From: Prashant Vithule Date: Mon, 1 Sep 2025 18:13:16 +0000 (+0530) Subject: ggml: aarch64: Implement SVE F16 kernels for vector functions (#15115) X-Git-Tag: upstream/0.0.6527~181 X-Git-Url: https://git.djapps.eu/?a=commitdiff_plain;h=a0c2b207c596d1092a08615de61ab56a7d63515f;p=pkg%2Fggml%2Fsources%2Fllama.cpp 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 --- diff --git a/ggml/src/ggml-cpu/simd-mappings.h b/ggml/src/ggml-cpu/simd-mappings.h index f71ce580..8bd56bda 100644 --- a/ggml/src/ggml-cpu/simd-mappings.h +++ b/ggml/src/ggml-cpu/simd-mappings.h @@ -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_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 #if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) diff --git a/ggml/src/ggml-cpu/vec.cpp b/ggml/src/ggml-cpu/vec.cpp index d8ec3b81..f2412dcc 100644 --- a/ggml/src/ggml-cpu/vec.cpp +++ b/ggml/src/ggml-cpu/vec.cpp @@ -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; -#if defined(GGML_SIMD) && !defined(__riscv_v_intrinsic) - const int np = (n & ~(GGML_F16_STEP - 1)); - GGML_F16_VEC sum[GGML_F16_ARR] = { GGML_F16_VEC_ZERO }; +#if defined(GGML_SIMD) && !defined(__riscv_v_intrinsic) + #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 + + 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); + + 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) { + 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); + + ax2 = GGML_F16x_VEC_LOAD(x + i + 1 * ggml_f16_epr, 1); + ay2 = GGML_F16x_VEC_LOAD(y + i + 1 * ggml_f16_epr, 1); + sum2 = GGML_F16x_VEC_FMA(sum2, ax2, ay2); + + 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); + } - GGML_F16_VEC ax[GGML_F16_ARR]; - GGML_F16_VEC ay[GGML_F16_ARR]; + const int np2 = (n & ~(ggml_f16_epr - 1)); // round down to multiple of 8 + 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); + } - 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); + if (np2 < n) { + 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)); - sum[j] = GGML_F16_VEC_FMA(sum[j], ax[j], ay[j]); + sum1 = svmad_f16_x(pg, hx, hy, sum1); } - } + GGML_F16x_VEC_REDUCE(sumf, sum1, sum2, sum3, sum4); + #else + const int np = (n & ~(GGML_F16_STEP - 1)); - // reduce sum0..sum3 to sum0 - GGML_F16_VEC_REDUCE(sumf, sum); + GGML_F16_VEC sum[GGML_F16_ARR] = { GGML_F16_VEC_ZERO }; - // 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])); - } + GGML_F16_VEC ax[GGML_F16_ARR]; + GGML_F16_VEC ay[GGML_F16_ARR]; - // if you hit this, you are likely running outside the FP range - assert(!isnan(sumf) && !isinf(sumf)); + 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 for (int i = 0; i < n; ++i) { sumf += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[i])*GGML_CPU_FP16_TO_FP32(y[i])); diff --git a/ggml/src/ggml-cpu/vec.h b/ggml/src/ggml-cpu/vec.h index 8ccf340d..1f7c5996 100644 --- a/ggml/src/ggml-cpu/vec.h +++ b/ggml/src/ggml-cpu/vec.h @@ -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(__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])); + #if defined(__ARM_FEATURE_SVE) + + const int sve_register_length = svcntb() * 8; + 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 + + 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); + } + + 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); + + svfloat16_t rx = GGML_F16x_VEC_LOAD(x[0] + k, 0); + 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); } - } -#else - const int np = (n & ~(GGML_F16_STEP - 1)); - GGML_F16_VEC sum[GGML_VEC_DOT_UNROLL][GGML_F16_ARR] = { { GGML_F16_VEC_ZERO } }; + if (np2 < n) { + svbool_t pg = svwhilelt_b16(np2, n); + 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)); - GGML_F16_VEC ax[GGML_F16_ARR]; - GGML_F16_VEC ay[GGML_F16_ARR]; + sum_00 = svmad_f16_x(pg, hx_0, hy, sum_00); + 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)); - 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); + GGML_F16_VEC sum[GGML_VEC_DOT_UNROLL][GGML_F16_ARR] = { { GGML_F16_VEC_ZERO } }; - for (int k = 0; k < GGML_VEC_DOT_UNROLL; ++k) { - ax[j] = GGML_F16_VEC_LOAD(x[k] + i + j*GGML_F16_EPR, j); + GGML_F16_VEC ax[GGML_F16_ARR]; + GGML_F16_VEC ay[GGML_F16_ARR]; - sum[k][j] = GGML_F16_VEC_FMA(sum[k][j], ax[j], ay[j]); + 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 - for (int k = 0; k < GGML_VEC_DOT_UNROLL; ++k) { - GGML_F16_VEC_REDUCE(sumf[k], sum[k]); - } + // reduce sum0..sum3 to sum0 + for (int k = 0; k < GGML_VEC_DOT_UNROLL; ++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])); + // 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 + #endif #else for (int i = 0; i < n; ++i) { 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) { #if defined(GGML_SIMD) -#if 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)); + #if defined(__ARM_FEATURE_SVE) + const int sve_register_length = svcntb() * 8; + const int ggml_f16_epr = sve_register_length / 16; + const int ggml_f16_step = 8 * ggml_f16_epr; + + GGML_F16x_VEC vx = GGML_F16x_VEC_SET1(v); + + const int np= (n & ~(ggml_f16_step - 1)); - GGML_F16_VEC vx = GGML_F16_VEC_SET1(v); + 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) { + ax1 = GGML_F16x_VEC_LOAD(x + i + 0 * ggml_f16_epr, 0); + ay1 = GGML_F16x_VEC_LOAD(y + i + 0 * ggml_f16_epr, 0); + ay1 = GGML_F16x_VEC_FMA(ay1, ax1, vx); - GGML_F16_VEC ax[GGML_F16_ARR]; - GGML_F16_VEC ay[GGML_F16_ARR]; + GGML_F16x_VEC_STORE(y + i + 0 * ggml_f16_epr, ay1, 0); - 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); + 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_F16_VEC_STORE(y + i + j*GGML_F16_EPR, ay, j); + 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 - 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 + GGML_F16x_VEC_STORE(y + k, ry, 0); + } + + if (np2 < n) { + 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 // scalar 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) { #if defined(GGML_SIMD) -#if 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)); + #if defined(__ARM_FEATURE_SVE) + const int sve_register_length = svcntb() * 8; + const int ggml_f16_epr = sve_register_length / 16; + const int ggml_f16_step = 2 * ggml_f16_epr; + + GGML_F16x_VEC vx = GGML_F16x_VEC_SET1(v); + const int np = (n & ~(ggml_f16_step - 1)); + svfloat16_t ay1, ay2; + + 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); + + ay2 = GGML_F16x_VEC_LOAD(y + i + 1*ggml_f16_epr, 1); + ay2 = GGML_F16x_VEC_MUL(ay2, vx); + GGML_F16x_VEC_STORE(y + i + 1*ggml_f16_epr, ay2, 1); + } + // 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)); - GGML_F16_VEC vx = GGML_F16_VEC_SET1(v); + GGML_F16_VEC vx = GGML_F16_VEC_SET1(v); - GGML_F16_VEC ay[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); - ay[j] = GGML_F16_VEC_MUL(ay[j], vx); + 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); + 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 + // 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 // scalar for (int i = 0; i < n; ++i) {