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SVE optimised float WSSJ kernel (#2917)
* optimisation of wssj in sve * clang format * compile bug fix * update comments * clang format * Update cpp/daal/src/algorithms/svm/svm_train_common_sve_impl.i Co-authored-by: Alexander Andreev <[email protected]> --------- Co-authored-by: Alexander Andreev <[email protected]>
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cpp/daal/src/algorithms/svm/svm_train_common_sve_impl.i
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| /******************************************************************************* | ||
| * Copyright contributors to the oneDAL project | ||
| * | ||
| * Licensed under the Apache License, Version 2.0 (the "License"); | ||
| * you may not use this file except in compliance with the License. | ||
| * You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| *******************************************************************************/ | ||
| /* | ||
| * Contains SVE optimizations for WSSj (Working Set Selection) algorithm. | ||
| */ | ||
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| #include <arm_sve.h> | ||
| #include "src/services/service_data_utils.h" | ||
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| namespace daal | ||
| { | ||
| namespace algorithms | ||
| { | ||
| namespace svm | ||
| { | ||
| namespace training | ||
| { | ||
| namespace internal | ||
| { | ||
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| /** | ||
| * \brief Working set selection (WSSj) function. | ||
| * Select an index j from a pair of indices B = {i, j} using WSS algorithm. | ||
| * | ||
| * \return The function implicitly returns GMax, which represents: | ||
| * M(alpha) = max { (GMin - (-y[j]*grad[j]))^2 / (2 * (Kii + Kjj - 2Kij)) } : j belongs to I_LOW(alpha) | ||
| */ | ||
| template <> | ||
| inline void HelperTrainSVM<float, sve>::WSSjLocal(const size_t jStart, const size_t jEnd, const float * KiBlock, const float * kernelDiag, | ||
| const float * grad, const char * I, const float GMin, const float Kii, const float tau, int & Bj, | ||
| float & GMax, float & GMax2, float & delta, SignNuType signNuType) | ||
| { | ||
| const int w = (int)svcntw(); //vector length | ||
| float fpMax = MaxVal<float>::get(); | ||
| float GMax2Local = -fpMax; // store min(grad[i]) or max(y[i]*grad[i]), y[i]*grad[i] = -GMin2 | ||
| float GMaxLocal = -fpMax; // store min(-b^2/a) or max(b^2/a), b^2/a = -GMin | ||
| float GMinLocal = GMin; | ||
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| float zero(0.0); | ||
| float two(2.0); | ||
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| const char sign = getSign(signNuType); | ||
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| svbool_t pgf = svptrue_b32(); //predicate for float | ||
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| svfloat32_t valGMax2 = svdup_f32(GMax2Local); | ||
| svfloat32_t valGMax = svdup_f32(GMaxLocal); | ||
| svfloat32_t valGMin = svdup_f32(GMinLocal); | ||
| svint32_t Bj_vec = svdup_s32(-1); | ||
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| // some constants used during optimization | ||
| // enum SVMVectorStatus low = 0x2 | ||
| svint32_t vecSignLow; | ||
| if (signNuType == SignNuType::none) | ||
| { | ||
| vecSignLow = svdup_n_s32(low); | ||
| } | ||
| else | ||
| { | ||
| DAAL_ASSERT((sign & (sign - 1)) == 0) // used to make sure sign is always having 1 bit set | ||
| svint32_t t1 = svdup_n_s32(low); | ||
| svint32_t t2 = svdup_n_s32(sign); | ||
| vecSignLow = svorr_s32_z(pgf, t1, t2); | ||
| } | ||
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| svfloat32_t two_vec = svdup_f32(two); | ||
| svfloat32_t Kii_vec = svdup_f32(Kii); | ||
