vllm/csrc/quantization/w8a8/cutlass/scaled_mm_entry.cu
Wentao Ye 241b4cfe66
[Refactor] Refactor FP8 & INT8 Quant Folder inside w8a8 (#25293)
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#include <cudaTypedefs.h>
#include <c10/cuda/CUDAGuard.h>
#include <torch/all.h>
#include "cutlass_extensions/common.hpp"
void cutlass_scaled_mm_sm75(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
std::optional<torch::Tensor> const& bias);
void cutlass_scaled_mm_sm80(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
std::optional<torch::Tensor> const& bias);
void cutlass_scaled_mm_sm89(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
std::optional<torch::Tensor> const& bias);
#if defined ENABLE_SCALED_MM_SM90 && ENABLE_SCALED_MM_SM90
void cutlass_scaled_mm_sm90(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
std::optional<torch::Tensor> const& bias);
#endif
#if defined ENABLE_CUTLASS_MOE_SM90 && ENABLE_CUTLASS_MOE_SM90
void cutlass_moe_mm_sm90(
torch::Tensor& out_tensors, torch::Tensor const& a_tensors,
torch::Tensor const& b_tensors, torch::Tensor const& a_scales,
torch::Tensor const& b_scales, torch::Tensor const& expert_offsets,
torch::Tensor const& problem_sizes, torch::Tensor const& a_strides,
torch::Tensor const& b_strides, torch::Tensor const& c_strides,
bool per_act_token, bool per_out_ch);
#endif
#if defined ENABLE_CUTLASS_MOE_SM100 && ENABLE_CUTLASS_MOE_SM100
void cutlass_moe_mm_sm100(
torch::Tensor& out_tensors, torch::Tensor const& a_tensors,
torch::Tensor const& b_tensors, torch::Tensor const& a_scales,
torch::Tensor const& b_scales, torch::Tensor const& expert_offsets,
torch::Tensor const& problem_sizes, torch::Tensor const& a_strides,
torch::Tensor const& b_strides, torch::Tensor const& c_strides,
bool per_act_token, bool per_out_ch);
#endif
#if defined ENABLE_SCALED_MM_SM120 && ENABLE_SCALED_MM_SM120
void cutlass_scaled_mm_sm120(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
std::optional<torch::Tensor> const& bias);
#endif
#if defined ENABLE_SCALED_MM_SM100 && ENABLE_SCALED_MM_SM100
void cutlass_scaled_mm_sm100(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
std::optional<torch::Tensor> const& bias);
#endif
#if defined(ENABLE_SCALED_MM_SM90) && ENABLE_SCALED_MM_SM90 || \
defined(ENABLE_SCALED_MM_SM100) && ENABLE_SCALED_MM_SM100 || \
defined(ENABLE_SCALED_MM_SM120) && ENABLE_SCALED_MM_SM120
void get_cutlass_moe_mm_data_caller(
const torch::Tensor& topk_ids, torch::Tensor& expert_offsets,
torch::Tensor& problem_sizes1, torch::Tensor& problem_sizes2,
torch::Tensor& input_permutation, torch::Tensor& output_permutation,
const int64_t num_experts, const int64_t n, const int64_t k,
const std::optional<torch::Tensor>& blockscale_offsets);
void get_cutlass_moe_mm_problem_sizes_caller(
const torch::Tensor& topk_ids, torch::Tensor& problem_sizes1,
torch::Tensor& problem_sizes2, const int64_t num_experts, const int64_t n,
const int64_t k, const std::optional<torch::Tensor>& blockscale_offsets);
void get_cutlass_pplx_moe_mm_data_caller(torch::Tensor& expert_offsets,
torch::Tensor& problem_sizes1,
torch::Tensor& problem_sizes2,
const torch::Tensor& expert_num_tokens,
const int64_t num_local_experts,
const int64_t padded_m,
const int64_t n, const int64_t k);
#endif
void cutlass_scaled_mm_azp_sm75(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
torch::Tensor const& azp_adj,
std::optional<torch::Tensor> const& azp,
std::optional<torch::Tensor> const& bias);
