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Batchnorm-forward and Batchnorm-infer Implemented using generic kernels (#320)
* Implement multiple-reduction in one kernel (kernels, device ops, examples) * Add generic elementwise kernel and device interface * Add generator for normal-distributed data initialization * Add host refer implementation of batchnorm-forward and batchnorm-infer * Add examples for implementing batchnorm-forward and batchnorm-infer using generic kernels * Remove un-needed including in batchnorm example * Renaming generic_elementwise to elementiwise in kernel and device classes/functions * Change in gemm_layernorm examples to use DeviceElementwise instead of Device5AryElementwise * Change in exampe 19_binary_elementwise to use DeviceElementwise instead of DeviceBinaryElementwise * Change in device_cgemm_4gemm_xdl_cshuffle.hpp to use kernel_elementwise instead of kernel_binary_elementwise * Add DeviceElementwiseBase and use it in device_normalize_instance.cpp * Removing and renaming files * Update to synchronize gemm_layernorm client example to the generic element-wise device op API * Update to synchronize with the latest headers directory and HostTensorDescriptor interface renaming * Merge two static member functions in device_elementwise.hpp * Remove unary_elementwise_1d kernel and device
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example/33_multiple_reduce/README.md
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example/33_multiple_reduce/README.md
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# Instructions for ```example_dual_reduce```
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## Run ```example_dual_reduce_multiblock```
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```bash
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# -D <xxx> : input 4-d tensor lengths
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# -v <x> : verification (0=no, 1=yes)
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#arg1: initialization (0=no init, 1=single integer value, 2=scope integer value, 3=decimal value)
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#arg2: time kernel (0=no, 1=yes)
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./bin/example_dual_reduce_multiblock -D 600,28,28,256 -v 1 2 1
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```
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Result
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```
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./bin/example_dual_reduce_multiblock -D 600,28,28,256 -v 1 2 1
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launch_and_time_kernel: grid_dim {150, 1, 1}, block_dim {256, 1, 1}
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Warm up 1 time
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Start running 10 times...
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Perf: 1.19529 ms, 201.499 GB/s, DeviceMultipleReduceBlockWise<256,M_C4_S1,K_C64_S1,InSrcVectorDim_1_InSrcVectorSize_1,OutDstVectorSize_1_1>
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```
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## Run ```example_dual_reduce_threadwise```
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```bash
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# -D <xxx> : input 4-d tensor lengths
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# -v <x> : verification (0=no, 1=yes)
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#arg1: initialization (0=no init, 1=single integer value, 2=scope integer value, 3=decimal value)
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#arg2: time kernel (0=no, 1=yes)
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./bin/example_dual_reduce_multiblock -D 8000,4,4,4 -v 1 2 1
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```
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Result
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```
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./bin/example_dual_reduce_threadwise -D 8000,4,4,4 -v 1 2 1
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launch_and_time_kernel: grid_dim {32, 1, 1}, block_dim {256, 1, 1}
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Warm up 1 time
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Start running 10 times...
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Perf: 0.01512 ms, 71.9577 GB/s, DeviceMultipleReduceThreadwise<256,M_C256_S1,K_C1_S4,InSrcVectorDim_1_InSrcVectorSize_2,OutDstVectorSize_1_1>
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```
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