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llama.cpp
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pass cdna compile

This commit is contained in:
zhang hui 2026-01-15 16:07:15 +08:00
parent be5ec5a6f0
commit a31225cc03
3 changed files with 72 additions and 8 deletions
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58
ggml/src/ggml-cuda/mma.cuh
View File

@ -339,6 +339,32 @@ namespace ggml_cuda_mma {
return -1;
}
}
#elif defined(AMD_MFMA_AVAILABLE)
static constexpr int ne = I * J / 64;
half2 x[ne] = {{0.0f, 0.0f}};
static constexpr __device__ bool supported() {
if (I == 16 && J == 8) return true;
return false;
}
static __device__ __forceinline__ int get_i(const int l) {
if constexpr (I == 16 && J == 8) {
return threadIdx.x % 16;
} else {
NO_DEVICE_CODE;
return -1;
}
}
static __device__ __forceinline__ int get_j(const int l) {
if constexpr (I == 16 && J == 8) {
return 2 * (threadIdx.x / 16) + l;
} else {
NO_DEVICE_CODE;
return -1;
}
}
#else
static constexpr int ne = I * J / WARP_SIZE;
half2 x[ne] = {{0.0f, 0.0f}};
@ -391,7 +417,22 @@ namespace ggml_cuda_mma {
static constexpr data_layout dl = DATA_LAYOUT_I_MAJOR;
#if defined(AMD_WMMA_AVAILABLE)
static constexpr int ne = I * J / 32;
static constexpr int ne = tile<I_, J_, half2, DATA_LAYOUT_I_MAJOR>::ne;
nv_bfloat162 x[ne] = {{0.0f, 0.0f}};
static constexpr __device__ bool supported() {
return tile<I_, J_, half2, DATA_LAYOUT_I_MAJOR>::supported();
}
static __device__ __forceinline__ int get_i(const int l) {
return tile<I_, J_, half2, DATA_LAYOUT_I_MAJOR>::get_i(l);
}
static __device__ __forceinline__ int get_j(const int l) {
return tile<I_, J_, half2, DATA_LAYOUT_I_MAJOR>::get_j(l);
}
#elif defined(AMD_MFMA_AVAILABLE)
static constexpr int ne = tile<I_, J_, half2, DATA_LAYOUT_I_MAJOR>::ne;
nv_bfloat162 x[ne] = {{0.0f, 0.0f}};
static constexpr __device__ bool supported() {
@ -1090,12 +1131,25 @@ namespace ggml_cuda_mma {
NO_DEVICE_CODE;
#endif // defined(RDNA4)
#elif defined(AMD_MFMA_AVAILABLE)
using bf16x4_t = __attribute__((ext_vector_type(4))) __bf16;
using floatx4_t = __attribute__((ext_vector_type(4))) float;
floatx4_t& acc_frag = reinterpret_cast<floatx4_t&>(D.x[0]);
#if defined(CDNA3) || defined(CDNA2)
using bf16x4_t = __attribute__((ext_vector_type(4))) __bf16;
const bf16x4_t& a_frag = reinterpret_cast<const bf16x4_t&>(A.x[0]);
const bf16x4_t& b_frag = reinterpret_cast<const bf16x4_t&>(B.x[0]);
acc_frag = __builtin_amdgcn_mfma_f32_16x16x16bf16_1k(a_frag, b_frag, acc_frag, 0, 0, 0);
#elif defined(CDNA1)
#pragma unroll
for (int i = 0; i < 2; ++i) {
using bf16x2_t = __attribute__((ext_vector_type(2))) __bf16;
const bf16x2_t& a_frag = reinterpret_cast<const bf16x2_t&>(A.x[i]);
const bf16x2_t& b_frag = reinterpret_cast<const bf16x2_t&>(B.x[i]);
acc_frag = __builtin_amdgcn_mfma_f32_16x16x8bf16(a_frag, b_frag, acc_frag, 0, 0, 0);
}
#else
GGML_UNUSED_VARS(D, A, B);
NO_DEVICE_CODE;
#endif // defined(CDNA3) || defined(CDNA2)
#else
GGML_UNUSED_VARS(D, A, B);
NO_DEVICE_CODE;

4
ggml/src/ggml-cuda/mmf.cu
View File

@ -198,9 +198,9 @@ bool ggml_cuda_should_use_mmf(enum ggml_type type, int cc, int warp_size, const
case GGML_TYPE_F32:
return ampere_mma_available(cc);
case GGML_TYPE_F16:
return volta_mma_available(cc) || turing_mma_available(cc) || amd_wmma_available(cc);
return volta_mma_available(cc) || turing_mma_available(cc) || amd_wmma_available(cc) || amd_mfma_available(cc);
case GGML_TYPE_BF16:
return ampere_mma_available(cc) || amd_wmma_available(cc);
return ampere_mma_available(cc) || amd_wmma_available(cc) || amd_mfma_available(cc);
default:
return false;
}

