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sycl: quantize and reorder the input to q8_1 when reorder is enabled (llama/13826)

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* [WIP]: fuse q8 quantization and reorder

* wip2: fuse q8 quantization and reorder

* working q8 reorder commit

* restored common.hpp

* remove debug prints

* remove unnecessary headers and remove trailing whitespace

* Update ggml/src/ggml-sycl/ggml-sycl.cpp

Co-authored-by: Alberto Cabrera Pérez <alberto.cabrera@intel.com>

---------

Co-authored-by: Alberto Cabrera Pérez <alberto.cabrera@intel.com>
This commit is contained in:
Atharva Dubey
2025-06-02 10:12:20 +01:00
committed by Georgi Gerganov
parent 9589645e72
commit ef2a79d2b8
3 changed files with 120 additions and 28 deletions
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79
ggml/src/ggml-sycl/ggml-sycl.cpp
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@ -1434,6 +1434,59 @@ static void quantize_q8_1(const float * __restrict__ x, void * __restrict__ vy,
reinterpret_cast<sycl::half &>(y[ib].ds.y()) = sum;
}
template <int ElementsPerWI>
static __dpct_inline__ void quantize_and_reorder_q8_1(const float * __restrict__ x, void * reordered_q8_tensor,
const int kx, const int kx_padded, const sycl::nd_item<1> & it) {
/*
Quantizes and reorders the resultant q8 tensor in a per row fashion
Each sub-group calculates one quant block. i.e. QK8_1 quant values and the d and sum values
*/
auto subgroup_id = it.get_group(0);
auto wi_id = it.get_local_id(0);
const int num_blocks_per_row = kx / QK8_1;
auto row = subgroup_id / num_blocks_per_row;
auto col = subgroup_id % num_blocks_per_row;
auto row_offset = row * (kx_padded / QK8_1) * sizeof(block_q8_1);
auto col_offset = QK8_1 * col + wi_id * ElementsPerWI;
auto quant_ptr = (int8_t *) ((char *) reordered_q8_tensor + row_offset + col_offset);
auto ds_ptr = (sycl::half2 *) ((char *) reordered_q8_tensor + row_offset + kx + col * sizeof(sycl::half2));
sycl::vec<float, ElementsPerWI> wi_f32_vals;
sycl::vec<int8_t, ElementsPerWI> quantized_values;
auto float_ptr_offset = subgroup_id * QK8_1 + ElementsPerWI * wi_id;
wi_f32_vals = *reinterpret_cast<const sycl::vec<float, ElementsPerWI> *>(x + float_ptr_offset);
float sum = 0.0f;
float amax = 0.0f;
#pragma unroll(ElementsPerWI)
for (int i = 0; i < ElementsPerWI; i++) {
sum += wi_f32_vals[i];
amax = sycl::fmax(amax, sycl::fabs(wi_f32_vals[i]));
quantized_values[i] = 0;
}
sum = sycl::reduce_over_group(it.get_group(), sum, sycl::plus<float>());
amax = sycl::reduce_over_group(it.get_group(), amax, sycl::maximum<float>());
float d = amax == 0 ? 1 : amax / 127;
#pragma unroll(ElementsPerWI)
for (int i = 0; i < ElementsPerWI; i++) {
quantized_values[i] = sycl::round(wi_f32_vals[i] / d);
}
d = amax == 0 ? 0 : d;
*reinterpret_cast<sycl::vec<int8_t, ElementsPerWI> *>(quant_ptr) = quantized_values;
if (wi_id == 0) {
*ds_ptr = sycl::half2(sycl::half(d), sycl::half(sum));
}
}
static void mul_mat_p021_f16_f32(
const void * __restrict__ vx, const float * __restrict__ y, float * __restrict__ dst,
const int ncols_x, const int nrows_x, const int nchannels_x, const int nchannels_y,
@ -1718,25 +1771,32 @@ static void pool2d_nchw_kernel(
o_ptr[cur_oh * ow + cur_ow] = res;
}
static void quantize_row_q8_1_sycl(const float *x, void *vy, const int kx,
const int ky, const int kx_padded,
queue_ptr stream) {
static void quantize_row_q8_1_sycl(const float * x, void * vy, const int kx, const int ky, const int kx_padded,
bool reorder_q8_tensor, queue_ptr stream) {
if (reorder_q8_tensor) {
auto local_range = std::size_t(WARP_SIZE);
auto num_quant_blocks = ky * (kx / QK8_1);
auto global_range = num_quant_blocks * local_range;
stream->parallel_for(sycl::nd_range<1>({ global_range }, { local_range }),
[=](sycl::nd_item<1> it) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
quantize_and_reorder_q8_1<QK8_1 / WARP_SIZE>(x, vy, kx, kx_padded, it);
});
} else {
const int block_num_x = (kx_padded + SYCL_QUANTIZE_BLOCK_SIZE - 1) / SYCL_QUANTIZE_BLOCK_SIZE;
const sycl::range<3> num_blocks(1, ky, block_num_x);
int constexpr QUANT_BLOCK_TILE = QK8_1 / WARP_SIZE;
static_assert(QK8_1 % WARP_SIZE == 0);
const sycl::range<3> block_size(1, 1, SYCL_QUANTIZE_BLOCK_SIZE / QUANT_BLOCK_TILE);
{
dpct::has_capability_or_fail(stream->get_device(),
{sycl::aspect::fp16});
dpct::has_capability_or_fail(stream->get_device(), { sycl::aspect::fp16 });
stream->parallel_for(
sycl::nd_range<3>(num_blocks * block_size, block_size),
stream->parallel_for(sycl::nd_range<3>(num_blocks * block_size, block_size),
[=](sycl::nd_item<3> item_ct1) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
quantize_q8_1<QUANT_BLOCK_TILE>(x, vy, kx, kx_padded, item_ct1);
});
}
}
}
static void ggml_mul_mat_p021_f16_f32_sycl(const void *vx, const float *y,
float *dst, const int ncols_x,
@ -2446,9 +2506,10 @@ static void ggml_sycl_op_mul_mat(ggml_backend_sycl_context & ctx, const ggml_ten
dev[i].src1_ddq = dev[i].src1_ddq_alloc.alloc(ctx.pool(i), nrows1*src1_padded_col_size*q8_1_ts/q8_1_bs);
if (src1_on_device && src1_is_contiguous) {
bool reorder_q8_tensor = src0->extra && ((ggml_tensor_extra_gpu *)src0->extra)->optimized_feature.reorder;
scope_op_debug_print scope_dbg_print(__func__, "/quantize_row_q8_1_sycl", dst,
/*num_src=*/2, " : converting src1 to Q8_1");
quantize_row_q8_1_sycl(dev[i].src1_ddf, dev[i].src1_ddq, ne10, nrows1, src1_padded_col_size, stream);
quantize_row_q8_1_sycl(dev[i].src1_ddf, dev[i].src1_ddq, ne10, nrows1, src1_padded_col_size, reorder_q8_tensor, stream);
/*
DPCT1010:90: SYCL uses exceptions to report errors and does not
use the error codes. The call was replaced with 0. You need to
@ -2554,7 +2615,7 @@ static void ggml_sycl_op_mul_mat(ggml_backend_sycl_context & ctx, const ggml_ten
if (convert_src1_to_q8_1 && !src1_is_contiguous) {
scope_op_debug_print scope_dbg_print(__func__, "/quantize_row_q8_1_sycl", dst,
/*num_src=*/2, " : converting src1 to Q8_1");
quantize_row_q8_1_sycl(src1_ddf_i, src1_ddq_i, ne10, src1_ncols, src1_padded_col_size, stream);
quantize_row_q8_1_sycl(src1_ddf_i, src1_ddq_i, ne10, src1_ncols, src1_padded_col_size, false, stream);
/*
DPCT1010:92: SYCL uses exceptions to report errors and does
not use the error codes. The call was replaced with 0. You

