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Revert "supports dynamic Cfp8" #3988

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4 changes: 2 additions & 2 deletions custom_ops/gpu_ops/append_attention.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -140,8 +140,8 @@ void AppendAttentionKernel(
key_cache,
value_cache,
attn_mask,
cache_quant_type_str == "block_wise_fp8" ? cache_k_quant_scales : cache_k_dequant_scales,
cache_quant_type_str == "block_wise_fp8" ? cache_v_quant_scales : cache_v_dequant_scales,
cache_k_dequant_scales,
cache_v_dequant_scales,
cache_k_zp,
cache_v_zp,
out_linear_shifts,
Expand Down
302 changes: 102 additions & 200 deletions custom_ops/gpu_ops/append_attn/append_attention_c8_impl.cuh
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199 changes: 28 additions & 171 deletions custom_ops/gpu_ops/append_attn/append_attention_func.cuh
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Original file line number Diff line number Diff line change
Expand Up @@ -384,113 +384,6 @@ __device__ __forceinline__ void produce_v_blockwise_c8(
}
}

template<uint32_t block_size,
uint32_t num_frags_z,
uint32_t NUM_WARP_Q,
typename T>
__device__ __forceinline__ void produce_k_dynamic_scale(
T* k_smem_scale,
T* cache_k_reg,
const int* block_table_now,
const T* cache_k_scale,
const uint32_t kv_idx,
const uint32_t kv_num_heads,
const uint32_t kv_head_idx,
const uint32_t chunk_end
) {
const uint32_t tx = threadIdx.x, ty = threadIdx.y;
if constexpr (NUM_WARP_Q == 4) {
// 4 warps shared block_size
const uint32_t tid = ty * 32 + tx;
int block_id = __ldg(&block_table_now[kv_idx / block_size]);
if (block_id < 0) block_id = 0;
const T* cache_k_scale_now = cache_k_scale + block_id * kv_num_heads * block_size + kv_head_idx * block_size;
if (tid < block_size) {
k_smem_scale[tid] = cache_k_scale_now[tid];
}
__syncthreads();
const uint32_t row_id = tx / 4;
for (uint32_t fz = 0; fz < num_frags_z; fz++) {
cache_k_reg[fz * 2] = k_smem_scale[fz * 16 + row_id];
cache_k_reg[fz * 2 + 1] = k_smem_scale[fz * 16 + row_id + 8];
}
} else {
// 1 warp 32 tokens
const uint32_t kv_idx_now = kv_idx + block_size * ty / 2;
int block_id = __ldg(&block_table_now[kv_idx_now / block_size]);
if (block_id < 0) block_id = 0;
const T* cache_k_scale_now = cache_k_scale + block_id * kv_num_heads * block_size + kv_head_idx * block_size;
const int kv_idx_this_thread = kv_idx + ty * 32 + tx;
if (kv_idx_this_thread < chunk_end) {
k_smem_scale[ty * 32 + tx] = cache_k_scale_now[(ty % 2) * 32 + tx];
} else {
k_smem_scale[ty * 32 + tx] = 0;
}
__syncwarp();
const uint32_t row_id = tx / 4;
for (uint32_t fz = 0; fz < num_frags_z; fz++) {
cache_k_reg[fz * 2] = k_smem_scale[ty * 32 + fz * 16 + row_id];
cache_k_reg[fz * 2 + 1] = k_smem_scale[ty * 32 + fz * 16 + row_id + 8];
}
}
}

template<uint32_t block_size,
uint32_t num_frags_z,
uint32_t NUM_WARP_Q,
typename T>
__device__ __forceinline__ void produce_v_dynamic_scale(
T* v_smem_scale,
T* cache_v_reg,
const int* block_table_now,
const T* cache_v_scale,
const uint32_t kv_idx,
const uint32_t kv_num_heads,
const uint32_t kv_head_idx,
const uint32_t chunk_end
) {
const uint32_t tx = threadIdx.x, ty = threadIdx.y;