18
ggml/src/ggml-cuda/mmf.cuh
View File

@ -30,12 +30,17 @@ static __global__ void mul_mat_f(
const int channel_ratio, const int stride_channel_x, const int stride_channel_y, const int stride_channel_dst,
const int sample_ratio, const int stride_sample_x, const int stride_sample_y, const int stride_sample_dst) {
// TODO: handle this in a consistent and simpler way after AMD MFMA support has been added
#if (!defined(GGML_USE_HIP) && !defined(GGML_USE_MUSA)) || defined(AMD_WMMA_AVAILABLE)
#if defined(VOLTA_MMA_AVAILABLE) || defined(TURING_MMA_AVAILABLE) || defined(AMD_WMMA_AVAILABLE) || defined(AMD_MFMA_AVAILABLE)
#if defined(AMD_WMMA_AVAILABLE)
if constexpr (!(std::is_same_v<T, half2> || std::is_same_v<T, nv_bfloat162>) || rows_per_block != MMF_ROWS_PER_BLOCK) {NO_DEVICE_CODE;} else {
typedef tile<16, 8, T, get_input_data_layout()> tile_A;
typedef tile<16, 8, T, get_input_data_layout()> tile_B;
typedef tile<16, 16, float, DATA_LAYOUT_J_MAJOR> tile_C;
#elif defined(AMD_MFMA_AVAILABLE)
if constexpr (!(std::is_same_v<T, half2> || std::is_same_v<T, nv_bfloat162>) || rows_per_block != MMF_ROWS_PER_BLOCK_CDNA) {NO_DEVICE_CODE;} else {
typedef tile<16, 8, T, DATA_LAYOUT_I_MAJOR> tile_A;
typedef tile<16, 8, T, DATA_LAYOUT_I_MAJOR> tile_B;
typedef tile<16, 16, float, DATA_LAYOUT_J_MAJOR> tile_C;
#else
#ifdef VOLTA_MMA_AVAILABLE
if constexpr (!std::is_same_v<T, half2> || rows_per_block != MMF_ROWS_PER_BLOCK) {NO_DEVICE_CODE;} else {
@ -261,7 +266,7 @@ static __global__ void mul_mat_f(
channel_ratio, stride_channel_x, stride_channel_y, stride_channel_dst,
sample_ratio, stride_sample_x, stride_sample_y, stride_sample_dst);
NO_DEVICE_CODE;
#endif // (!defined(GGML_USE_HIP) && !defined(GGML_USE_MUSA)) || defined(AMD_WMMA_AVAILABLE)
#endif // defined(VOLTA_MMA_AVAILABLE) || defined(TURING_MMA_AVAILABLE) || defined(AMD_WMMA_AVAILABLE) || defined(AMD_MFMA_AVAILABLE)
}
//This kernel is for larger batch sizes of mul_mat_id
@ -276,12 +281,17 @@ static __global__ void mul_mat_f_ids(
const int sample_ratio, const int stride_sample_x, const int stride_sample_y, const int stride_sample_dst,
const uint3 sis1_fd, const uint3 nch_fd) {
// TODO: handle this in a consistent and simpler way after AMD MFMA support has been added
#if (!defined(GGML_USE_HIP) && !defined(GGML_USE_MUSA)) || defined(AMD_WMMA_AVAILABLE)
#if defined(VOLTA_MMA_AVAILABLE) || defined(TURING_MMA_AVAILABLE) || defined(AMD_WMMA_AVAILABLE) || defined(AMD_MFMA_AVAILABLE)
#if defined(AMD_WMMA_AVAILABLE)
if constexpr (!(std::is_same_v<T, half2> || std::is_same_v<T, nv_bfloat162>) || rows_per_block != MMF_ROWS_PER_BLOCK) {NO_DEVICE_CODE;} else {
typedef tile<16, 8, T, get_input_data_layout()> tile_A;
typedef tile<16, 8, T, get_input_data_layout()> tile_B;
typedef tile<16, 16, float, DATA_LAYOUT_J_MAJOR> tile_C;
#elif defined(AMD_MFMA_AVAILABLE)
if constexpr (!(std::is_same_v<T, half2> || std::is_same_v<T, nv_bfloat162>) || rows_per_block != MMF_ROWS_PER_BLOCK_CDNA) {NO_DEVICE_CODE;} else {
typedef tile<16, 8, T, DATA_LAYOUT_I_MAJOR> tile_A;
typedef tile<16, 8, T, DATA_LAYOUT_I_MAJOR> tile_B;
typedef tile<16, 16, float, DATA_LAYOUT_J_MAJOR> tile_C;
#else
#ifdef VOLTA_MMA_AVAILABLE
if constexpr (!std::is_same_v<T, half2> || rows_per_block != MMF_ROWS_PER_BLOCK) {NO_DEVICE_CODE;} else {
@ -532,7 +542,7 @@ static __global__ void mul_mat_f_ids(
channel_ratio, stride_channel_x, stride_channel_y, stride_channel_dst,
sample_ratio, stride_sample_x, stride_sample_y, stride_sample_dst, sis1_fd, nch_fd);
NO_DEVICE_CODE;
#endif // (!defined(GGML_USE_HIP) && !defined(GGML_USE_MUSA)) || defined(AMD_WMMA_AVAILABLE)
#endif // defined(VOLTA_MMA_AVAILABLE) || defined(TURING_MMA_AVAILABLE) || defined(AMD_WMMA_AVAILABLE) || defined(AMD_MFMA_AVAILABLE)
}
template<typename T, int rows_per_block, int cols_per_block, int nwarps>