- updates to support ROCm 5.2
- workarounds in tests where NV tools were used unconditionally
- implemented `get_num_blocks()` and `add_memfence()` for AMD GPU
- backported from history some atomics
- added bf16 support
- minor warnings cleanup
- added dockerfile to run on a ROCm enabled machine
Co-authored-by: B1tway <andrew.shukshov@gmail.com>
Co-authored-by: Andrey Shukshov <36711069+B1tway@users.noreply.github.com>
- Removed driver module -- accelerator runtime is handled by pytorch
- Added basic support for ROCM based on @micmelesse 's PR -- now can execute empty kernel on AMD devices without any compile-time changes
- Now only using PREFER_SHARED for kernels when the size of shared memory is greater than 49k. Otherwise there can be poor L1 performance for broadcast tensors
* Load libcuda.so.1 if libcuda.so is not there. Error if both aren't
there.
* Support for multiple grad_to_none in triton.testing.do_bench
* Benchmark dataframe printed along with name
- A100 support via mma.16816
- Thread swizzling for conflict-free shared memory accesses without
padding
- Complete overhaul of the LLVM code generation in
codegen/selection/generator.cc to remove overengineering
- Added debugging capabilities in the Python binding
- Compilation error for kernels that spill