ggml: aarch64: Implement SVE F16 kernels for vector functions (#15115)

* Added sve implementation for vec_dot_fp16 Kernel

* removed white spaces

* Added comment

* removed white spaces

* changed GGML_F16x_VEC_FMA for code consistency

* Update vec.h

---------

Co-authored-by: vithulep <p.m.vithule1517@gmail.com>
This commit is contained in:
Prashant Vithule
2025-09-01 23:43:16 +05:30
committed by GitHub
parent 4b20d8b7e3
commit a0c2b207c5
3 changed files with 404 additions and 92 deletions

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@@ -215,6 +215,47 @@ inline static float ggml_lookup_fp16_to_fp32(ggml_fp16_t f) {
#define GGML_F32_VEC_MUL GGML_F32xt_MUL #define GGML_F32_VEC_MUL GGML_F32xt_MUL
#define GGML_F32_VEC_REDUCE GGML_F32xt_REDUCE #define GGML_F32_VEC_REDUCE GGML_F32xt_REDUCE
// F16 SVE
#define DEFAULT_PG32 svptrue_b32()
#define DEFAULT_PG16 svptrue_b16()
#define GGML_F32Cxt svfloat16_t
#define GGML_F32Cxt_ZERO svdup_n_f16(0.0f)
#define GGML_F32Cxt_SET1(x) svdup_n_f16(x)
#define GGML_F32Cxt_LOAD(p) svld1_f16(DEFAULT_PG16, (const __fp16 *)(p))
#define GGML_F32Cxt_STORE(dst_ptr, src_vec) svst1_f16(DEFAULT_PG16, (__fp16 *)(dst_ptr), (src_vec))
#define GGML_F32Cxt_FMA_IMPL(pg, a, b, c) svmad_f16_x(pg, b, c, a)
#define GGML_F32Cxt_FMA(...) GGML_F32Cxt_FMA_IMPL(DEFAULT_PG16, __VA_ARGS__)
#define GGML_F32Cxt_ADD_IMPL(pg, a, b) svadd_f16_x(pg, a, b)
#define GGML_F32Cxt_ADD(...) GGML_F32Cxt_ADD_IMPL(DEFAULT_PG16, __VA_ARGS__)
#define GGML_F32Cxt_MUL_IMPL(pg, a, b) svmul_f16_x(pg, a, b)
#define GGML_F32Cxt_MUL(...) GGML_F32Cxt_MUL_IMPL(DEFAULT_PG16, __VA_ARGS__)
#define GGML_F32Cxt_REDUCE GGML_F16xt_REDUCE_MIXED
#define GGML_F16x_VEC GGML_F32Cxt
#define GGML_F16x_VEC_ZERO GGML_F32Cxt_ZERO
#define GGML_F16x_VEC_SET1 GGML_F32Cxt_SET1
#define GGML_F16x_VEC_LOAD(p, i) GGML_F32Cxt_LOAD(p)
#define GGML_F16x_VEC_STORE(p, r, i) GGML_F32Cxt_STORE((__fp16 *)(p), r)
#define GGML_F16x_VEC_FMA GGML_F32Cxt_FMA
#define GGML_F16x_VEC_ADD GGML_F32Cxt_ADD
#define GGML_F16x_VEC_MUL GGML_F32Cxt_MUL
#define GGML_F16x_VEC_REDUCE GGML_F32Cxt_REDUCE
#define GGML_F16xt_REDUCE_ONE_IMPL(pg, a) svaddv_f16(pg, a)
#define GGML_F16xt_REDUCE_ONE(...) GGML_F16xt_REDUCE_ONE_IMPL(DEFAULT_PG16, __VA_ARGS__)
#define GGML_F16xt_REDUCE_MIXED_IMPL(pg16, res, sum1, sum2, sum3, sum4) \
{ \
sum1 = svadd_f16_x(pg16, sum1, sum2); \
sum3 = svadd_f16_x(pg16, sum3, sum4); \
sum1 = svadd_f16_x(pg16, sum1, sum3); \
__fp16 sum_f16 = svaddv_f16(pg16, sum1); \
(res) = (ggml_float) sum_f16; \
}
#define GGML_F16xt_REDUCE_MIXED(...) GGML_F16xt_REDUCE_MIXED_IMPL(DEFAULT_PG16, __VA_ARGS__)
