mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2026-09-11 15:29:03 +02:00
ggml-cpu(s390x): add Q1_0 vector intrinsic support (#28606)
* ggml-cpu: add `ggml_vec_dot_q1_0_q8_0` support Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * ggml-cpu: clean up variable naming for understanding Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> * docs: update support for Q1_0 Signed-off-by: Aaron Teo <aaron.teo1@ibm.com> --------- Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
This commit is contained in:
+2
-1
@@ -243,6 +243,7 @@ IBM VXE/VXE2 SIMD acceleration depends on the BLAS implementation. It is strongl
|
||||
| FP32 | ✅ | ✅ | ❓ |
|
||||
| FP16 | ✅ | ✅ | ❓ |
|
||||
| BF16 | ✅ | ✅ | ❓ |
|
||||
| Q1_0 | ✅ | ❓ | ❓ |
|
||||
| Q4_0 | ✅ | ❓ | ❓ |
|
||||
| Q4_1 | ✅ | ❓ | ❓ |
|
||||
| MXFP4 | ✅ | ❓ | ❓ |
|
||||
@@ -272,4 +273,4 @@ IBM VXE/VXE2 SIMD acceleration depends on the BLAS implementation. It is strongl
|
||||
- 🚫 - acceleration unavailable, will still run using scalar implementation
|
||||
- ❓ - acceleration unknown, please contribute if you can test it yourself
|
||||
|
||||
Last Updated by **Aaron Teo (aaron.teo1@ibm.com)** on Feb 15, 2026.
|
||||
Last Updated by **Aaron Teo (aaron.teo1@ibm.com)** on Sep 8, 2026.
|
||||
|
||||
@@ -247,7 +247,6 @@
|
||||
// quants.c
|
||||
#define quantize_row_q8_K_generic quantize_row_q8_K
|
||||
#define ggml_vec_dot_nvfp4_q8_0_generic ggml_vec_dot_nvfp4_q8_0
|
||||
#define ggml_vec_dot_q1_0_q8_0_generic ggml_vec_dot_q1_0_q8_0
|
||||
#define ggml_vec_dot_q2_0_q8_0_generic ggml_vec_dot_q2_0_q8_0
|
||||
#define ggml_vec_dot_tq1_0_q8_K_generic ggml_vec_dot_tq1_0_q8_K
|
||||
#define ggml_vec_dot_tq2_0_q8_K_generic ggml_vec_dot_tq2_0_q8_K
|
||||
|
||||
@@ -146,6 +146,74 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
|
||||
|
||||
//===================================== Dot products =================================
|
||||
|
||||
void ggml_vec_dot_q1_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
|
||||
const int qk = QK1_0; // 128
|
||||
const int nb = n / qk;
|
||||
|
||||
assert(n % qk == 0);
|
||||
assert(nrc == 1);
|
||||
UNUSED(nrc);
|
||||
UNUSED(bx);
|
||||
UNUSED(by);
|
||||
UNUSED(bs);
|
||||
|
||||
const block_q1_0 * GGML_RESTRICT x = vx;
|
||||
const block_q8_0 * GGML_RESTRICT y = vy;
|
||||
|
||||
#if defined(__VXE__) || defined(__VXE2__)
|
||||
float32x4_t v_sumf = vec_splats(0.0f);
|
||||
|
||||
const uint8x16_t v_zero = vec_splats((uint8_t)0x00); // zero
|
||||
const uint8x16_t v_bias = vec_splats((uint8_t)0x80); // bias from signed to unsigned
|
||||
// v ^ 0x80 == v + 128
|
||||
|
||||
const uint8x16_t v_idx = (const uint8x16_t){ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1 };
|
||||
const uint8x16_t v_bit = (const uint8x16_t){ 1, 2, 4, 8, 16, 32, 64, 128, 1, 2, 4, 8, 16, 32, 64, 128 };
|
||||
|
||||
for (int i = 0; i < nb; ++i) {
|
||||
const uint8x16_t v_x = vec_xl(0, (const uint8_t *)x[i].qs);
|
||||
const float32x4_t v_xd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
|
||||
|
||||
for (int k = 0; k < 4; ++k) {
|
||||
// sub-block k holds elements 32k .. 32k+31
|
||||
const block_q8_0 * GGML_RESTRICT yb = &y[i*4 + k];
|
||||
const float32x4_t v_yd = vec_splats(GGML_CPU_FP16_TO_FP32(yb->d));
|
||||
|
||||
const uint8x16_t v_xrl = vec_perm(v_x, v_x, vec_add(v_idx, vec_splats((uint8_t)(k*4 + 0))));
|
||||
const uint8x16_t v_xrh = vec_perm(v_x, v_x, vec_add(v_idx, vec_splats((uint8_t)(k*4 + 2))));
|
||||
|
||||
// isolate each lane's bit, then set all ones where that bit is clear, the -d case
|
||||
const int8x16_t v_ml = (int8x16_t)vec_cmpeq(vec_and(v_xrl, v_bit), v_zero);
|
||||
const int8x16_t v_mh = (int8x16_t)vec_cmpeq(vec_and(v_xrh, v_bit), v_zero);
|
||||
|
||||
const int8x16_t v_yl = vec_xl(0, (const int8_t *)yb->qs);
|
||||
const int8x16_t v_yh = vec_xl(QK8_0/2, (const int8_t *)yb->qs);
|
||||
|
||||
// weights are only +1 or -1, so negate y
|
||||
const int8x16_t v_ysl = vec_sub(vec_xor(v_yl, v_ml), v_ml);
|
||||
const int8x16_t v_ysh = vec_sub(vec_xor(v_yh, v_mh), v_mh);
|
||||
|
||||
// bias to unsigned, then vec_sum4 adds each group of 4 bytes into one word
|
||||
const uint32x4_t v_p = vec_add(vec_sum4(vec_xor((uint8x16_t)v_ysl, v_bias), v_zero),
|
||||
vec_sum4(vec_xor((uint8x16_t)v_ysh, v_bias), v_zero));
|
||||
|
||||
// each word summed 8 biased bytes, so take back 8 * 128
|
||||
const int32x4_t v_xy = vec_sub((int32x4_t)v_p, vec_splats((int32_t)1024));
|
||||
|
||||
// apply both block scales and add into the running total
|
||||
v_sumf = vec_madd(vec_float(v_xy), vec_mul(v_xd, v_yd), v_sumf);
|
||||
}
|
||||
}
|
||||
|
||||
*s = vec_hsum_f32x4(v_sumf);
|
||||
#else
|
||||
UNUSED(nb);
|
||||
UNUSED(x);
|
||||
UNUSED(y);
|
||||
ggml_vec_dot_q1_0_q8_0_generic(n, s, bs, vx, bx, vy, by, nrc);
|
||||
#endif
|
||||
}
|
||||
|
||||
void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
|
||||
const int qk = QK8_0;
|
||||
const int nb = n / qk;
|
||||
|
||||
Reference in New Issue
Block a user