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4a2a56c22f
* Rangify STL algorithms This commit adapts rangified std::copy(), std::fill() & std::transform() * Rangify check_err() By rangifying check_err(), we can not only compare values between std::vector<>s, but also compare any ranges which have same value type. * Allow constructing Tensor<> like a HostTensorDescriptor * Simplify Tensor<> object construction logics * Remove more unnecessary 'HostTensorDescriptor' objects * Re-format example code * Re-write more HostTensorDescriptor ctor call
Instructions for example_gemm_add_add_fastgelu_xdl_fp16
Run example_gemm_add_add_fastgelu_xdl_fp16
#arg1: verification (0=no, 1=yes)
#arg2: initialization (0=no init, 1=integer value, 2=decimal value)
#arg3: time kernel (0=no, 1=yes)
#arg4 to 11: M (256x), N(128x), K(32x), StrideA, StrideB, StrideD0, StrideD1, StrideE"
./bin/example_gemm_add_add_fastgelu_xdl_fp16 1 1 1
Result (MI100 @ 1087Mhz, 133.5TFlops peak FP16)
a_m_k: dim 2, lengths {3840, 4096}, strides {4096, 1}
b_k_n: dim 2, lengths {4096, 4096}, strides {1, 4096}
d0_m_n: dim 2, lengths {3840, 4096}, strides {0, 1}
d1_m_n: dim 2, lengths {3840, 4096}, strides {4096, 1}
e_m_n: dim 2, lengths {3840, 4096}, strides {4096, 1}
launch_and_time_kernel: grid_dim {480, 1, 1}, block_dim {256, 1, 1}
Warm up 1 time
Start running 10 times...
Perf: 1.26914 ms, 101.525 TFlops, 100.804 GB/s, DeviceGemmMultipleD_Xdl_CShuffle<256, 256, 128, 32, 8, 8>