6
ggml/src/ggml-sycl/mmvq.cpp
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@ -29,8 +29,6 @@ static void mul_mat_vec_q_reorder(const void * __restrict__ vx, const void * __r
static_assert(blocks_per_subgroup > 0);
static_assert(block_elements_per_subgroup > 0);
const block_q8_1 * y = (const block_q8_1 *) vy;
float partial_sum = 0.0f;
for (int i = sg.get_local_linear_id() / block_elements_per_subgroup; i < blocks_per_row; i += blocks_per_subgroup) {
const int ibx = row * blocks_per_row + i; // x block index
@ -40,13 +38,15 @@ static void mul_mat_vec_q_reorder(const void * __restrict__ vx, const void * __r
// Y block index that aligns with ibx
const int iby = i * block_type::block_to_q8_1_ratio();
const int8_t* q8_1_quant_ptr = (const int8_t*)vy + iby * QK8_1;
const sycl::half2* q8_1_ds_ptr = (const sycl::half2*)((const char*)vy + ncols + iby * sizeof(sycl::half2));
#pragma unroll
for (int elem = 0; elem < block_elements_per_subgroup; elem += WARP_SIZE) {
// x block quant index when casting the quants to int
const int iqs = elem + block_traits::vdr_mmvq * (sg.get_local_linear_id() % block_elements_per_subgroup);
partial_sum += reorder_vec_dot_q_sycl()(vx, bx_offset, d_offset, &y[iby], iqs, nblocks);
partial_sum += reorder_vec_dot_q_sycl()(vx, bx_offset, d_offset, q8_1_quant_ptr, q8_1_ds_ptr, iqs, nblocks);
}
}