| svfloat32_t tau_vec = svdup_f32(tau); | ||
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| for (size_t j_cur = jStart; j_cur < jEnd; j_cur += w) | ||
| { | ||
| svint32_t Bj_vec_cur = svindex_s32(j_cur, 1); // Bj value starts with j_cur | ||
| svbool_t pg2 = svwhilelt_b32(j_cur, jEnd); // adapts to vector length | ||
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| svint32_t vec_I = svld1sb_s32(pg2, reinterpret_cast<const int8_t *>(&I[j_cur])); // load chars | ||
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| // Combine 2 if conditions | ||
| // cond1: !(I[j]&sign) {continue} | ||
| // cond2: (I[j]&low)!=low {continue} | ||
| // combined: (I[j] & (sign | low)) == (sign | low) | ||
| // assertion @L63 is a prerequisite for the combined condition to satisfy | ||
| svint32_t result_of_and32 = svand_s32_m(pg2, vec_I, vecSignLow); | ||
| pg2 = svcmpeq_s32(pg2, result_of_and32, vecSignLow); // if pg2 bit is 0 then continue; | ||
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| svfloat32_t valGrad = svld1_f32(pg2, &grad[j_cur]); // load grads | ||
| // if (gradj > GMax2) { GMax2 = gradj; } | ||
| valGMax2 = svmax_f32_m(pg2, valGMax2, valGrad); | ||
| // cond3: if (gradj < GMin) { continue; } | ||
| svbool_t cond3 = svcmpge_f32(pg2, valGrad, valGMin); | ||
| pg2 = svand_b_z(pg2, pg2, cond3); // combine all 3 conditions | ||
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| svfloat32_t b_vec = svsub_f32_x(pg2, valGMin, valGrad); // b = Gmin - grad | ||
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| svfloat32_t KiBlock_vec = svld1_f32(pg2, KiBlock + j_cur - jStart); // load kiBlocs | ||
| svfloat32_t kernelDiag_vec = svld1_f32(pg2, &kernelDiag[j_cur]); // load kernelDiags | ||
| svfloat32_t a_vec = svnmls_f32_x(pg2, kernelDiag_vec, two_vec, KiBlock_vec); // a_tmp = two * KiBlock[j - jStart] - kernelDiag[j] | ||
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| // originally, if a < 0, a = tau | ||
| // mask3_ : 1 if Kii > a_tmp | ||
| // if mask3_ : 1, a = Kii - a_tmp, else a = tau. | ||
| svbool_t mask3_ = svcmpgt_f32(pg2, Kii_vec, a_vec); | ||
| a_vec = svsel_f32(mask3_, svsub_f32_x(mask3_, Kii_vec, a_vec), tau_vec); | ||
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| svfloat32_t dt_vec = svdiv_f32_x(pg2, b_vec, a_vec); // b/a = delta. | ||
| svfloat32_t objFunc_vec = svmul_f32_x(pg2, dt_vec, b_vec); // objFunc = b * delta | ||
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| svbool_t mask4_ = svcmpgt_f32(pg2, objFunc_vec, valGMax); // if (objFunc > GMax) | ||
| valGMax = svsel_f32(mask4_, objFunc_vec, valGMax); // if mask is 1, valGMax = objFunc_vec, else valGMax original value | ||
| Bj_vec = svsel_s32(mask4_, Bj_vec_cur, Bj_vec); // if mask is 1, Bj_vec = Bj_vec_cur, else Bj_vec original value | ||
| } | ||
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| // reductions | ||
| GMax = svmaxv_f32(pgf, valGMax); | ||
| GMax2 = svmaxv_f32(pgf, valGMax2); | ||
| svbool_t tmp_mask = svcmpeq(pgf, svdup_f32(GMax), valGMax); | ||
| Bj = svmaxv_s32(tmp_mask, Bj_vec); | ||
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| if (Bj != -1) | ||
| { | ||
| const double gradBj = grad[Bj]; | ||
| const double b = GMin - gradBj; | ||
| double a = Kii + kernelDiag[Bj] - two * KiBlock[Bj - jStart]; | ||
| if (a <= zero) | ||
| { | ||
| a = tau; | ||
| } | ||
| delta = b / a; | ||
| GMax = b * delta; | ||
| } | ||
| else | ||
| { | ||
| GMax = -fpMax; | ||
| GMax2 = -fpMax; | ||
| } | ||
| delta = -delta; | ||
| } | ||
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| } // namespace internal | ||
| } // namespace training | ||
| } // namespace svm | ||
| } // namespace algorithms | ||
| } // namespace daal |