void cutlass_scaled_mm_azp_sm80(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
torch::Tensor const& azp_adj,
std::optional<torch::Tensor> const& azp,
std::optional<torch::Tensor> const& bias);
void cutlass_scaled_mm_azp_sm89(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
torch::Tensor const& azp_adj,
std::optional<torch::Tensor> const& azp,
std::optional<torch::Tensor> const& bias);
#if defined ENABLE_SCALED_MM_SM90 && ENABLE_SCALED_MM_SM90
void cutlass_scaled_mm_azp_sm90(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
torch::Tensor const& azp_adj,
std::optional<torch::Tensor> const& azp,
std::optional<torch::Tensor> const& bias);
#endif
bool cutlass_scaled_mm_supports_fp8(int64_t cuda_device_capability) {
// CUTLASS FP8 kernels need at least
// CUDA 12.0 on SM90 systems (Hopper)
// CUDA 12.4 on SM89 systems (Lovelace)
#if defined CUDA_VERSION
if (cuda_device_capability >= 90) {
return CUDA_VERSION >= 12000;
} else if (cuda_device_capability >= 89) {
return CUDA_VERSION >= 12040;
}
#endif
return false;
}
bool cutlass_scaled_mm_supports_block_fp8(int64_t cuda_device_capability) {
// CUTLASS block-quantized FP8 kernels need at least CUDA 12.0
// and at least SM90 (Hopper)
#if defined CUDA_VERSION
if (cuda_device_capability >= 100) {
return CUDA_VERSION >= 12080;
} else if (cuda_device_capability >= 90) {
return CUDA_VERSION >= 12000;
}
#endif
return false;
}
bool cutlass_group_gemm_supported(int64_t cuda_device_capability) {
// CUTLASS grouped FP8 kernels need at least CUDA 12.3 and SM90 (Hopper)
// or CUDA 12.8 and SM100 (Blackwell)
#if defined CUDA_VERSION
if (cuda_device_capability >= 100) {
return CUDA_VERSION >= 12080;
}
if (cuda_device_capability >= 90) {
return CUDA_VERSION >= 12030;
}
#endif
return false;
}
void cutlass_scaled_mm(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b, torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
std::optional<torch::Tensor> const& bias) {
// Checks for conformality
TORCH_CHECK(a.dim() == 2 && b.dim() == 2 && c.dim() == 2);
TORCH_CHECK(c.size(0) == a.size(0) && a.size(1) == b.size(0) &&
b.size(1) == c.size(1));
// Check for strides and alignment
TORCH_CHECK(a.stride(1) == 1 && c.stride(1) == 1); // Row-major
TORCH_CHECK(b.stride(0) == 1); // Column-major
TORCH_CHECK(c.stride(0) % 16 == 0 &&
b.stride(1) % 16 == 0); // 16 Byte Alignment
if (bias) {
TORCH_CHECK(bias->numel() == b.size(1) && bias->is_contiguous() &&
bias->dim() == 1);
}
at::cuda::OptionalCUDAGuard const device_guard(device_of(a));
int32_t version_num = get_sm_version_num();
#if defined ENABLE_SCALED_MM_SM120 && ENABLE_SCALED_MM_SM120
if (version_num >= 120) {
cutlass_scaled_mm_sm120(c, a, b, a_scales, b_scales, bias);
return;
}
#endif
#if defined ENABLE_SCALED_MM_SM100 && ENABLE_SCALED_MM_SM100
if (version_num >= 100 && version_num < 120) {
cutlass_scaled_mm_sm100(c, a, b, a_scales, b_scales, bias);
return;
}
#endif
// Guard against compilation issues for sm90 kernels
#if defined ENABLE_SCALED_MM_SM90 && ENABLE_SCALED_MM_SM90
if (version_num >= 90 && version_num < 100) {
// Hopper
cutlass_scaled_mm_sm90(c, a, b, a_scales, b_scales, bias);
return;
}
#endif
#if defined ENABLE_SCALED_MM_C2X && ENABLE_SCALED_MM_C2X
if (version_num == 89) {
// Ada Lovelace
cutlass_scaled_mm_sm89(c, a, b, a_scales, b_scales, bias);
return;
}
if (version_num >= 80) {
// Ampere
cutlass_scaled_mm_sm80(c, a, b, a_scales, b_scales, bias);
return;
}
if (version_num >= 75) {
// Turing
cutlass_scaled_mm_sm75(c, a, b, a_scales, b_scales, bias);
