Files
llama.cpp/ggml/src/ggml-sycl/cpy.hpp
Akarshan Biswas cd1fce6d4f SYCL: Add set_rows support for quantized types (#14883)
* SYCL: Add set_rows support for quantized types

This commit adds support for GGML_OP_SET_ROWS operation for various
quantized tensor types (Q8_0, Q5_1, Q5_0, Q4_1, Q4_0, IQ4_NL) and BF16
type in the SYCL backend.

The quantization/dequantization copy kernels were moved from cpy.cpp
to cpy.hpp to make them available for set_rows.cpp.

This addresses part of the TODOs mentioned in the code.

* Use get_global_linear_id() instead

ggml-ci

* Fix formatting

ggml-ci

* Use const for ne11 and size_t variables in set_rows_sycl_q

ggml-ci

* Increase block size for q kernel to 256

ggml-ci

* Cleanup imports

* Add float.h to cpy.hpp
2025-07-28 20:32:15 +05:30

224 lines
6.1 KiB
C++

#ifndef GGML_SYCL_CPY_HPP
#define GGML_SYCL_CPY_HPP
#include "common.hpp"
#include <float.h>
typedef void (*cpy_kernel_t)(const char * cx, char * cdst);
__dpct_inline__ int best_index_int8(int n, const int8_t * val, float x) {
if (x <= val[0]) {
return 0;
}
if (x >= val[n - 1]) {
return n - 1;
}
int ml = 0, mu = n - 1;
while (mu - ml > 1) {
int mav = (ml + mu) / 2;
if (x < val[mav]) {
mu = mav;
} else {
ml = mav;
}
}
return x - val[mu - 1] < val[mu] - x ? mu - 1 : mu;
}
inline void cpy_blck_f32_q8_0(const char * cxi, char * cdsti) {
const float * xi = (const float *) cxi;
block_q8_0 * dsti = (block_q8_0 *) cdsti;
float amax = 0.0f; // absolute max
for (int j = 0; j < QK8_0; j++) {
const float v = xi[j];
amax = sycl::fmax(amax, sycl::fabs((float) v));
}
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f / d : 0.0f;
dsti->d = d;
for (int j = 0; j < QK8_0; ++j) {
const float x0 = xi[j] * id;
dsti->qs[j] = sycl::round((float) x0);
}
}
inline void cpy_blck_f32_q4_0(const char * cxi, char * cdsti) {
const float * xi = (const float *) cxi;
block_q4_0 * dsti = (block_q4_0 *) cdsti;
float amax = 0.0f;
float vmax = 0.0f;
for (int j = 0; j < QK4_0; ++j) {
const float v = xi[j];
if (amax < sycl::fabs((float) v)) {
amax = sycl::fabs((float) v);
vmax = v;
}
}
const float d = vmax / -8;
const float id = d ? 1.0f / d : 0.0f;
dsti->d = d;
for (int j = 0; j < QK4_0 / 2; ++j) {
const float x0 = xi[0 + j] * id;
const float x1 = xi[QK4_0 / 2 + j] * id;
const uint8_t xi0 = dpct::min(15, (int8_t) (x0 + 8.5f));
const uint8_t xi1 = dpct::min(15, (int8_t) (x1 + 8.5f));
dsti->qs[j] = xi0;
dsti->qs[j] |= xi1 << 4;
}
}
inline void cpy_blck_f32_q4_1(const char * cxi, char * cdsti) {
const float * xi = (const float *) cxi;
block_q4_1 * dsti = (block_q4_1 *) cdsti;
float vmin = FLT_MAX;
float vmax = -FLT_MAX;
for (int j = 0; j < QK4_1; ++j) {
const float v = xi[j];
vmin = sycl::min(v, vmin);
vmax = sycl::max(v, vmax);
}
const float d = (vmax - vmin) / ((1 << 4) - 1);
const float id = d ? 1.0f / d : 0.0f;
dsti->dm.x() = d;
dsti->dm.y() = vmin;
for (int j = 0; j < QK4_1 / 2; ++j) {
const float x0 = (xi[0 + j] - vmin) * id;
const float x1 = (xi[QK4_1 / 2 + j] - vmin) * id;