// F16 NEON // F16 NEON
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) #if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)

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@@ -207,33 +207,97 @@ void ggml_vec_dot_f16(int n, float * GGML_RESTRICT s, size_t bs, ggml_fp16_t * G
ggml_float sumf = 0.0; ggml_float sumf = 0.0;
#if defined(GGML_SIMD) && !defined(__riscv_v_intrinsic) #if defined(GGML_SIMD) && !defined(__riscv_v_intrinsic)
const int np = (n & ~(GGML_F16_STEP - 1)); #if defined(__ARM_FEATURE_SVE)
const int sve_register_length = svcntb() * 8; //get vector length
const int ggml_f16_epr = sve_register_length / 16; // running when 16
const int ggml_f16_step = 8 * ggml_f16_epr; // choose 8 SVE registers
GGML_F16_VEC sum[GGML_F16_ARR] = { GGML_F16_VEC_ZERO }; const int np= (n & ~(ggml_f16_step - 1));
svfloat16_t sum1 = svdup_n_f16(0.0f);
svfloat16_t sum2 = svdup_n_f16(0.0f);
svfloat16_t sum3 = svdup_n_f16(0.0f);
svfloat16_t sum4 = svdup_n_f16(0.0f);
GGML_F16_VEC ax[GGML_F16_ARR]; svfloat16_t ax1, ax2, ax3, ax4, ax5, ax6, ax7, ax8;
GGML_F16_VEC ay[GGML_F16_ARR]; svfloat16_t ay1, ay2, ay3, ay4, ay5, ay6, ay7, ay8;
for (int i = 0; i < np; i += ggml_f16_step) {
ax1 = GGML_F16x_VEC_LOAD(x + i + 0 * ggml_f16_epr, 0);
ay1 = GGML_F16x_VEC_LOAD(y + i + 0 * ggml_f16_epr, 0);
sum1 = GGML_F16x_VEC_FMA(sum1, ax1, ay1);
for (int i = 0; i < np; i += GGML_F16_STEP) { ax2 = GGML_F16x_VEC_LOAD(x + i + 1 * ggml_f16_epr, 1);
for (int j = 0; j < GGML_F16_ARR; j++) { ay2 = GGML_F16x_VEC_LOAD(y + i + 1 * ggml_f16_epr, 1);
ax[j] = GGML_F16_VEC_LOAD(x + i + j*GGML_F16_EPR, j); sum2 = GGML_F16x_VEC_FMA(sum2, ax2, ay2);
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j);
sum[j] = GGML_F16_VEC_FMA(sum[j], ax[j], ay[j]); ax3 = GGML_F16x_VEC_LOAD(x + i + 2 * ggml_f16_epr, 2);
ay3 = GGML_F16x_VEC_LOAD(y + i + 2 * ggml_f16_epr, 2);
sum3 = GGML_F16x_VEC_FMA(sum3, ax3, ay3);
ax4 = GGML_F16x_VEC_LOAD(x + i + 3 * ggml_f16_epr, 3);
ay4 = GGML_F16x_VEC_LOAD(y + i + 3 * ggml_f16_epr, 3);
sum4 = GGML_F16x_VEC_FMA(sum4, ax4, ay4);
ax5 = GGML_F16x_VEC_LOAD(x + i + 4 * ggml_f16_epr, 4);
ay5 = GGML_F16x_VEC_LOAD(y + i + 4 * ggml_f16_epr, 4);
sum1 = GGML_F16x_VEC_FMA(sum1, ax5, ay5);
ax6 = GGML_F16x_VEC_LOAD(x + i + 5 * ggml_f16_epr, 5);
ay6 = GGML_F16x_VEC_LOAD(y + i + 5 * ggml_f16_epr, 5);
sum2 = GGML_F16x_VEC_FMA(sum2, ax6, ay6);
ax7 = GGML_F16x_VEC_LOAD(x + i + 6 * ggml_f16_epr, 6);
ay7 = GGML_F16x_VEC_LOAD(y + i + 6 * ggml_f16_epr, 6);
sum3 = GGML_F16x_VEC_FMA(sum3, ax7, ay7);
