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370efa6c08
* refactor * start * add device gemm file * add BatchStrideD0 * add stridd0 * add gridwise file * add d0 parameters to gridwise gemm * add c layout transformer * add d0 threadwise copy * init kernel * init kernel * regular code * nm desc put to out * kernel parameter can not use reference * host add bias+gelu * run right for bias+gelu * change AddFastGelu into another file * interface add d1 bias parameters * add d1 parameter to argument * add d1 parameter to gridwise * first all code,not verify * gelu change to relu and GetElementSpaceSize bug * add instance * start add to ckprofiler * ckprofiler finish code * change input parameter for ckProfiler * fix host bias+gelu bug * show help for ckProfiler * fix bug for lunch kernel ignore parametes * add pad and fix about bug * mutiple d0 * add dynamic d0_element_op * change profiler and instance to mutiple d0 * example have 2 d0 * remove some comments not using * change 2 d0 have self parameters * change d element_op name * change class name(multiple_d) * fix bug * fix bug that don't find file * update profiler * refactor * update profiler * clean * revert example change * add gon layout * optimize parameter for gno * add gon to gemm+gemm * change helping input parameters * change to GemmPadder_v2 * using ForEach * fix gb_per_sec Co-authored-by: Chao Liu <lc.roy86@gmail.com> Co-authored-by: ltqin <letaoqin@amd.com>
Profile GEMM kernels
#arg1: tensor operation (gemm=GEMM)
#arg2: data type (0=fp32, 1=fp16)
#arg3: matrix layout (0=NN, 1=NT, 2=TN, 3=TT)
#arg4: verification (0=no, 1=yes)
#arg5: initialization (0=no init, 1=integer value, 2=decimal value)
#arg6: print matrix value (0=no, 1=yes)
#arg7: run kernel # of times (>1)
#arg8 to 13: M, N, K, StrideA, StrideB, StrideC
################ op datatype layout verify init log repeat M___ N___ K___ StrideA StrideB StrideC
./bin/ckProfiler gemm 1 1 1 1 0 5 3840 4096 4096 4096 4096 4096
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}
c_m_n: dim 2, lengths {3840, 4096}, strides {4096, 1}
....
Best Perf: 1.1933 ms, 107.977 TFlops, 79.0848 GB/s
Profile 2d forward convolution kernels
#arg1: tensor operation (conv=Convolution)
#arg2: data type (0=fp32, 1=fp16)
#arg3: input tensor layout (0=NCHW, 1=NHWC)
#arg4: weight tensor layout (0=KCYX, 1=KYXC)
#arg5: output tensor layout (0=NKHW, 1=NHWK)
#arg6: verification (0=no, 1=yes)
#arg7: initialization (0=no init, 1=integer value, 2=decimal value)
#arg8: print matrix value (0=no, 1=yes)
#arg9: run kernel # of times (>1)
#arg10 to 24: N, K, C, Y, X, Hi, Wi, Sy, Sx, Dy, Dx, LeftPy, LeftPx, RightPy, RightPx
################ op datatype in_layout wei_layout out_layout verify init log repeat N__ K___ C___ Y X Hi__ Wi__ Strides Dilations LeftPads RightPads
./bin/ckProfiler conv2d_fwd 1 1 1 1 1 1 0 5 128 256 192 3 3 71 71 2 2 1 1 1 1 1 1
Result (MI100 @ 1087Mhz, 133.5TFlops peak FP16)
in_n_c_hi_wi: dim 4, lengths {128, 192, 71, 71}, strides {967872, 1, 13632, 192}
wei_k_c_y_x: dim 4, lengths {256, 192, 3, 3}, strides {1728, 1, 576, 192}
out_n_k_ho_wo: dim 4, lengths {128, 256, 36, 36}, strides {331776, 1, 9216, 256}
....
Best Perf: 1.42509 ms, 102.988 TFlops, 234.086 GB/s