45
ggml/src/ggml-sycl/vecdotq.hpp
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@ -285,21 +285,21 @@ template <> struct reorder_vec_dot_q_sycl<GGML_TYPE_Q4_0> {
}
__dpct_inline__ float operator()(const void * __restrict__ vbq, const int ibx_offset, const int d_offset,
const block_q8_1 * __restrict__ bq8_1, const int & iqs, int /* nblocks */) {
const int8_t* q8_1_quant_ptr, const sycl::half2* q8_1_ds, const int & iqs, int /* nblocks */) {
const uint8_t * bq4_0 = static_cast<const uint8_t *>(vbq) + ibx_offset;
const ggml_half d = *(reinterpret_cast<const ggml_half *>(static_cast<const uint8_t *>(vbq) + d_offset));
int v[q4_0_traits::vdr_mmvq];
int u[2 * q4_0_traits::vdr_mmvq];
#pragma unroll
#pragma unroll
for (size_t i = 0; i < q4_0_traits::vdr_mmvq; ++i) {
v[i] = get_int_from_uint8(bq4_0, iqs + i);
u[2 * i + 0] = get_int_from_int8_aligned(bq8_1->qs, iqs + i);
u[2 * i + 1] = get_int_from_int8_aligned(bq8_1->qs, iqs + i + q4_0_traits::qi);
u[2 * i + 0] = get_int_from_int8_aligned(q8_1_quant_ptr, iqs + i);
u[2 * i + 1] = get_int_from_int8_aligned(q8_1_quant_ptr, iqs + i + q4_0_traits::qi);
}
return vec_dot_q4_0_q8_1_impl(v, u, d, bq8_1->ds);
return vec_dot_q4_0_q8_1_impl(v, u, d, *q8_1_ds);
};
};
@ -347,7 +347,7 @@ template <> struct reorder_vec_dot_q_sycl<GGML_TYPE_Q4_K> {
using q4_k_traits = typename q4_k_block::traits;
float operator()(const void * __restrict__ vbq, const int ibx_offset, const int d_offset,
const block_q8_1 * __restrict__ bq8_1, const int & iqs, int nblocks) {
const int8_t* q8_1_quant_ptr, const sycl::half2* q8_1_ds, const int & iqs, int nblocks) {
const int ib = ibx_offset / (QK_K / 2);
const uint8_t * base = static_cast<const uint8_t *>(vbq);
@ -360,7 +360,38 @@ template <> struct reorder_vec_dot_q_sycl<GGML_TYPE_Q4_K> {
const int * q4 = (const int *) (qs + 16 * bq8_offset + 4 * ((iqs / 2) % 4));
const uint16_t * scales = (const uint16_t *) scs;
return vec_dot_q4_K_q8_1_common(q4, scales, *dms, bq8_1, iqs);
int v[2];
int u[2 * QR4_K];
float d8[QR4_K];
v[0] = q4[0];
v[1] = q4[4];
uint16_t aux[2];
const int j = (QR4_K * ((iqs / 2) / (QI8_1 / 2))) / 2;
if (j < 2) {
aux[0] = scales[j + 0] & 0x3f3f;
aux[1] = scales[j + 2] & 0x3f3f;
} else {
aux[0] = ((scales[j + 2] >> 0) & 0x0f0f) | ((scales[j - 2] & 0xc0c0) >> 2);
aux[1] = ((scales[j + 2] >> 4) & 0x0f0f) | ((scales[j - 0] & 0xc0c0) >> 2);
}
const uint8_t * sc = (const uint8_t *) aux;
const uint8_t * m = sc + 2;
for (int i = 0; i < QR4_K; ++i) {
const int8_t* quant_base_ptr = q8_1_quant_ptr + (bq8_offset + i) * QK8_1;
sycl::half2 ds_values = *(q8_1_ds + bq8_offset + i);
d8[i] = ds_values[0];
const int * q8 = (const int *) quant_base_ptr + ((iqs / 2) % 4);
u[2 * i + 0] = q8[0];
u[2 * i + 1] = q8[4];
}
return vec_dot_q4_K_q8_1_impl_vmmq(v, u, sc, m, *dms, d8);
}
};