ax8 = GGML_F16x_VEC_LOAD(x + i + 7 * ggml_f16_epr, 7);
ay8 = GGML_F16x_VEC_LOAD(y + i + 7 * ggml_f16_epr, 7);
sum4 = GGML_F16x_VEC_FMA(sum4, ax8, ay8);
} }
}
// reduce sum0..sum3 to sum0 const int np2 = (n & ~(ggml_f16_epr - 1)); // round down to multiple of 8
GGML_F16_VEC_REDUCE(sumf, sum); for (int k = np; k < np2; k += ggml_f16_epr) {
svfloat16_t rx = GGML_F16x_VEC_LOAD(x + k, 0);
svfloat16_t ry = GGML_F16x_VEC_LOAD(y + k, 0);
sum1 = GGML_F16x_VEC_FMA(sum1, rx, ry);
}
// leftovers if (np2 < n) {
for (int i = np; i < n; ++i) { svbool_t pg = svwhilelt_b16(np2, n);
sumf += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[i])*GGML_CPU_FP16_TO_FP32(y[i])); svfloat16_t hx = svld1_f16(pg, (const __fp16 *)(x + np2));
} svfloat16_t hy = svld1_f16(pg, (const __fp16 *)(y + np2));
// if you hit this, you are likely running outside the FP range sum1 = svmad_f16_x(pg, hx, hy, sum1);
assert(!isnan(sumf) && !isinf(sumf)); }
GGML_F16x_VEC_REDUCE(sumf, sum1, sum2, sum3, sum4);
#else
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC sum[GGML_F16_ARR] = { GGML_F16_VEC_ZERO };
GGML_F16_VEC ax[GGML_F16_ARR];
GGML_F16_VEC ay[GGML_F16_ARR];
for (int i = 0; i < np; i += GGML_F16_STEP) {
for (int j = 0; j < GGML_F16_ARR; j++) {
ax[j] = GGML_F16_VEC_LOAD(x + i + j*GGML_F16_EPR, j);
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j);
sum[j] = GGML_F16_VEC_FMA(sum[j], ax[j], ay[j]);
}
}
// reduce sum0..sum3 to sum0
GGML_F16_VEC_REDUCE(sumf, sum);
// leftovers
for (int i = np; i < n; ++i) {
sumf += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[i])*GGML_CPU_FP16_TO_FP32(y[i]));
}
// if you hit this, you are likely running outside the FP range
assert(!isnan(sumf) && !isinf(sumf));
#endif
#else #else
for (int i = 0; i < n; ++i) { for (int i = 0; i < n; ++i) {
sumf += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[i])*GGML_CPU_FP16_TO_FP32(y[i])); sumf += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[i])*GGML_CPU_FP16_TO_FP32(y[i]));

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@@ -119,45 +119,149 @@ inline static void ggml_vec_dot_f16_unroll(const int n, const int xs, float * GG
} }
#if defined(GGML_SIMD) #if defined(GGML_SIMD)
#if defined(__riscv_v_intrinsic) #if defined(__ARM_FEATURE_SVE)
// todo: RVV impl
for (int i = 0; i < n; ++i) { const int sve_register_length = svcntb() * 8;
for (int j = 0; j < GGML_VEC_DOT_UNROLL; ++j) { const int ggml_f16_epr = sve_register_length / 16; // running when 16
sumf[j] += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[j][i])*GGML_CPU_FP16_TO_FP32(y[i])); const int ggml_f16_step = 8 * ggml_f16_epr; // choose 8 SVE registers
