ggml-hexagon: mm for mtmd (#17894)
* feat: add run_mtmd script for hexagon * fix: fix issue in fp16xfp32 mm * fix: remove opt_experiment for fp16xfp32 mm * fix: ggml-hexagon: matmul fp16xfp32 support non-contigious src0 * fix: fix syntax check for run-mtmd.sh for cli
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@ -1976,9 +1976,6 @@ static bool ggml_hexagon_supported_mul_mat(const struct ggml_hexagon_session * s
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break;
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break;
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case GGML_TYPE_F16:
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case GGML_TYPE_F16:
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if (!opt_experimental) {
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return false;
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}
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break;
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break;
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default:
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default:
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@ -903,7 +903,7 @@ static void vec_dot_f16_f32(const int n, float * restrict s, const void * restri
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const float * restrict vy = (const float * restrict) y;
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const float * restrict vy = (const float * restrict) y;
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for (uint32_t i = 0; i < n; i++) {
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for (uint32_t i = 0; i < n; i++) {
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rsum += vx[i] * (__fp16) vy[i];
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rsum += (float)vx[i] * vy[i];
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}
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}
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*s = rsum;
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*s = rsum;
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return;
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return;
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@ -917,7 +917,7 @@ static void vec_dot_f16_f32(const int n, float * restrict s, const void * restri
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// for some reason we need volatile here so that the compiler doesn't try anything funky
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// for some reason we need volatile here so that the compiler doesn't try anything funky
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volatile HVX_Vector rsum = Q6_V_vsplat_R(0);
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volatile HVX_Vector rsum = Q6_V_vsplat_R(0);
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float r_sum_scalar = 0.0f;
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uint32_t i = 0;
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uint32_t i = 0;
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for (i = 0; i < nv0; i++) {
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for (i = 0; i < nv0; i++) {
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@ -926,31 +926,42 @@ static void vec_dot_f16_f32(const int n, float * restrict s, const void * restri
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HVX_Vector x = vx[i];
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HVX_Vector x = vx[i];
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HVX_VectorPair xp = Q6_Wqf32_vmpy_VhfVhf(Q6_Vh_vshuff_Vh(x), Q6_Vh_vsplat_R(0x3C00)); // mul by 1.0
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HVX_VectorPair xp = Q6_Wqf32_vmpy_VhfVhf(Q6_Vh_vshuff_Vh(x), Q6_Vh_vsplat_R(0x3C00)); // mul by 1.0
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HVX_Vector hi = Q6_Vqf32_vmpy_VsfVsf(Q6_Vsf_equals_Vqf32(Q6_V_hi_W(xp)), Q6_V_hi_W(yp));
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//NOTE: need volatile here to prevent compiler optimization
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HVX_Vector lo = Q6_Vqf32_vmpy_VsfVsf(Q6_Vsf_equals_Vqf32(Q6_V_lo_W(xp)), Q6_V_lo_W(yp));
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// Seem compiler cannot guarantee read-after-write??
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volatile HVX_Vector hi = Q6_Vqf32_vmpy_VsfVsf(Q6_Vsf_equals_Vqf32(Q6_V_hi_W(xp)), Q6_V_hi_W(yp));
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volatile HVX_Vector lo = Q6_Vqf32_vmpy_VsfVsf(Q6_Vsf_equals_Vqf32(Q6_V_lo_W(xp)), Q6_V_lo_W(yp));
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HVX_Vector sum = Q6_Vqf32_vadd_Vqf32Vqf32(hi, lo);
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HVX_Vector sum = Q6_Vqf32_vadd_Vqf32Vqf32(hi, lo);
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rsum = Q6_Vqf32_vadd_Vqf32Vqf32(rsum, sum);
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rsum = Q6_Vqf32_vadd_Vqf32Vqf32(rsum, sum);
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}
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}
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if (nv1) {
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if (nv1) {
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HVX_VectorPair yp = vy[i];
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// HVX_VectorPair yp = vy[i];
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HVX_Vector x = vx[i];
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// HVX_Vector x = vx[i];
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HVX_VectorPair xp = Q6_Wqf32_vmpy_VhfVhf(Q6_Vh_vshuff_Vh(x), Q6_Vh_vsplat_R(0x3C00)); // mul by 1.0
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// HVX_VectorPair xp = Q6_Wqf32_vmpy_VhfVhf(Q6_Vh_vshuff_Vh(x), Q6_Vh_vsplat_R(0x3C00)); // mul by 1.0
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if (nv1 >= 32) {
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// if (nv1 >= 32) {
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HVX_Vector hi = Q6_Vqf32_vmpy_VsfVsf(Q6_Vsf_equals_Vqf32(Q6_V_hi_W(xp)), Q6_V_hi_W(yp));
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// volatile HVX_Vector hi = Q6_Vqf32_vmpy_VsfVsf(Q6_Vsf_equals_Vqf32(Q6_V_hi_W(xp)), Q6_V_hi_W(yp));
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rsum = Q6_Vqf32_vadd_Vqf32Vqf32(rsum, hi);
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// rsum = Q6_Vqf32_vadd_Vqf32Vqf32(rsum, hi);
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nv1 -= 32;
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// nv1 -= 32;
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}
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// }
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// rsum = hvx_vec_qf32_reduce_sum(rsum);
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// if (nv1) {
