing flag to the log of multi-GPU launch
[ROCm/hip commit: f61b79d9a3]
What Cuda refers to "linear texture memory" is the OpenCL equivalent of CL_MEM_OBJECT_IMAGE1D_BUFFER. For these types of allocations we should create a typed buffer instead of an image.
Currently there is no check in the texture fetch functions as to what kind of SRD is written into the texture object, so any kind of incorrect programming will cause the TA to hang. Fortunately for us, every one writes correct code :)
Change-Id: I80dab85a992f2c0754ebf303d40ac6b5e045c7c1
[ROCm/hip commit: 4829a7c215]
Currently the texture C++ API is forwarded to the ihip*Impl() calls, which are not even a part of Cuda. These should be forwarded to their respective Cuda C APIs instead.
This change also fixes a bug with hipUnbindTexture() creating a dangling pointer.
Change-Id: Ifafc9d106855a11bec84a18ea214b3d89e39990d
[ROCm/hip commit: 5429b40afe]
Similar to the previous patch, this change adds type constraints to texture indirect functions. Since we don't have to deduce the return type for these, we simply just have to check if the user provided a valid channel type.
Change-Id: Ia094bd6126e01df2ea90902c9aa59cb6cfe85773
[ROCm/hip commit: 117f0ab102]
When sampling a pixel the hw always returns a float4. The type in the texture reference controls the bitcast that we perform before returning the sampled pixel. Creating a texture with an unsupported will lead to potential UB.
This change makes it so that it's only possible to use textures with a type that makes sense. Using something like texture<int, hipTextureType1D, hipReadModeNormalizedFloat> will now lead to a compilation error with a message "Invalid channel type!".
Change-Id: I7fde44cb1d4b9737e0c48c28cb59c018c59ccaa2
[ROCm/hip commit: ef2415edc7]
HIP-Clang cuda_wrapper headers require clang include path before standard C++ include path.
However libc++ include path requires to be before clang include path.
To workaround this, we pass -isystem with the parent directory of clang include
path instead of the clang include path itself.
[ROCm/hip commit: 08d9759eba]
This change addresses three things.
First the available APIs are brought up to par with Cuda (missing ones are added and incorrect ones removed).
Second the size of hip/hcc_detail/texture_functions.h. Using some template magic we can bring down the code size down from ~11k lines to only ~900 lines in total.
Third this change fixes some bugs in the declaration of the texture fetch funcitons. Currently the return type for textures with read mode set to hipReadModeNormalizedFloat is not float. This causes pixel data to be lost during the bitcast when the texture pixel element size is less than the size of float.
The new headers will only be enabled for VDI to avoid breaking HCC.
Change-Id: I77cb29293fb79e55681be094c37702a48d80b64c
[ROCm/hip commit: a0751402d8]
This allows printf to work with hip-clang and HCC runtime. See comments under #1919 for a reported bug and feature request.
[ROCm/hip commit: 899c878703]
GCC emits a warning about using static functions like
hipCUDAErrorTohipError inside this function, because it has an
inline directive, but it's not static. Adding static to this function
to silence warnings (and prevent potential problems in the future).
[ROCm/hip commit: f7e85649f4]
NVCC warned if you tried to use hipOccupancyMaxActiveBlocksPerMultiprocessor
because when passing in a device function pointer, "const void* func" was
insufficient to describe it accurately. Adding a C++ templated class type
definition for this function.
[ROCm/hip commit: 4128d68ed7]
- Need to check the availability of `__has_attribute` builtin macro
instead of compiler versions. That's more reliable and portable among
various compilers.
- Provides a very basic support of vectors for unknown compilers.
[ROCm/hip commit: 774035d869]
There are now two implementations of printf in HIP:
1. The implemenation for HCC is controlled by the HC_FEATURE_PRINTF
macro, and it works only with the HCC compiler used in combination
with the HCC runtime.
2. The implementation for hip-clang requires the VDI runtime, and is
always enabled with that combination.
Change-Id: Ibaeda7900ffe2ce602ca0094aafed0f1147ac2b6
[ROCm/hip commit: 64cd527335]
There are now two implementations of printf in HIP:
1. The implemenation for HCC is controlled by the HC_FEATURE_PRINTF
macro, and it works only with the HCC compiler used in combination
with the HCC runtime.
2. The implementation for hip-clang requires the VDI runtime, and is
always enabled with that combination.
[ROCm/hip commit: 09130b3b92]
Fix compilation error on hip-hcc+clang , hip-vdi+clang
Enabled hipExtLaunchMultiKernelMultiDevice test on hip-vdi path
hipExtLaunchMultiKernelMultiDevice common declaration for all paths
Change-Id: I76031840614fce8e12a8e845548fa43a389a741a
[ROCm/hip commit: 6a5d04209c]
Michael LIAO
Maneesh Gupta
Sameer Sahasrabuddhe
Siu Chi Chan
Vladislav Sytchenko
Sarbojit2019
Benjamin Sherman
Joseph Greathouse
Nick Curtis
Yaxun (Sam) Liu
Sarbojit Sarkar
Jatin Chaudhary
Aryan Salmanpour
mhbliao
Sameer Sahasrabuddhe
Evgeny Mankov
Alex Voicu
Lad, Aditya
agodavar
saleelk
Rahul Garg