const int np = (n & ~(ggml_f16_step - 1));
svfloat16_t sum_00 = svdup_n_f16(0.0f);
svfloat16_t sum_01 = svdup_n_f16(0.0f);
svfloat16_t sum_02 = svdup_n_f16(0.0f);
svfloat16_t sum_03 = svdup_n_f16(0.0f);
svfloat16_t sum_10 = svdup_n_f16(0.0f);
svfloat16_t sum_11 = svdup_n_f16(0.0f);
svfloat16_t sum_12 = svdup_n_f16(0.0f);
svfloat16_t sum_13 = svdup_n_f16(0.0f);
svfloat16_t ax1, ax2, ax3, ax4, ax5, ax6, ax7, ax8;
svfloat16_t ay1, ay2, ay3, ay4, ay5, ay6, ay7, ay8;
for (int i = 0; i < np; i += ggml_f16_step) {
ay1 = GGML_F16x_VEC_LOAD(y + i + 0 * ggml_f16_epr, 0); // 8 elements
ax1 = GGML_F16x_VEC_LOAD(x[0] + i + 0*ggml_f16_epr, 0); // 8 elemnst
sum_00 = GGML_F16x_VEC_FMA(sum_00, ax1, ay1); // sum_00 = sum_00+ax1*ay1
ax1 = GGML_F16x_VEC_LOAD(x[1] + i + 0*ggml_f16_epr, 0); // 8 elements
sum_10 = GGML_F16x_VEC_FMA(sum_10, ax1, ay1);
ay2 = GGML_F16x_VEC_LOAD(y + i + 1 * ggml_f16_epr, 1); // next 8 elements
ax2 = GGML_F16x_VEC_LOAD(x[0] + i + 1*ggml_f16_epr, 1); // next 8 ekements
sum_01 = GGML_F16x_VEC_FMA(sum_01, ax2, ay2);
ax2 = GGML_F16x_VEC_LOAD(x[1] + i + 1*ggml_f16_epr, 1);
sum_11 = GGML_F16x_VEC_FMA(sum_11, ax2, ay2);
ay3 = GGML_F16x_VEC_LOAD(y + i + 2 * ggml_f16_epr, 2);
ax3 = GGML_F16x_VEC_LOAD(x[0] + i + 2*ggml_f16_epr, 2);
sum_02 = GGML_F16x_VEC_FMA(sum_02, ax3, ay3);
ax1 = GGML_F16x_VEC_LOAD(x[1] + i + 2*ggml_f16_epr, 2);
sum_12 = GGML_F16x_VEC_FMA(sum_12, ax3, ay3);
ay4 = GGML_F16x_VEC_LOAD(y + i + 3 * ggml_f16_epr, 3);
ax4 = GGML_F16x_VEC_LOAD(x[0] + i + 3*ggml_f16_epr, 3);
sum_03 = GGML_F16x_VEC_FMA(sum_03, ax4, ay4);
ax4 = GGML_F16x_VEC_LOAD(x[1] + i + 3*ggml_f16_epr, 3);
sum_13 = GGML_F16x_VEC_FMA(sum_13, ax4, ay4);
ay5 = GGML_F16x_VEC_LOAD(y + i + 4 * ggml_f16_epr, 4);
ax5 = GGML_F16x_VEC_LOAD(x[0] + i + 4*ggml_f16_epr, 4);
sum_00 = GGML_F16x_VEC_FMA(sum_00, ax5, ay5);
ax5 = GGML_F16x_VEC_LOAD(x[1] + i + 4*ggml_f16_epr, 4);
sum_10 = GGML_F16x_VEC_FMA(sum_10, ax5, ay5);
ay6 = GGML_F16x_VEC_LOAD(y + i + 5 * ggml_f16_epr, 5);
ax6 = GGML_F16x_VEC_LOAD(x[0] + i + 5*ggml_f16_epr, 5);
sum_01 = GGML_F16x_VEC_FMA(sum_01, ax6, ay6);
ax6 = GGML_F16x_VEC_LOAD(x[1] + i + 5*ggml_f16_epr, 5);
sum_11 = GGML_F16x_VEC_FMA(sum_11, ax6, ay6);
ay7 = GGML_F16x_VEC_LOAD(y + i + 6 * ggml_f16_epr, 6);
ax7 = GGML_F16x_VEC_LOAD(x[0] + i + 6*ggml_f16_epr, 6);
sum_02 = GGML_F16x_VEC_FMA(sum_02, ax7, ay7);
ax7 = GGML_F16x_VEC_LOAD(x[1] + i + 6*ggml_f16_epr, 6);
sum_12 = GGML_F16x_VEC_FMA(sum_12, ax7, ay7);
ay8 = GGML_F16x_VEC_LOAD(y + i + 7 * ggml_f16_epr, 7);