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// volatile HVX_Vector lo = Q6_Vqf32_vmpy_VsfVsf(Q6_Vsf_equals_Vqf32(Q6_V_lo_W(xp)), Q6_V_lo_W(yp));
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// HVX_Vector sum = hvx_vec_qf32_reduce_sum_n(lo, nv1);
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// rsum = Q6_Vqf32_vadd_Vqf32Vqf32(rsum, sum);
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// }
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//process the remainder using scalar loop
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rsum = hvx_vec_qf32_reduce_sum(rsum);
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rsum = hvx_vec_qf32_reduce_sum(rsum);
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const __fp16 * restrict sx = (const __fp16 * restrict) x;
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const float * restrict sy = (const float * restrict) y;
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if (nv1) {
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for (uint32_t i = nv0 * 64; i < n; i++) {
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HVX_Vector lo = Q6_Vqf32_vmpy_VsfVsf(Q6_Vsf_equals_Vqf32(Q6_V_lo_W(xp)), Q6_V_lo_W(yp));
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r_sum_scalar += (float) sx[i] * sy[i];
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HVX_Vector sum = hvx_vec_qf32_reduce_sum_n(lo, nv1);
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rsum = Q6_Vqf32_vadd_Vqf32Vqf32(rsum, sum);
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}
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}
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// hvx_vec_dump_fp16("X", x);
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// hvx_vec_dump_fp16("X", x);
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@ -961,7 +972,7 @@ static void vec_dot_f16_f32(const int n, float * restrict s, const void * restri
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rsum = hvx_vec_qf32_reduce_sum(rsum);
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rsum = hvx_vec_qf32_reduce_sum(rsum);
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}
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}
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*s = hvx_vec_get_fp32(Q6_Vsf_equals_Vqf32(rsum));
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*s = hvx_vec_get_fp32(Q6_Vsf_equals_Vqf32(rsum)) + r_sum_scalar;
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# ifdef HTP_DEBUG
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# ifdef HTP_DEBUG
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{
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{
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@ -1498,9 +1509,6 @@ static void matmul_f16_f32(struct htp_tensor * restrict src0,
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uint64_t t1, t2;
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uint64_t t1, t2;
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t1 = HAP_perf_get_qtimer_count();
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t1 = HAP_perf_get_qtimer_count();
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const size_t src0_row_size = sizeof(__fp16) * ne00;
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const size_t src1_row_size = sizeof(float) * ne10;
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assert(ne12 % ne02 == 0);
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assert(ne12 % ne02 == 0);
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assert(ne13 % ne03 == 0);
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assert(ne13 % ne03 == 0);
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@ -1510,8 +1518,6 @@ static void matmul_f16_f32(struct htp_tensor * restrict src0,
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// This is the size of the rest of the dimensions of the result
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// This is the size of the rest of the dimensions of the result
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const uint32_t nr1 = ne1 * ne2 * ne3;
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const uint32_t nr1 = ne1 * ne2 * ne3;
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uint32_t chunk_size = 64;
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// distribute the thread work across the inner or outer loop based on which one is larger
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// distribute the thread work across the inner or outer loop based on which one is larger
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uint32_t nchunk0 = nr0 > nr1 ? nth : 1; // parallelize by src0 rows
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uint32_t nchunk0 = nr0 > nr1 ? nth : 1; // parallelize by src0 rows
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uint32_t nchunk1 = nr0 > nr1 ? 1 : nth; // parallelize by src1 rows
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uint32_t nchunk1 = nr0 > nr1 ? 1 : nth; // parallelize by src1 rows
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@ -1544,11 +1550,11 @@ static void matmul_f16_f32(struct htp_tensor * restrict src0,
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const uint32_t blck_0 = 64;
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const uint32_t blck_0 = 64;
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const uint32_t blck_1 = 64;
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const uint32_t blck_1 = 64;
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float tmp[32];
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__attribute__((aligned(128))) float tmp[64];
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for (uint32_t iir1 = ir1_start; iir1 < ir1_end; iir1 += blck_1) {
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for (uint32_t iir1 = ir1_start; iir1 < ir1_end; iir1 += blck_1) {
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for (uint32_t iir0 = ir0_start; iir0 < ir0_end; iir0 += blck_0) {
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for (uint32_t iir0 = ir0_start; iir0 < ir0_end; iir0 += blck_0) {
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for (uint32_t ir1 = iir1; ir1 < iir1 + blck_1 && ir1 < ir1_end; ir1++) {
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for (uint32_t ir1 = iir1; ir1 < MIN(iir1 + blck_1, ir1_end); ir1++) {
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const uint32_t i13 = (ir1 / (ne12 * ne1));
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const uint32_t i13 = (ir1 / (ne12 * ne1));
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const uint32_t i12 = (ir1 - i13 * ne12 * ne1) / ne1;
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const uint32_t i12 = (ir1 - i13 * ne12 * ne1) / ne1;
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const uint32_t i11 = (ir1 - i13 * ne12 * ne1 - i12 * ne1);