if constexpr (NUM_WARP_Q == 4) {
// 4 warps shared block_size
const uint32_t tid = ty * 32 + tx;
int block_id = __ldg(&block_table_now[kv_idx / block_size]);
if (block_id < 0) block_id = 0;
const T* cache_v_scale_now = cache_v_scale + block_id * kv_num_heads * block_size + kv_head_idx * block_size;
if (tid < block_size) {
v_smem_scale[tid] = cache_v_scale_now[tid];
}
__syncthreads();
const uint32_t row_id = tx % 4 * 2;
for (uint32_t fz = 0; fz < num_frags_z; fz++) {
cache_v_reg[fz * 4] = v_smem_scale[fz * 16 + row_id];
cache_v_reg[fz * 4 + 1] = v_smem_scale[fz * 16 + row_id + 1];
cache_v_reg[fz * 4 + 2] = v_smem_scale[fz * 16 + row_id + 8];
cache_v_reg[fz * 4 + 3] = v_smem_scale[fz * 16 + row_id + 9];
}
} else {
// 1 warp 32 tokens
const uint32_t kv_idx_now = kv_idx + block_size * ty / 2;
int block_id = __ldg(&block_table_now[kv_idx_now / block_size]);
if (block_id < 0) block_id = 0;
const T* cache_v_scale_now = cache_v_scale + block_id * kv_num_heads * block_size + kv_head_idx * block_size;
const int kv_idx_this_thread = kv_idx + ty * 32 + tx;
if (kv_idx_this_thread < chunk_end) {
v_smem_scale[ty * 32 + tx] = cache_v_scale_now[(ty % 2) * 32 + tx];
} else {
v_smem_scale[ty * 32 + tx] = 0;
}
__syncwarp();
const uint32_t row_id = tx % 4 * 2;
for (uint32_t fz = 0; fz < num_frags_z; fz++) {
cache_v_reg[fz * 4] = v_smem_scale[ty * 32 + fz * 16 + row_id];
cache_v_reg[fz * 4 + 1] = v_smem_scale[ty * 32 + fz * 16 + row_id + 1];
cache_v_reg[fz * 4 + 2] = v_smem_scale[ty * 32 + fz * 16 + row_id + 8];
cache_v_reg[fz * 4 + 3] = v_smem_scale[ty * 32 + fz * 16 + row_id + 9];
}
}
}