const uint8_t xi0 = dpct::min(15, (int8_t) (x0 + 0.5f));
const uint8_t xi1 = dpct::min(15, (int8_t) (x1 + 0.5f));
dsti->qs[j] = xi0;
dsti->qs[j] |= xi1 << 4;
}
}
inline void cpy_blck_f32_q5_0(const char * cxi, char * cdsti) {
const float * xi = (const float *) cxi;
block_q5_0 * dsti = (block_q5_0 *) cdsti;
float amax = 0.0f;
float vmax = 0.0f;
for (int j = 0; j < QK5_0; ++j) {
const float v = xi[j];
if (amax < sycl::fabs((float) v)) {
amax = sycl::fabs((float) v);
vmax = v;
}
}
const float d = vmax / -16;
const float id = d ? 1.0f / d : 0.0f;
dsti->d = d;
uint32_t qh = 0;
for (int j = 0; j < QK5_0 / 2; ++j) {
const float x0 = xi[0 + j] * id;
const float x1 = xi[QK5_0 / 2 + j] * id;
const uint8_t xi0 = dpct::min(31, (int8_t) (x0 + 16.5f));
const uint8_t xi1 = dpct::min(31, (int8_t) (x1 + 16.5f));
dsti->qs[j] = (xi0 & 0xf) | ((xi1 & 0xf) << 4);
qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_0 / 2);
}
memcpy(dsti->qh, &qh, sizeof(qh));
}
inline void cpy_blck_f32_q5_1(const char * cxi, char * cdsti) {
const float * xi = (const float *) cxi;
block_q5_1 * dsti = (block_q5_1 *) cdsti;
float min = xi[0];
float max = xi[0];
for (int j = 1; j < QK5_1; ++j) {
const float v = xi[j];
min = v < min ? v : min;
max = v > max ? v : max;
}
const float d = (max - min) / 31;
const float id = d ? 1.0f / d : 0.0f;
dsti->dm.x() = d;
dsti->dm.y() = min;
uint32_t qh = 0;
for (int j = 0; j < QK5_1 / 2; ++j) {
const float x0 = (xi[0 + j] - min) * id;
const float x1 = (xi[QK5_1 / 2 + j] - min) * id;
const uint8_t xi0 = (uint8_t) (x0 + 0.5f);
const uint8_t xi1 = (uint8_t) (x1 + 0.5f);
dsti->qs[j] = (xi0 & 0xf) | ((xi1 & 0xf) << 4);
qh |= ((xi0 & 0x10u) >> 4) << (j + 0);
qh |= ((xi1 & 0x10u) >> 4) << (j + QK5_1 / 2);
}
memcpy(dsti->qh, &qh, sizeof(qh));
}
inline void cpy_blck_f32_iq4_nl(const char * cxi, char * cdsti) {
const float * xi = (const float *) cxi;
block_iq4_nl * dsti = (block_iq4_nl *) cdsti;
float amax = 0.0f;
float vmax = 0.0f;
for (int j = 0; j < QK4_NL; ++j) {
const float v = xi[j];
if (amax < sycl::fabs((float) v)) {
amax = sycl::fabs((float) v);
vmax = v;
}
}
float d = vmax / kvalues_iq4nl[0];
const float id = d ? 1.0f / d : 0.0f;
float sumqx = 0, sumq2 = 0;
for (int j = 0; j < QK4_NL / 2; ++j) {
const float x0 = xi[0 + j] * id;
const float x1 = xi[QK4_NL / 2 + j] * id;
const uint8_t xi0 = best_index_int8(16, kvalues_iq4nl, x0);
const uint8_t xi1 = best_index_int8(16, kvalues_iq4nl, x1);
dsti->qs[j] = xi0 | (xi1 << 4);
const float v0 = kvalues_iq4nl[xi0];
const float v1 = kvalues_iq4nl[xi1];
const float w0 = xi[0 + j] * xi[0 + j];
const float w1 = xi[QK4_NL / 2 + j] * xi[QK4_NL / 2 + j];
sumqx += w0 * v0 * xi[j] + w1 * v1 * xi[QK4_NL / 2 + j];
sumq2 += w0 * v0 * v0 + w1 * v1 * v1;
}
dsti->d = sumq2 > 0 ? sumqx / sumq2 : d;
}
void ggml_sycl_cpy(ggml_backend_sycl_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1);
void ggml_sycl_dup(ggml_backend_sycl_context & ctx, ggml_tensor * dst);
#endif // GGML_SYCL_CPY_HPP