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const uint32_t i11 = (ir1 - i13 * ne12 * ne1 - i12 * ne1);
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@ -1561,13 +1567,16 @@ static void matmul_f16_f32(struct htp_tensor * restrict src0,
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const uint32_t i2 = i12;
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const uint32_t i2 = i12;
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const uint32_t i3 = i13;
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const uint32_t i3 = i13;
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const uint8_t * restrict src0_row = (const uint8_t *) src0->data + (0 + i02 * nb02 + i03 * nb03);
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const uint8_t * restrict src0_base = (const uint8_t *) src0->data + (0 + i02 * nb02 + i03 * nb03);
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const uint8_t * restrict src1_col =
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const uint8_t * restrict src1_col =
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(const uint8_t *) src1->data + (i11 + i12 * ne11 + i13 * ne12 * ne11) * src1_row_size;
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(const uint8_t *) src1->data + (i11 * nb11 + i12 * nb12 + i13 * nb13);
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float * dst_col = (float *) ((uint8_t * restrict) dst->data + (i1 * nb1 + i2 * nb2 + i3 * nb3));
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float * dst_col = (float *) ((uint8_t * restrict) dst->data + (i1 * nb1 + i2 * nb2 + i3 * nb3));
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for (uint32_t ir0 = iir0; ir0 < iir0 + blck_0 && ir0 < ir0_end; ir0++) {
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const uint32_t ir0_block_end = MIN(iir0 + blck_0, ir0_end);
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vec_dot_f16_f32(ne00, &tmp[ir0 - iir0], src0_row + ir0 * src0_row_size, src1_col);
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for (uint32_t ir0 = iir0; ir0 < ir0_block_end; ir0++) {
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// Use nb01 stride for non-contiguous src0 support
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const uint8_t * restrict src0_row = src0_base + ir0 * nb01;
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vec_dot_f16_f32(ne00, &tmp[ir0 - iir0], src0_row, src1_col);
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}
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}
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hvx_copy_fp32_ua((uint8_t *) &dst_col[iir0], (uint8_t *) tmp, MIN(iir0 + blck_0, ir0_end) - iir0);
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hvx_copy_fp32_ua((uint8_t *) &dst_col[iir0], (uint8_t *) tmp, MIN(iir0 + blck_0, ir0_end) - iir0);
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@ -0,0 +1,65 @@
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#!/bin/sh
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#
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# Basedir on device
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basedir=/data/local/tmp/llama.cpp
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cli_opts=
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branch=.
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[ "$B" != "" ] && branch=$B
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adbserial=
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[ "$S" != "" ] && adbserial="-s $S"
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model="gemma-3-4b-it-Q4_0.gguf"
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[ "$M" != "" ] && model="$M"
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mmproj="mmproj-F16.gguf"
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[ "$MMPROJ" != "" ] && mmproj="$MMPROJ"
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image=
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[ "$IMG" != "" ] && image="$IMG"
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device="HTP0"
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[ "$D" != "" ] && device="$D"
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verbose=
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[ "$V" != "" ] && verbose="GGML_HEXAGON_VERBOSE=$V"
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experimental="GGML_HEXAGON_EXPERIMENTAL=1"
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[ "$E" != "" ] && experimental="GGML_HEXAGON_EXPERIMENTAL=$E"
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sched=
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[ "$SCHED" != "" ] && sched="GGML_SCHED_DEBUG=2" cli_opts="$cli_opts -v"
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profile=
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[ "$PROF" != "" ] && profile="GGML_HEXAGON_PROFILE=$PROF GGML_HEXAGON_OPSYNC=1"
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opmask=
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[ "$OPMASK" != "" ] && opmask="GGML_HEXAGON_OPMASK=$OPMASK"
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nhvx=
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[ "$NHVX" != "" ] && nhvx="GGML_HEXAGON_NHVX=$NHVX"
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ndev=
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[ "$NDEV" != "" ] && ndev="GGML_HEXAGON_NDEV=$NDEV"
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# MTMD backend device for vision model (defaults to CPU if not set)
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mtmd_backend=
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[ "$MTMD_DEVICE" != "" ] && mtmd_backend="MTMD_BACKEND_DEVICE=$MTMD_DEVICE"
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set -x
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adb $adbserial shell " \
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cd $basedir; ulimit -c unlimited; \
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LD_LIBRARY_PATH=$basedir/$branch/lib \
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ADSP_LIBRARY_PATH=$basedir/$branch/lib \
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$verbose $experimental $sched $opmask $profile $nhvx $ndev $mtmd_backend \
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./$branch/bin/llama-mtmd-cli --no-mmap -m $basedir/../gguf/$model \
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--mmproj $basedir/../gguf/$mmproj \
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--image $basedir/../gguf/$image \
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--poll 1000 -t 6 --cpu-mask 0xfc --cpu-strict 1 \
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--ctx-size 8192 --batch-size 128 -ctk q8_0 -ctv q8_0 -fa on \
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-ngl 99 --device $device -v $cli_opts $@ \
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"
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