template <SharedMemFillMode fill_mode,
uint32_t num_warps,
uint32_t block_size,
Expand Down Expand Up @@ -923,8 +816,7 @@ template <uint32_t num_frags_x,
typename T,
typename CacheT,
bool is_scale_channel_wise = false,
bool IsFP8 = false,
bool IsDynamicC8 = false>
bool IsFP8=false>
__device__ __forceinline__ void compute_qk_c8(smem_t* q_smem,
uint32_t* q_smem_offset_r,
smem_t* k_smem,
Expand Down Expand Up @@ -968,27 +860,20 @@ __device__ __forceinline__ void compute_qk_c8(smem_t* q_smem,
convert_c8<T,IsFP8>(b_frag_dq_T, b_frag[fy * 2]);
convert_c8<T,IsFP8>(b_frag_dq_T + 4, b_frag[fy * 2 + 1]);
// scale zp
if constexpr (!IsDynamicC8) {
if constexpr (is_scale_channel_wise) {
const int scale_col = (ky * 2 + fy) * 4;
b_frag_dq_T[0] *= cache_k_scale[scale_col];
b_frag_dq_T[1] *= cache_k_scale[scale_col + 1];
b_frag_dq_T[2] *= cache_k_scale[scale_col + 2];
b_frag_dq_T[3] *= cache_k_scale[scale_col + 3];
b_frag_dq_T[4] *= cache_k_scale[scale_col];
b_frag_dq_T[5] *= cache_k_scale[scale_col + 1];
b_frag_dq_T[6] *= cache_k_scale[scale_col + 2];
b_frag_dq_T[7] *= cache_k_scale[scale_col + 3];
} else {
#pragma unroll
for (uint32_t b_i = 0; b_i < 8; ++b_i) {
b_frag_dq_T[b_i] *= cache_k_scale[0];
}
}
if constexpr (is_scale_channel_wise) {
const int scale_col = (ky * 2 + fy) * 4;
b_frag_dq_T[0] *= cache_k_scale[scale_col];
b_frag_dq_T[1] *= cache_k_scale[scale_col + 1];
b_frag_dq_T[2] *= cache_k_scale[scale_col + 2];
b_frag_dq_T[3] *= cache_k_scale[scale_col + 3];
b_frag_dq_T[4] *= cache_k_scale[scale_col];
b_frag_dq_T[5] *= cache_k_scale[scale_col + 1];
b_frag_dq_T[6] *= cache_k_scale[scale_col + 2];
b_frag_dq_T[7] *= cache_k_scale[scale_col + 3];
} else {
#pragma unroll
for (uint32_t b_i = 0; b_i < 8; ++b_i) {
b_frag_dq_T[b_i] *= cache_k_scale[fz * 2 + b_i / 4];
b_frag_dq_T[b_i] *= cache_k_scale[0];
}
}
#pragma unroll
Expand Down Expand Up @@ -1208,9 +1093,7 @@ template <uint32_t num_frags_x,
uint32_t block_size,
typename T,
typename CacheT,
bool is_scale_channel_wise = false,
bool IsFP8 = false,
bool IsDynamicC8 = false>
bool is_scale_channel_wise = false, bool IsFP8=false>
__device__ __forceinline__ void compute_sfm_v_c8(
smem_t* v_smem,
uint32_t* v_smem_offset_r,
Expand Down Expand Up @@ -1252,28 +1135,16 @@ __device__ __forceinline__ void compute_sfm_v_c8(
convert_c8<T,IsFP8>(b_frag_dq_T, b_frag[fz * 2]);
convert_c8<T,IsFP8>(b_frag_dq_T + 4, b_frag[fz * 2 + 1]);
// scale zp
if constexpr (!IsDynamicC8) {
if constexpr (is_scale_channel_wise) {
#pragma unroll
for (uint32_t b_i = 0; b_i < 8; ++b_i) {
b_frag_dq_T[b_i] *= cache_v_scale[b_i / 4 + fy * 2];
}
} else {
if constexpr (is_scale_channel_wise) {
#pragma unroll
for (uint32_t b_i = 0; b_i < 8; ++b_i) {
b_frag_dq_T[b_i] *= cache_v_scale[0];
}
for (uint32_t b_i = 0; b_i < 8; ++b_i) {
b_frag_dq_T[b_i] *= cache_v_scale[b_i / 4 + fy * 2];
}
} else {
const int scale_col = (kz * 2 + fz) * 4;
b_frag_dq_T[0] *= cache_v_scale[scale_col];
b_frag_dq_T[1] *= cache_v_scale[scale_col + 1];
b_frag_dq_T[2] *= cache_v_scale[scale_col + 2];
b_frag_dq_T[3] *= cache_v_scale[scale_col + 3];
b_frag_dq_T[4] *= cache_v_scale[scale_col];
b_frag_dq_T[5] *= cache_v_scale[scale_col + 1];
b_frag_dq_T[6] *= cache_v_scale[scale_col + 2];
b_frag_dq_T[7] *= cache_v_scale[scale_col + 3];
#pragma unroll
for (uint32_t b_i = 0; b_i < 8; ++b_i) {
b_frag_dq_T[b_i] *= cache_v_scale[0];
}
}
#pragma unroll
for (uint32_t fx = 0; fx < num_frags_x; ++fx) { // m: num_frags_x * 16
Expand All @@ -1300,9 +1171,7 @@ template <uint32_t num_frags_x,
uint32_t block_size,
typename T,
typename CacheT,
bool is_scale_channel_wise = false,
bool IsFP8 = false,
bool IsDynamicC8 = false>
bool is_scale_channel_wise = false, bool IsFP8=false>
__device__ __forceinline__ void compute_sfm_v_c8_iter_sq_bvec(
smem_t* v_smem,
uint32_t* v_smem_offset_r,
Expand Down Expand Up @@ -1346,28 +1215,16 @@ __device__ __forceinline__ void compute_sfm_v_c8_iter_sq_bvec(
convert_c8<T,IsFP8>(b_frag_dq_T, b_frag[fz * 2]);
convert_c8<T,IsFP8>(b_frag_dq_T + 4, b_frag[fz * 2 + 1]);
// scale zp
if constexpr (!IsDynamicC8) {
if constexpr (is_scale_channel_wise) {
if constexpr (is_scale_channel_wise) {
#pragma unroll
for (uint32_t b_i = 0; b_i < 8; ++b_i) {
b_frag_dq_T[b_i] *= cache_v_scale[b_i / 4 + fy * 2];
}
} else {
#pragma unroll
for (uint32_t b_i = 0; b_i < 8; ++b_i) {
b_frag_dq_T[b_i] *= cache_v_scale[0];
}
for (uint32_t b_i = 0; b_i < 8; ++b_i) {
b_frag_dq_T[b_i] *= cache_v_scale[b_i / 4 + fy * 2];
}
} else {
const int scale_col = (kz * 2 + fz) * 4;
b_frag_dq_T[0] *= cache_v_scale[scale_col];
b_frag_dq_T[1] *= cache_v_scale[scale_col + 1];
b_frag_dq_T[2] *= cache_v_scale[scale_col + 2];
b_frag_dq_T[3] *= cache_v_scale[scale_col + 3];
b_frag_dq_T[4] *= cache_v_scale[scale_col];
b_frag_dq_T[5] *= cache_v_scale[scale_col + 1];
b_frag_dq_T[6] *= cache_v_scale[scale_col + 2];
b_frag_dq_T[7] *= cache_v_scale[scale_col + 3];
#pragma unroll
for (uint32_t b_i = 0; b_i < 8; ++b_i) {
b_frag_dq_T[b_i] *= cache_v_scale[0];
}
}
#pragma unroll
for (uint32_t fx = 0; fx < num_frags_x; ++fx) { // m: num_frags_x * 16
Expand Down
5 changes: 1 addition & 4 deletions custom_ops/gpu_ops/append_attn/append_attention_kernel.h
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Expand Up @@ -103,7 +103,6 @@ void CascadeAppendAttentionC8Kernel(
const bool causal,
const bool is_decoder,
const bool enable_prefill,
const std::string& cache_quant_type_str,
cudaStream_t& stream,
paddle::Tensor* out);

Expand Down Expand Up @@ -265,10 +264,9 @@ void CascadeAppendAttentionKernel(
causal,
is_decoder,
enable_prefill,
cache_quant_type_str,
stream,
out);
} else if (cache_quant_type_str == "cache_fp8" or cache_quant_type_str == "block_wise_fp8") {
} else if (cache_quant_type_str == "cache_fp8") {
CascadeAppendAttentionC8Kernel<T, OutT, true>(meta_data,
qkv,
cache_k,
Expand Down Expand Up @@ -301,7 +299,6 @@ void CascadeAppendAttentionKernel(
causal,
is_decoder,
enable_prefill,
cache_quant_type_str,
stream,
out);
} else if (cache_quant_type_str == "cache_int4_zp") {
Expand Down
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