cpu_mxv.hpp

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#ifndef SPLA_CPU_MXV_HPP
#define SPLA_CPU_MXV_HPP
 
#include <schedule/schedule_tasks.hpp>
 
#include <core/dispatcher.hpp>
#include <core/registry.hpp>
#include <core/tmatrix.hpp>
#include <core/top.hpp>
#include <core/tscalar.hpp>
#include <core/ttype.hpp>
#include <core/tvector.hpp>
 
namespace spla {
 
    template<typename T>
    class Algo_mxv_masked_cpu final : public RegistryAlgo {
    public:
        ~Algo_mxv_masked_cpu() override = default;
 
        std::string get_name() override {
            return "mxv_masked";
        }
 
        std::string get_description() override {
            return "sequential masked matrix-vector product on cpu";
        }
 
        Status execute(const DispatchContext& ctx) override {
            TIME_PROFILE_SCOPE("cpu/mxv");
 
            auto t = ctx.task.template cast_safe<ScheduleTask_mxv_masked>();
 
            auto r           = t->r.template cast_safe<TVector<T>>();
            auto mask        = t->mask.template cast_safe<TVector<T>>();
            auto M           = t->M.template cast_safe<TMatrix<T>>();
            auto v           = t->v.template cast_safe<TVector<T>>();
            auto op_multiply = t->op_multiply.template cast_safe<TOpBinary<T, T, T>>();
            auto op_add      = t->op_add.template cast_safe<TOpBinary<T, T, T>>();
            auto op_select   = t->op_select.template cast_safe<TOpSelect<T>>();
            auto init        = t->init.template cast_safe<TScalar<T>>();
 
            const uint DM       = M->get_n_rows();
            const T    sum_init = init->get_value();
 
            r->validate_wd(FormatVector::CpuDense);
            mask->validate_rw(FormatVector::CpuDense);
            v->validate_rw(FormatVector::CpuDense);
            M->validate_rw(FormatMatrix::CpuLil);
 
            CpuDenseVec<T>*       p_dense_r    = r->template get<CpuDenseVec<T>>();
            const CpuDenseVec<T>* p_dense_mask = mask->template get<CpuDenseVec<T>>();
            const CpuDenseVec<T>* p_dense_v    = v->template get<CpuDenseVec<T>>();
            const CpuLil<T>*      p_lil_M      = M->template get<CpuLil<T>>();
            auto                  early_exit   = t->get_desc_or_default()->get_early_exit();
 
            auto& func_multiply = op_multiply->function;
            auto& func_add      = op_add->function;
            auto& func_select   = op_select->function;
 
            for (uint i = 0; i < DM; ++i) {
                T sum = sum_init;
 
                if (func_select(p_dense_mask->Ax[i])) {
                    const auto& row = p_lil_M->Ar[i];
 
                    for (const auto& j_x : row) {
                        const uint j = j_x.first;
                        sum          = func_add(sum, func_multiply(j_x.second, p_dense_v->Ax[j]));
 
                        if ((sum != sum_init) && early_exit) break;
                    }
                }
 
                p_dense_r->Ax[i] = sum;
            }
 
            return Status::Ok;
        }
    };
 
}// namespace spla
 
#endif//SPLA_CPU_MXV_HPP