ax8 = GGML_F16x_VEC_LOAD(x[0] + i + 7*ggml_f16_epr, 7);
sum_03 = GGML_F16x_VEC_FMA(sum_03, ax8, ay8);
ax8 = GGML_F16x_VEC_LOAD(x[1] + i + 7*ggml_f16_epr, 7);
sum_13 = GGML_F16x_VEC_FMA(sum_13, ax8, ay8);
} }
}
#else
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC sum[GGML_VEC_DOT_UNROLL][GGML_F16_ARR] = { { GGML_F16_VEC_ZERO } }; const int np2 = (n & ~(ggml_f16_epr - 1));
for (int k = np; k < np2; k += ggml_f16_epr) {
svfloat16_t ry = GGML_F16x_VEC_LOAD(y + k, 0);
GGML_F16_VEC ax[GGML_F16_ARR]; svfloat16_t rx = GGML_F16x_VEC_LOAD(x[0] + k, 0);
GGML_F16_VEC ay[GGML_F16_ARR]; sum_00 = GGML_F16x_VEC_FMA(sum_00, rx, ry);
rx = GGML_F16x_VEC_LOAD(x[1] + k, 0);
sum_10 = GGML_F16x_VEC_FMA(sum_10, rx, ry);
}
for (int i = 0; i < np; i += GGML_F16_STEP) { if (np2 < n) {
for (int j = 0; j < GGML_F16_ARR; j++) { svbool_t pg = svwhilelt_b16(np2, n);
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j); svfloat16_t hx_0 = svld1_f16(pg, (const __fp16 *)(x[0] + np2));
svfloat16_t hx_1 = svld1_f16(pg, (const __fp16 *)(x[1] + np2));
svfloat16_t hy = svld1_f16(pg, (const __fp16 *)(y + np2));
for (int k = 0; k < GGML_VEC_DOT_UNROLL; ++k) { sum_00 = svmad_f16_x(pg, hx_0, hy, sum_00);
ax[j] = GGML_F16_VEC_LOAD(x[k] + i + j*GGML_F16_EPR, j); sum_10 = svmad_f16_x(pg, hx_1, hy, sum_10);
}
GGML_F16x_VEC_REDUCE(sumf[0], sum_00, sum_01, sum_02, sum_03);
GGML_F16x_VEC_REDUCE(sumf[1], sum_10, sum_11, sum_12, sum_13);
#elif defined(__riscv_v_intrinsic)
// todo: RVV impl
for (int i = 0; i < n; ++i) {
for (int j = 0; j < GGML_VEC_DOT_UNROLL; ++j) {
sumf[j] += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[j][i])*GGML_CPU_FP16_TO_FP32(y[i]));
}
}
#else
const int np = (n & ~(GGML_F16_STEP - 1));
sum[k][j] = GGML_F16_VEC_FMA(sum[k][j], ax[j], ay[j]); GGML_F16_VEC sum[GGML_VEC_DOT_UNROLL][GGML_F16_ARR] = { { GGML_F16_VEC_ZERO } };
GGML_F16_VEC ax[GGML_F16_ARR];
GGML_F16_VEC ay[GGML_F16_ARR];
for (int i = 0; i < np; i += GGML_F16_STEP) {
for (int j = 0; j < GGML_F16_ARR; j++) {
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j);
for (int k = 0; k < GGML_VEC_DOT_UNROLL; ++k) {
ax[j] = GGML_F16_VEC_LOAD(x[k] + i + j*GGML_F16_EPR, j);
sum[k][j] = GGML_F16_VEC_FMA(sum[k][j], ax[j], ay[j]);
}
} }
} }
}
// reduce sum0..sum3 to sum0 // reduce sum0..sum3 to sum0
for (int k = 0; k < GGML_VEC_DOT_UNROLL; ++k) { for (int k = 0; k < GGML_VEC_DOT_UNROLL; ++k) {
GGML_F16_VEC_REDUCE(sumf[k], sum[k]); GGML_F16_VEC_REDUCE(sumf[k], sum[k]);
}
// leftovers
for (int i = np; i < n; ++i) {
for (int j = 0; j < GGML_VEC_DOT_UNROLL; ++j) {
