cpu_v_eadd.hpp

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#ifndef SPLA_CPU_V_EADD_HPP
#define SPLA_CPU_V_EADD_HPP
 
#include <schedule/schedule_tasks.hpp>
 
#include <core/dispatcher.hpp>
#include <core/registry.hpp>
#include <core/top.hpp>
#include <core/tscalar.hpp>
#include <core/ttype.hpp>
#include <core/tvector.hpp>
 
namespace spla {
 
    template<typename T>
    class Algo_v_eadd_cpu final : public RegistryAlgo {
    public:
        ~Algo_v_eadd_cpu() override = default;
 
        std::string get_name() override {
            return "v_eadd";
        }
 
        std::string get_description() override {
            return "sequential element-wise add vector operation";
        }
 
        Status execute(const DispatchContext& ctx) override {
            auto                t = ctx.task.template cast_safe<ScheduleTask_v_eadd>();
            ref_ptr<TVector<T>> u = t->u.template cast_safe<TVector<T>>();
            ref_ptr<TVector<T>> v = t->v.template cast_safe<TVector<T>>();
 
            if (u->is_valid(FormatVector::CpuCoo) && v->is_valid(FormatVector::CpuCoo)) {
                return execute_spNsp(ctx);
            }
            if (u->is_valid(FormatVector::CpuDense) && v->is_valid(FormatVector::CpuDense)) {
                return execute_dnNdn(ctx);
            }
 
            return execute_spNsp(ctx);
        }
 
    private:
        Status execute_spNsp(const DispatchContext& ctx) {
            TIME_PROFILE_SCOPE("cpu/vector_eadd_spNsp");
 
            auto                        t  = ctx.task.template cast_safe<ScheduleTask_v_eadd>();
            ref_ptr<TVector<T>>         r  = t->r.template cast_safe<TVector<T>>();
            ref_ptr<TVector<T>>         u  = t->u.template cast_safe<TVector<T>>();
            ref_ptr<TVector<T>>         v  = t->v.template cast_safe<TVector<T>>();
            ref_ptr<TOpBinary<T, T, T>> op = t->op.template cast_safe<TOpBinary<T, T, T>>();
 
            r->validate_wd(FormatVector::CpuCoo);
            u->validate_rw(FormatVector::CpuCoo);
            v->validate_rw(FormatVector::CpuCoo);
 
            CpuCooVec<T>*       p_r      = r->template get<CpuCooVec<T>>();
            const CpuCooVec<T>* p_u      = u->template get<CpuCooVec<T>>();
            const CpuCooVec<T>* p_v      = v->template get<CpuCooVec<T>>();
            const auto&         function = op->function;
 
            const T u_fill_value = u->get_fill_value();
            const T v_fill_value = v->get_fill_value();
 
            assert(p_r->Ax.empty());
 
            const auto u_count = p_u->values;
            const auto v_count = p_v->values;
            uint       u_iter  = 0;
            uint       v_iter  = 0;
 
            while (u_iter < u_count && v_iter < v_count) {
                if (p_u->Ai[u_iter] < p_v->Ai[v_iter]) {
                    p_r->Ai.push_back(p_u->Ai[u_iter]);
                    p_r->Ax.push_back(function(p_u->Ax[u_iter], v_fill_value));
                    u_iter += 1;
                } else if (p_v->Ai[v_iter] < p_u->Ai[u_iter]) {
                    p_r->Ai.push_back(p_v->Ai[v_iter]);
                    p_r->Ax.push_back(function(u_fill_value, p_v->Ax[v_iter]));
                    v_iter += 1;
                } else {
                    p_r->Ai.push_back(p_u->Ai[u_iter]);
                    p_r->Ax.push_back(function(p_u->Ax[u_iter], p_v->Ax[v_iter]));
                    u_iter += 1;
                    v_iter += 1;
                }
                p_r->values += 1;
            }
            while (u_iter < u_count) {
                p_r->Ai.push_back(p_u->Ai[u_iter]);
                p_r->Ax.push_back(function(p_u->Ax[u_iter], v_fill_value));
                u_iter += 1;
                p_r->values += 1;
            }
            while (v_iter < v_count) {
                p_r->Ai.push_back(p_v->Ai[v_iter]);
                p_r->Ax.push_back(function(u_fill_value, p_v->Ax[v_iter]));
                v_iter += 1;
                p_r->values += 1;
            }
 
            return Status::Ok;
        }
        Status execute_dnNdn(const DispatchContext& ctx) {
            TIME_PROFILE_SCOPE("cpu/vector_eadd_dnNdn");
 
            auto                        t  = ctx.task.template cast_safe<ScheduleTask_v_eadd>();
            ref_ptr<TVector<T>>         r  = t->r.template cast_safe<TVector<T>>();
            ref_ptr<TVector<T>>         u  = t->u.template cast_safe<TVector<T>>();
            ref_ptr<TVector<T>>         v  = t->v.template cast_safe<TVector<T>>();
            ref_ptr<TOpBinary<T, T, T>> op = t->op.template cast_safe<TOpBinary<T, T, T>>();
 
            r->validate_wd(FormatVector::CpuDense);
            u->validate_rw(FormatVector::CpuDense);
            v->validate_rw(FormatVector::CpuDense);
 
            auto*       p_r      = r->template get<CpuDenseVec<T>>();
            const auto* p_u      = u->template get<CpuDenseVec<T>>();
            const auto* p_v      = v->template get<CpuDenseVec<T>>();
            const auto& function = op->function;
 
            const uint N = r->get_n_rows();
 
            for (uint i = 0; i < N; i++) {
                p_r->Ax[i] = function(p_u->Ax[i], p_v->Ax[i]);
            }
 
            return Status::Ok;
        }
    };
 
}// namespace spla
 
#endif//SPLA_CPU_V_EADD_HPP