// Adated from FasterTransformer, https://github.com/NVIDIA/FasterTransformer/blob/release/v5.3_tag/src/fastertransformer/kernels/decoder_masked_multihead_attention/decoder_masked_multihead_attention_template.hpp #pragma once #include #include #include #include #include #ifdef ENABLE_BF16 #include #endif template struct num_elems; template <> struct num_elems { static constexpr int value = 1; }; template <> struct num_elems { static constexpr int value = 2; }; template <> struct num_elems { static constexpr int value = 4; }; template <> struct num_elems { static constexpr int value = 1; }; template <> struct num_elems { static constexpr int value = 2; }; #ifdef ENABLE_BF16 template <> struct num_elems<__nv_bfloat16> { static constexpr int value = 1; }; template <> struct num_elems<__nv_bfloat162> { static constexpr int value = 2; }; #endif #ifdef ENABLE_FP8 template <> struct num_elems<__nv_fp8_e4m3> { static constexpr int value = 1; }; template <> struct num_elems<__nv_fp8x2_e4m3> { static constexpr int value = 2; }; #endif template struct packed_as; template struct packed_as { using type = T; }; template<> struct packed_as { using type = half2; }; template<> struct packed_as { using type = float2; }; template<> struct packed_as { using type = int16_t; }; template<> struct packed_as { using type = int2; }; template<> struct packed_as { using type = half; }; template<> struct packed_as { using type = float; }; #ifdef ENABLE_BF16 template<> struct packed_as<__nv_bfloat16, 2> { using type = __nv_bfloat162; }; template<> struct packed_as<__nv_bfloat162, 1> { using type = __nv_bfloat16; }; #endif #ifdef ENABLE_FP8 template<> struct packed_as<__nv_fp8_e4m3, 2> { using type = __nv_fp8x2_e4m3; }; template<> struct packed_as<__nv_fp8x2_e4m3, 1> { using type = __nv_fp8_e4m3; }; template<> struct packed_as<__nv_fp8_e5m2, 2> { using type = __nv_fp8x2_e5m2; }; template<> struct packed_as<__nv_fp8x2_e5m2, 1> { using type = __nv_fp8_e5m2; }; #endif inline __device__ float2 operator*(float2 a, float2 b) { return make_float2(a.x * b.x, a.y * b.y); } inline __device__ float2 operator+(float2 a, float2 b) { return make_float2(a.x + b.x, a.y + b.y); } inline __device__ float2 operator-(float2 a, float2 b) { return make_float2(a.x - b.x, a.y - b.y); } inline __device__ float2 operator*(float2 a, float b) { return make_float2(a.x * b, a.y * b); } inline __device__ float2 operator+(float2 a, float b) { return make_float2(a.x + b, a.y + b); } inline __device__ float2 operator-(float2 a, float b) { return make_float2(a.x - b, a.y - b); } static inline __device__ int8_t float_to_int8_rn(float x) { uint32_t dst; asm volatile("cvt.rni.sat.s8.f32 %0, %1;" : "=r"(dst) : "f"(x)); return reinterpret_cast(dst); } template inline __device__ T ldg(const T* val) { return __ldg(val); } #if ENABLE_BF16 #define bf1622float2 __bfloat1622float2 #define float22bf162 __float22bfloat162_rn #define bf162bf162 __bfloat162bfloat162 inline __device__ int16_t bf1622int16(__nv_bfloat162 val) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ < 800 float2 f_val; f_val.x = max(min(__low2float(val), 127.f), -128.f); f_val.y = max(min(__high2float(val), 127.f), -128.f); union { int8_t int8[2]; int16_t int16; }; int8[0] = static_cast(static_cast(f_val.x)); int8[1] = static_cast(static_cast(f_val.y)); return int16; #else val = __hmin2(val, make_bfloat162(127., 127.)); val = __hmax2(val, make_bfloat162(-128., -128.)); union { int8_t int8[2]; int16_t int16; }; int8[0] = static_cast(static_cast(val.x)); int8[1] = static_cast(static_cast(val.y)); return int16; #endif } #endif #if ENABLE_BF16 template<> inline __device__ __nv_bfloat162 ldg(const __nv_bfloat162* val) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ < 800 return val[0]; #else return __ldg(val); #endif } template<> inline __device__ __nv_bfloat16 ldg(const __nv_bfloat16* val) { #if defined(__CUDA_ARCH__) && __CUDA_ARCH__ < 800 return val[0]; #else return __ldg(val); #endif } #endif // ENABLE_BF16 template __device__ inline T_OUT cuda_cast(T_IN val) { return val; } template <> __device__ inline float2 cuda_cast(int2 val) { return make_float2(val.x, val.y); } template <> __device__ inline float2 cuda_cast(float val) { return make_float2(val, val); } template <> __device__ inline float2 cuda_cast(half2 val) { return __half22float2(val); } template <> __device__ inline half2 cuda_cast(float2 val) { return __float22half2_rn(val); } template <> __device__ inline half2 cuda_cast(float val) { return __float2half2_rn(val); } template <> __device__ inline half2 cuda_cast(half val) { return __half2half2(val); } template <> __device__ inline int8_t cuda_cast(half val) { union { int8_t int8[2]; int16_t int16; }; union { half fp16; int16_t int16_in; }; fp16 = val; asm volatile("cvt.rni.sat.s8.f16 %0, %1;" : "=h"(int16) : "h"(int16_in)); return int8[0]; } template <> __device__ inline int16_t cuda_cast(half2 val) { union { int8_t int8[2]; int16_t int16; }; int8[0] = cuda_cast(val.x); int8[1] = cuda_cast(val.y); return int16; } template <> __device__ inline int8_t cuda_cast(float val) { union { int8_t int8[2]; int16_t int16; }; asm volatile("cvt.rni.sat.s8.f32 %0, %1;" : "=h"(int16) : "f"(val)); return int8[0]; } template <> __device__ inline int16_t cuda_cast(float2 val) { union { int8_t int8[2]; int16_t int16; }; int8[0] = cuda_cast(val.x); int8[1] = cuda_cast(val.y); return int16; } template <> __device__ inline half2 cuda_cast(int16_t val) { union { int8_t int8[2]; int16_t int16; }; int16 = val; return make_half2(int8[0], int8[1]); } template <> __device__ inline float2 cuda_cast(int16_t val) { union { int8_t int8[2]; int16_t int16; }; int16 = val; return make_float2(int8[0], int8[1]); } #ifdef ENABLE_BF16 template <> __device__ inline __nv_bfloat16 cuda_cast(int32_t val) { return static_cast(val); } template <> __device__ inline __nv_bfloat16 cuda_cast(int8_t val) { return static_cast(val); } template <> __device__ inline int8_t cuda_cast(__nv_bfloat16 val) { return static_cast(val); } template <> __device__ inline float cuda_cast(__nv_bfloat16 val) { return __bfloat162float(val); } template <> __device__ inline float2 cuda_cast(__nv_bfloat162 val) { return bf1622float2(val); } template <> __device__ inline half cuda_cast(__nv_bfloat16 val) { return __float2half(__bfloat162float(val)); } template <> __device__ inline int16_t cuda_cast(__nv_bfloat162 val) { return bf1622int16(val); } template <> __device__ inline __nv_bfloat16 cuda_cast<__nv_bfloat16, float>(float val) { return __float2bfloat16(val); } template <> __device__ inline __nv_bfloat16 cuda_cast<__nv_bfloat16, half>(half val) { return __float2bfloat16(__half2float(val)); } template <> __device__ inline __nv_bfloat162 cuda_cast<__nv_bfloat162, __nv_bfloat16>(__nv_bfloat16 val) { return bf162bf162(val); } template <> __device__ inline __nv_bfloat162 cuda_cast<__nv_bfloat162, float>(float val) { return __float2bfloat162_rn(val); } template <> __device__ inline __nv_bfloat162 cuda_cast<__nv_bfloat162, float2>(float2 val) { return float22bf162(val); } template <> __device__ inline __nv_bfloat162 cuda_cast<__nv_bfloat162, int16_t>(int16_t val) { union { int8_t int8[2]; int16_t int16; }; int16 = val; __nv_bfloat162 res; res.x = cuda_cast<__nv_bfloat16>(int8[0]); res.y = cuda_cast<__nv_bfloat16>(int8[1]); return res; } template <> __device__ inline __nv_bfloat162 cuda_cast<__nv_bfloat162, half2>(half2 val) { return float22bf162(__half22float2(val)); } #endif // ENABLE BF16 template __device__ inline To cuda_sum(Ti val) { return cuda_cast(val); }; template __device__ inline To cuda_sum(float2 val) { return cuda_cast(val.x + val.y); }; // Unary maximum: compute the max of a vector type template __device__ inline To cuda_max(Ti val) { return cuda_cast(val); }; template <> __device__ inline float cuda_max(float2 val) { return fmaxf(val.x, val.y); } template <> __device__ inline half cuda_max(half2 val) { return __hmax(val.x, val.y); } #ifdef ENABLE_BF16 template <> __device__ inline __nv_bfloat16 cuda_max(__nv_bfloat162 val) { #if (defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 800)) return __hmax(val.x, val.y); #endif } #endif // Binary maximum: compute the max of two scalar types template __device__ inline T cuda_max(T val1, T val2) { return (val1 > val2) ? val1 : val2; } template __device__ inline T cuda_abs(T val) { assert(false); return {}; } template <> __device__ inline float cuda_abs(float val) { return fabs(val); } template <> __device__ inline float2 cuda_abs(float2 val) { return make_float2(fabs(val.x), fabs(val.y)); } template <> __device__ inline half cuda_abs(half val) { return __habs(val); } template <> __device__ inline half2 cuda_abs(half2 val) { return __habs2(val); } #ifdef ENABLE_BF16 #if __CUDA_ARCH__ >= 800 || !defined(__CUDA_ARCH__) template <> __device__ inline __nv_bfloat16 cuda_abs(__nv_bfloat16 val) { return __habs(val); } template <> __device__ inline __nv_bfloat162 cuda_abs(__nv_bfloat162 val) { return __habs2(val); } #endif #endif // ENABLE_FP16