sumf[j] += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[j][i])*GGML_CPU_FP16_TO_FP32(y[i]));
} }
}
#endif // leftovers
for (int i = np; i < n; ++i) {
for (int j = 0; j < GGML_VEC_DOT_UNROLL; ++j) {
sumf[j] += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[j][i])*GGML_CPU_FP16_TO_FP32(y[i]));
}
}
#endif
#else #else
for (int i = 0; i < n; ++i) { for (int i = 0; i < n; ++i) {
for (int j = 0; j < GGML_VEC_DOT_UNROLL; ++j) { for (int j = 0; j < GGML_VEC_DOT_UNROLL; ++j) {
@@ -293,35 +397,112 @@ inline static void ggml_vec_mad_f32(const int n, float * GGML_RESTRICT y, const
inline static void ggml_vec_mad_f16(const int n, ggml_fp16_t * GGML_RESTRICT y, const ggml_fp16_t * GGML_RESTRICT x, const float v) { inline static void ggml_vec_mad_f16(const int n, ggml_fp16_t * GGML_RESTRICT y, const ggml_fp16_t * GGML_RESTRICT x, const float v) {
#if defined(GGML_SIMD) #if defined(GGML_SIMD)
#if defined(__riscv_v_intrinsic) #if defined(__ARM_FEATURE_SVE)
// todo: RVV impl const int sve_register_length = svcntb() * 8;
// scalar const int ggml_f16_epr = sve_register_length / 16;
for (int i = 0; i < n; ++i) { const int ggml_f16_step = 8 * ggml_f16_epr;
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i]) + GGML_CPU_FP16_TO_FP32(x[i])*v);
}
#else
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC vx = GGML_F16_VEC_SET1(v); GGML_F16x_VEC vx = GGML_F16x_VEC_SET1(v);
GGML_F16_VEC ax[GGML_F16_ARR]; const int np= (n & ~(ggml_f16_step - 1));
GGML_F16_VEC ay[GGML_F16_ARR];
for (int i = 0; i < np; i += GGML_F16_STEP) { svfloat16_t ax1, ax2, ax3, ax4, ax5, ax6, ax7, ax8;
for (int j = 0; j < GGML_F16_ARR; j++) { svfloat16_t ay1, ay2, ay3, ay4, ay5, ay6, ay7, ay8;
ax[j] = GGML_F16_VEC_LOAD(x + i + j*GGML_F16_EPR, j); for (int i = 0; i < np; i += ggml_f16_step) {
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j); ax1 = GGML_F16x_VEC_LOAD(x + i + 0 * ggml_f16_epr, 0);
ay[j] = GGML_F16_VEC_FMA(ay[j], ax[j], vx); ay1 = GGML_F16x_VEC_LOAD(y + i + 0 * ggml_f16_epr, 0);
ay1 = GGML_F16x_VEC_FMA(ay1, ax1, vx);
GGML_F16_VEC_STORE(y + i + j*GGML_F16_EPR, ay, j); GGML_F16x_VEC_STORE(y + i + 0 * ggml_f16_epr, ay1, 0);
ax2 = GGML_F16x_VEC_LOAD(x + i + 1 * ggml_f16_epr, 1);
ay2 = GGML_F16x_VEC_LOAD(y + i + 1 * ggml_f16_epr, 1);
ay2 = GGML_F16x_VEC_FMA(ay2, ax2, vx);
GGML_F16x_VEC_STORE(y + i + 1 * ggml_f16_epr, ay2, 1);
ax3 = GGML_F16x_VEC_LOAD(x + i + 2 * ggml_f16_epr, 2);
ay3 = GGML_F16x_VEC_LOAD(y + i + 2 * ggml_f16_epr, 2);
ay3 = GGML_F16x_VEC_FMA(ay3, ax3, vx);
GGML_F16x_VEC_STORE(y + i + 2 * ggml_f16_epr, ay3, 2);