return;
}
#endif
TORCH_CHECK_NOT_IMPLEMENTED(
false,
"No compiled cutlass_scaled_mm for a compute capability less than "
"CUDA device capability: ",
version_num);
}
void cutlass_moe_mm(
torch::Tensor& out_tensors, torch::Tensor const& a_tensors,
torch::Tensor const& b_tensors, torch::Tensor const& a_scales,
torch::Tensor const& b_scales, torch::Tensor const& expert_offsets,
torch::Tensor const& problem_sizes, torch::Tensor const& a_strides,
torch::Tensor const& b_strides, torch::Tensor const& c_strides,
bool per_act_token, bool per_out_ch) {
int32_t version_num = get_sm_version_num();
#if defined ENABLE_CUTLASS_MOE_SM100 && ENABLE_CUTLASS_MOE_SM100
if (version_num >= 100 && version_num < 110) {
cutlass_moe_mm_sm100(out_tensors, a_tensors, b_tensors, a_scales, b_scales,
expert_offsets, problem_sizes, a_strides, b_strides,
c_strides, per_act_token, per_out_ch);
return;
}
#endif
#if defined ENABLE_CUTLASS_MOE_SM90 && ENABLE_CUTLASS_MOE_SM90
if (version_num >= 90 && version_num < 100) {
cutlass_moe_mm_sm90(out_tensors, a_tensors, b_tensors, a_scales, b_scales,
expert_offsets, problem_sizes, a_strides, b_strides,
c_strides, per_act_token, per_out_ch);
return;
}
#endif
TORCH_CHECK_NOT_IMPLEMENTED(
false,
"No compiled cutlass_scaled_mm for CUDA device capability: ", version_num,
". Required capability: 90 or 100");
}
void get_cutlass_moe_mm_data(
const torch::Tensor& topk_ids, torch::Tensor& expert_offsets,
torch::Tensor& problem_sizes1, torch::Tensor& problem_sizes2,
torch::Tensor& input_permutation, torch::Tensor& output_permutation,
const int64_t num_experts, const int64_t n, const int64_t k,
const std::optional<torch::Tensor>& blockscale_offsets) {
// This function currently gets compiled only if we have a valid cutlass moe
// mm to run it for.
int32_t version_num = get_sm_version_num();
#if (defined ENABLE_CUTLASS_MOE_SM90 && ENABLE_CUTLASS_MOE_SM90) || \
(defined ENABLE_CUTLASS_MOE_SM100 && ENABLE_CUTLASS_MOE_SM100)
get_cutlass_moe_mm_data_caller(topk_ids, expert_offsets, problem_sizes1,
problem_sizes2, input_permutation,
output_permutation, num_experts, n, k,
blockscale_offsets);
return;
#endif
TORCH_CHECK_NOT_IMPLEMENTED(
false,
"No compiled get_cutlass_moe_mm_data: no cutlass_scaled_mm kernel for "
"CUDA device capability: ",
version_num, ". Required capability: 90 or 100");
}
void get_cutlass_moe_mm_problem_sizes(
const torch::Tensor& topk_ids, torch::Tensor& problem_sizes1,
torch::Tensor& problem_sizes2, const int64_t num_experts, const int64_t n,
const int64_t k, const std::optional<torch::Tensor>& blockscale_offsets) {
int32_t version_num = get_sm_version_num();
#if (defined ENABLE_CUTLASS_MOE_SM90 && ENABLE_CUTLASS_MOE_SM90) || \
(defined ENABLE_CUTLASS_MOE_SM100 && ENABLE_CUTLASS_MOE_SM100)
get_cutlass_moe_mm_problem_sizes_caller(topk_ids, problem_sizes1,
problem_sizes2, num_experts, n, k,
blockscale_offsets);
return;
#endif
TORCH_CHECK_NOT_IMPLEMENTED(
false,
"No compiled get_cutlass_moe_mm_problem_sizes: no cutlass_scaled_mm "
"kernel for CUDA device capability: ",
version_num, ". Required capability: 90 or 100");
}
void get_cutlass_pplx_moe_mm_data(torch::Tensor& expert_offsets,
torch::Tensor& problem_sizes1,
torch::Tensor& problem_sizes2,
const torch::Tensor& expert_num_tokens,
const int64_t num_local_experts,
const int64_t padded_m, const int64_t n,
const int64_t k) {
// This function currently gets compiled only if we have a valid cutlass moe
// mm to run it for.
