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| //////////////////////////////////////////////////////////////////////////////////////////////////// | |
| namespace layer_norm { | |
| template< | |
| uint32_t HIDDEN_SIZE_, | |
| typename weight_t_, | |
| typename input_t_, | |
| typename residual_t_, | |
| typename output_t_, | |
| typename compute_t_, | |
| typename index_t_, | |
| uint32_t THREADS_PER_CTA_ | |
| > | |
| struct Kernel_traits_base { | |
| using weight_t = weight_t_; | |
| using input_t = input_t_; | |
| using residual_t = residual_t_; | |
| using output_t = output_t_; | |
| using compute_t = compute_t_; | |
| using index_t = index_t_; | |
| enum { HIDDEN_SIZE = HIDDEN_SIZE_ }; | |
| enum { THREADS_PER_CTA = THREADS_PER_CTA_ }; | |
| enum { THREADS_PER_WARP = 32 }; | |
| }; | |
| //////////////////////////////////////////////////////////////////////////////////////////////////// | |
| template< | |
| uint32_t HIDDEN_SIZE_, | |
| typename weight_t_, | |
| typename input_t_, | |
| typename residual_t_, | |
| typename output_t_, | |
| typename compute_t_, | |
| typename index_t_, | |
| bool Has_colscale, | |
| uint32_t THREADS_PER_CTA_, | |
| uint32_t BYTES_PER_LDG_, | |
| typename Base = Kernel_traits_base<HIDDEN_SIZE_, | |
| weight_t_, | |
| input_t_, | |
| residual_t_, | |
| output_t_, | |
| compute_t_, | |
| index_t_, | |
| THREADS_PER_CTA_> | |
| > | |
| struct Kernel_traits_finalize : public Base { | |
| enum { ROWS_PER_CTA = Base::THREADS_PER_CTA / Base::THREADS_PER_WARP }; | |
| static_assert((int) ROWS_PER_CTA <= (int) Base::THREADS_PER_WARP); | |
| // Bytes per global load from the input. | |
| enum { BYTES_PER_LDG = BYTES_PER_LDG_ }; | |
| // Number of elements fetched by a global load. | |
| enum { ELTS_PER_LDG = BYTES_PER_LDG / sizeof(compute_t_) }; | |
| // Bytes per global store of the weights. | |
| enum { BYTES_PER_STG = ELTS_PER_LDG * sizeof(weight_t_) }; | |
| static_assert(sizeof(BYTES_PER_LDG) == 4, "Conflict-free smem transpose only implemented for 4B compute type!"); | |
| static_assert(Base::THREADS_PER_CTA == ROWS_PER_CTA * Base::THREADS_PER_WARP, "We assume one warp per row!"); | |
| // The total number of BYTES_PER_LDG-wide words in a hidden vector. | |
| enum { COLS = HIDDEN_SIZE_ * sizeof(compute_t_) / BYTES_PER_LDG }; | |
| static_assert(COLS * BYTES_PER_LDG == HIDDEN_SIZE_ * sizeof(compute_t_)); | |
| // Shared memory size to transpose the CTA result. | |
| enum { SMEM_BYTES_TRANSPOSE = Base::THREADS_PER_CTA * BYTES_PER_LDG }; | |
| // Shared memory size to coalsece the CTA result. | |
| enum { SMEM_BYTES_OUTPUT = Base::THREADS_PER_WARP * BYTES_PER_LDG }; | |
| // Shared memory requirement per CTA. | |
| static constexpr int NUM_FACTORS = Has_colscale ? 3 : 2; | |
| enum { SMEM_BYTES_PER_CTA = NUM_FACTORS * SMEM_BYTES_TRANSPOSE + NUM_FACTORS * SMEM_BYTES_OUTPUT }; | |
| // The type of the reducer. | |
| using Reducer = layer_norm::Reducer<compute_t_, 1, 1, 1>; | |
| // Condition for the whole CTA to participate in syncthreads. | |
| static_assert(COLS % Base::THREADS_PER_WARP == 0); | |
| enum { CTAS = COLS / Base::THREADS_PER_WARP }; | |
| }; | |
| //////////////////////////////////////////////////////////////////////////////////////////////////// | |
| template< | |
| typename weight_t_, | |
| typename input_t_, | |
| typename residual_t_, | |