ax4 = GGML_F16x_VEC_LOAD(x + i + 3 * ggml_f16_epr, 3);
ay4 = GGML_F16x_VEC_LOAD(y + i + 3 * ggml_f16_epr, 3);
ay4 = GGML_F16x_VEC_FMA(ay4, ax4, vx);
GGML_F16x_VEC_STORE(y + i + 3 * ggml_f16_epr, ay4, 3);
ax5 = GGML_F16x_VEC_LOAD(x + i + 4 * ggml_f16_epr, 4);
ay5 = GGML_F16x_VEC_LOAD(y + i + 4 * ggml_f16_epr, 4);
ay5 = GGML_F16x_VEC_FMA(ay5, ax5, vx);
GGML_F16x_VEC_STORE(y + i + 4 * ggml_f16_epr, ay5, 4);
ax6 = GGML_F16x_VEC_LOAD(x + i + 5 * ggml_f16_epr, 5);
ay6 = GGML_F16x_VEC_LOAD(y + i + 5 * ggml_f16_epr, 5);
ay6 = GGML_F16x_VEC_FMA(ay6, ax6, vx);
GGML_F16x_VEC_STORE(y + i + 5 * ggml_f16_epr, ay6, 5);
ax7 = GGML_F16x_VEC_LOAD(x + i + 6 * ggml_f16_epr, 6);
ay7 = GGML_F16x_VEC_LOAD(y + i + 6 * ggml_f16_epr, 6);
ay7 = GGML_F16x_VEC_FMA(ay7, ax7, vx);
GGML_F16x_VEC_STORE(y + i + 6 * ggml_f16_epr, ay7, 6);
ax8 = GGML_F16x_VEC_LOAD(x + i + 7 * ggml_f16_epr, 7);
ay8 = GGML_F16x_VEC_LOAD(y + i + 7 * ggml_f16_epr, 7);
ay8 = GGML_F16x_VEC_FMA(ay8, ax8, vx);
GGML_F16x_VEC_STORE(y + i + 7 * ggml_f16_epr, ay8, 7);
} }
} const int np2 = (n & ~(ggml_f16_epr - 1));
for (int k = np; k < np2; k += ggml_f16_epr) {
svfloat16_t rx = GGML_F16x_VEC_LOAD(x + k, 0);
svfloat16_t ry = GGML_F16x_VEC_LOAD(y + k, 0);
ry = GGML_F16x_VEC_FMA(ry, rx, vx);
// leftovers GGML_F16x_VEC_STORE(y + k, ry, 0);
for (int i = np; i < n; ++i) { }
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i]) + GGML_CPU_FP16_TO_FP32(x[i])*v);
} if (np2 < n) {
#endif svbool_t pg = svwhilelt_b16(np2, n);
svfloat16_t hx = svld1_f16(pg, (const __fp16 *)(x + np2));
svfloat16_t hy = svld1_f16(pg, (const __fp16 *)(y + np2));
hy = svmad_f16_x(pg, hx, vx, hy);
svst1_f16(pg, (__fp16 *)(y + np2), hy);
}
#elif defined(__riscv_v_intrinsic)
// todo: RVV impl
// scalar
for (int i = 0; i < n; ++i) {
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i]) + GGML_CPU_FP16_TO_FP32(x[i])*v);
}
#else
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC vx = GGML_F16_VEC_SET1(v);
GGML_F16_VEC ax[GGML_F16_ARR];
GGML_F16_VEC ay[GGML_F16_ARR];
for (int i = 0; i < np; i += GGML_F16_STEP) {
for (int j = 0; j < GGML_F16_ARR; j++) {
ax[j] = GGML_F16_VEC_LOAD(x + i + j*GGML_F16_EPR, j);
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j);
ay[j] = GGML_F16_VEC_FMA(ay[j], ax[j], vx);
GGML_F16_VEC_STORE(y + i + j*GGML_F16_EPR, ay, j);
}
}
// leftovers
for (int i = np; i < n; ++i) {
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i]) + GGML_CPU_FP16_TO_FP32(x[i])*v);
}
#endif
#else #else
// scalar // scalar
for (int i = 0; i < n; ++i) { for (int i = 0; i < n; ++i) {
