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https://github.com/ROCm/composable_kernel.git
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15c89e81f0
* initial stub for standalone softmax * start device_softmax_mk_to_mk as a wrapper to device_reduce_mk_to_m * host softmax validates * compiles; to implement beta scaling * use NaN trick to efficiently ignore OOB values during sum of exponentials * freeload device_reduce's utility functions * clean up interface * adding prior value (beta scaling) * remove restriction related to perf considerations * apply clang-format * clean; disable diagnostics * resolve conflicts * add exp wrapper * honor HostTensorDesc interface; allow implicit cast from different vector<T> type * test softmax for fp16/fp32 * update readme * amend commit NaN trick * remove redundant param added during development * format * replace ScalarDataType with AccDataType * separate out test programs by precision type * move softmax sample code to its own folder * format * keep up with recent changes in reduction API * remove extra header
Instructions for example_reduce_blockwise
Run example_reduce_blockwise
# -D <xxx> : input 4-d tensor lengths
# -v <x> : verification (0=no, 1=yes)
#arg1: initialization (0=no init, 1=single integer value, 2=scope integer value, 3=decimal value)
#arg2: time kernel (0=no, 1=yes)
./bin/example_reduce_blockwise -D 16,64,32,960 -v 1 1 1
Result
./bin/example_reduce_blockwise -D 16,64,32,960 -v 1 1 1
launch_and_time_kernel: grid_dim {240, 1, 1}, block_dim {256, 1, 1}
Warm up 1 time
Start running 10 times...
Perf: 0.282592 ms, 222.641 GB/s, DeviceReduceBlockWise<256,M_C4_S1,K_C64_S1,InSrcVectorDim_0_InSrcVectorSize_1_OutDstVectorSize_1>
Instructions for example_reduce_blockwise_two_call
Run example_reduce_blockwise_two_call
#arg1: verification (0=no, 1=yes(
#arg2: initialization (0=no init, 1=single integer value, 2=scope integer value, 3=decimal value)
#arg3: time kernel (0=no, 1=yes)
./bin/example_reduce_blockwise_two_call 1 2 1
Result
./bin/example_reduce_blockwise_two_call 1 2 1
launch_and_time_kernel: grid_dim {204800, 1, 1}, block_dim {256, 1, 1}
Warm up 1 time
Start running 10 times...
launch_and_time_kernel: grid_dim {6400, 1, 1}, block_dim {256, 1, 1}
Warm up 1 time
Start running 10 times...
Perf: 2.1791 ms, 771.42 GB/s, DeviceReduceBlockWise<256,M_C32_S1,K_C8_S1,InSrcVectorDim_1_InSrcVectorSize_1_OutDstVectorSize_1> => DeviceReduceBlockWise<256,M_C256_S1,K_C1_S1,InSrcVectorDim_1_InSrcVectorSize_1_OutDstVectorSize_1>