| typename output_t_, | |
| typename compute_t_, | |
| typename index_t_, | |
| uint32_t HIDDEN_SIZE_, | |
| uint32_t CTAS_PER_ROW_, | |
| uint32_t WARPS_M_, | |
| uint32_t WARPS_N_, | |
| uint32_t BYTES_PER_LDG_ = 16, | |
| typename Base = Kernel_traits_base< | |
| HIDDEN_SIZE_, | |
| weight_t_, | |
| input_t_, | |
| residual_t_, | |
| output_t_, | |
| compute_t_, | |
| index_t_, | |
| WARPS_M_*WARPS_N_*THREADS_PER_WARP | |
| > | |
| > | |
| struct Kernel_traits : public Base { | |
| using input_t = typename Base::input_t; | |
| using residual_t = typename Base::residual_t; | |
| using weight_t = typename Base::weight_t; | |
| using compute_t = typename Base::compute_t; | |
| using output_t = typename Base::output_t; | |
| using index_t = typename Base::index_t; | |
| // using mask_t = unsigned char; | |
| using mask_t = bool; | |
| enum { CTAS_PER_ROW = CTAS_PER_ROW_ }; | |
| enum { WARPS_M = WARPS_M_ }; | |
| enum { WARPS_N = WARPS_N_ }; | |
| enum { COLS = HIDDEN_SIZE_ }; | |
| enum { HIDDEN_SIZE = HIDDEN_SIZE_ }; | |
| enum { BYTES_PER_LDG = BYTES_PER_LDG_ }; | |
| enum { NUM_ELTS = BYTES_PER_LDG / sizeof(input_t) }; | |
| enum { THREADS_PER_ROW = WARPS_N * THREADS_PER_WARP }; | |
| enum { THREADS_PER_CTA = WARPS_M * THREADS_PER_ROW }; | |
| enum { ROWS_PER_CTA = WARPS_M }; | |
| enum { BYTES_PER_ROW = COLS * sizeof(input_t) }; | |
| enum { BYTES_PER_ROW_PER_CTA = THREADS_PER_ROW * BYTES_PER_LDG }; | |
| // Multi-row per CTA not supported for multi-CTA => no smem for WGRAD needed | |
| enum { SMEM_BYTES_WGRAD = CTAS_PER_ROW > 1 ? 0 : ROWS_PER_CTA * COLS * sizeof(compute_t) }; | |
| static_assert(WARPS_M == 1 || CTAS_PER_ROW == 1); | |
| using reduce_t = typename layer_norm::TypeToVec2<compute_t>::Type; | |
| using Reducer = layer_norm::Reducer<reduce_t, CTAS_PER_ROW, WARPS_M, WARPS_N>; | |
| enum { SMEM_BYTES_DGRAD = Reducer::SMEM_BYTES }; | |
| enum { SMEM_BYTES = SMEM_BYTES_DGRAD + SMEM_BYTES_WGRAD }; | |
| using Ivec = layer_norm::Vec<input_t, NUM_ELTS>; | |
| using Rvec = layer_norm::Vec<residual_t, NUM_ELTS>; | |
| using Ovec = layer_norm::Vec<output_t, NUM_ELTS>; | |
| using Wvec = layer_norm::Vec<weight_t, NUM_ELTS>; | |
| using Cvec = layer_norm::Vec<compute_t, NUM_ELTS>; | |
| using Mvec = layer_norm::Vec<mask_t, NUM_ELTS>; | |
| enum { ELTS_PER_LDG = BYTES_PER_LDG / sizeof(input_t) }; | |
| // Assume that each thread can handle the same number of elements in the output and weights as in the input. | |
| static_assert(sizeof(input_t) == sizeof(output_t)); | |
| static_assert(sizeof(input_t) <= sizeof(residual_t)); | |
| // The number of columns fetched per load from input: one per thread. | |
| enum { VEC_COLS_PER_LDG = CTAS_PER_ROW * THREADS_PER_ROW }; | |
| // The total number of vectorized loads/stores per hidden vector. | |
| enum { VEC_COLS = COLS / ELTS_PER_LDG }; | |
| // The number of loads per thread for the input. | |
| enum { LDGS = VEC_COLS / VEC_COLS_PER_LDG }; | |
| static_assert(LDGS * VEC_COLS_PER_LDG == VEC_COLS); | |
| //static_assert(LDGS * BYTES_PER_ROW_PER_CTA * CTAS_PER_ROW == BYTES_PER_ROW, ""); | |
| using Stats = layer_norm::Stats<compute_t, CTAS_PER_ROW, WARPS_M, WARPS_N>; | |
| enum { SMEM_BYTES_FWD = Stats::SMEM_BYTES }; | |
| }; | |
| //////////////////////////////////////////////////////////////////////////////////////////////////// | |
| } // namespace layer_norm | |