int32_t version_num = get_sm_version_num();
#if (defined ENABLE_CUTLASS_MOE_SM90 && ENABLE_CUTLASS_MOE_SM90) || \
(defined ENABLE_CUTLASS_MOE_SM100 && ENABLE_CUTLASS_MOE_SM100)
get_cutlass_pplx_moe_mm_data_caller(expert_offsets, problem_sizes1,
problem_sizes2, expert_num_tokens,
num_local_experts, padded_m, n, k);
return;
#endif
TORCH_CHECK_NOT_IMPLEMENTED(
false,
"No compiled get_cutlass_pplx_moe_mm_data: no cutlass_scaled_mm kernel "
"for CUDA device capability: ",
version_num, ". Required capability: 90 or 100");
}
void cutlass_scaled_mm_azp(torch::Tensor& c, torch::Tensor const& a,
torch::Tensor const& b,
torch::Tensor const& a_scales,
torch::Tensor const& b_scales,
torch::Tensor const& azp_adj,
std::optional<torch::Tensor> const& azp,
std::optional<torch::Tensor> const& bias) {
// Checks for conformality
TORCH_CHECK(a.dim() == 2 && b.dim() == 2 && c.dim() == 2);
TORCH_CHECK(c.size(0) == a.size(0) && a.size(1) == b.size(0) &&
b.size(1) == c.size(1));
TORCH_CHECK(a_scales.numel() == 1 || a_scales.numel() == a.size(0));
TORCH_CHECK(b_scales.numel() == 1 || b_scales.numel() == b.size(1));
// Check for strides and alignment
TORCH_CHECK(a.stride(1) == 1 && c.stride(1) == 1); // Row-major
TORCH_CHECK(b.stride(0) == 1); // Column-major
TORCH_CHECK(c.stride(0) % 16 == 0 &&
b.stride(1) % 16 == 0); // 16 Byte Alignment
TORCH_CHECK(a_scales.is_contiguous() && b_scales.is_contiguous());
// bias, azp, azp_adj are all 1d
// bias and azp_adj have n elements, azp has m elements
if (bias) {
TORCH_CHECK(bias->numel() == b.size(1) && bias->is_contiguous());
}
if (azp) {
TORCH_CHECK(azp->numel() == a.size(0) && azp->is_contiguous());
}
TORCH_CHECK(azp_adj.numel() == b.size(1) && azp_adj.is_contiguous());
// azp & bias types
TORCH_CHECK(azp_adj.dtype() == torch::kInt32);
TORCH_CHECK(!azp || azp->dtype() == torch::kInt32);
TORCH_CHECK(!bias || bias->dtype() == c.dtype(),
"currently bias dtype must match output dtype ", c.dtype());
at::cuda::OptionalCUDAGuard const device_guard(device_of(a));
int32_t version_num = get_sm_version_num();
#if defined ENABLE_SCALED_MM_SM90 && ENABLE_SCALED_MM_SM90
if (version_num >= 90) {
cutlass_scaled_mm_azp_sm90(c, a, b, a_scales, b_scales, azp_adj, azp, bias);
return;
}
#endif
#if defined ENABLE_SCALED_MM_C2X && ENABLE_SCALED_MM_C2X
if (version_num == 89) {
// Ada Lovelace
cutlass_scaled_mm_azp_sm89(c, a, b, a_scales, b_scales, azp_adj, azp, bias);
return;
}
if (version_num >= 80) {
// Ampere
cutlass_scaled_mm_azp_sm80(c, a, b, a_scales, b_scales, azp_adj, azp, bias);
return;
}
// Turing
TORCH_CHECK(version_num >= 75);
cutlass_scaled_mm_azp_sm75(c, a, b, a_scales, b_scales, azp_adj, azp, bias);
return;
#endif
TORCH_CHECK_NOT_IMPLEMENTED(
false,
"No compiled cutlass_scaled_mm_azp for a compute capability less than "
"CUDA device capability: ",
version_num);
}