@@ -517,33 +698,59 @@ inline static void ggml_vec_scale_f32(const int n, float * y, const float v) {
inline static void ggml_vec_scale_f16(const int n, ggml_fp16_t * y, const float v) { inline static void ggml_vec_scale_f16(const int n, ggml_fp16_t * y, const float v) {
#if defined(GGML_SIMD) #if defined(GGML_SIMD)
#if defined(__riscv_v_intrinsic) #if defined(__ARM_FEATURE_SVE)
// todo: RVV impl const int sve_register_length = svcntb() * 8;
// scalar const int ggml_f16_epr = sve_register_length / 16;
for (int i = 0; i < n; ++i) { const int ggml_f16_step = 2 * ggml_f16_epr;
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i])*v);
}
#else
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC vx = GGML_F16_VEC_SET1(v); GGML_F16x_VEC vx = GGML_F16x_VEC_SET1(v);
const int np = (n & ~(ggml_f16_step - 1));
svfloat16_t ay1, ay2;
GGML_F16_VEC ay[GGML_F16_ARR]; for (int i = 0; i < np; i += ggml_f16_step) {
ay1 = GGML_F16x_VEC_LOAD(y + i + 0*ggml_f16_epr, 0);
ay1 = GGML_F16x_VEC_MUL(ay1, vx);
GGML_F16x_VEC_STORE(y + i + 0*ggml_f16_epr, ay1, 0);
for (int i = 0; i < np; i += GGML_F16_STEP) { ay2 = GGML_F16x_VEC_LOAD(y + i + 1*ggml_f16_epr, 1);
for (int j = 0; j < GGML_F16_ARR; j++) { ay2 = GGML_F16x_VEC_MUL(ay2, vx);
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j); GGML_F16x_VEC_STORE(y + i + 1*ggml_f16_epr, ay2, 1);
ay[j] = GGML_F16_VEC_MUL(ay[j], vx);
GGML_F16_VEC_STORE(y + i + j*GGML_F16_EPR, ay, j);
} }
} // leftovers
// maximum number of leftover elements will be less that ggmlF_16x_epr. Apply predicated svmad on available elements only
if (np < n) {
svbool_t pg = svwhilelt_b16(np, n);
svfloat16_t hy = svld1_f16(pg, (__fp16 *)(y + np));
svfloat16_t out = svmul_f16_m(pg, hy, vx);
svst1_f16(pg, (__fp16 *)(y + np), out);
}
#elif defined(__riscv_v_intrinsic)
// todo: RVV impl
// scalar
for (int i = 0; i < n; ++i) {
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i])*v);
}
#else
const int np = (n & ~(GGML_F16_STEP - 1));
// leftovers GGML_F16_VEC vx = GGML_F16_VEC_SET1(v);
for (int i = np; i < n; ++i) {
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i])*v); GGML_F16_VEC ay[GGML_F16_ARR];
}
#endif for (int i = 0; i < np; i += GGML_F16_STEP) {
for (int j = 0; j < GGML_F16_ARR; j++) {
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR, j);
ay[j] = GGML_F16_VEC_MUL(ay[j], vx);
GGML_F16_VEC_STORE(y + i + j*GGML_F16_EPR, ay, j);
}
}
// leftovers
for (int i = np; i < n; ++i) {
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i])*v);
}
#endif
#else #else
// scalar // scalar
for (int i = 0; i < n; ++i) { for (int i = 0; i < n; ++i) {