cl_v_assign.hpp

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#ifndef SPLA_CL_V_ASSIGN_HPP
#define SPLA_CL_V_ASSIGN_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>
 
#include <opencl/cl_formats.hpp>
#include <opencl/cl_program_builder.hpp>
#include <opencl/generated/auto_vector_assign.hpp>
 
#include <sstream>
 
namespace spla {
 
    template<typename T>
    class Algo_v_assign_masked_cl final : public RegistryAlgo {
    public:
        ~Algo_v_assign_masked_cl() override = default;
 
        std::string get_name() override {
            return "v_assign_masked";
        }
 
        std::string get_description() override {
            return "parallel vector masked assignment on opencl device";
        }
 
        Status execute(const DispatchContext& ctx) override {
            auto                t    = ctx.task.template cast_safe<ScheduleTask_v_assign_masked>();
            ref_ptr<TVector<T>> mask = t->mask.template cast_safe<TVector<T>>();
 
            if (mask->is_valid(FormatVector::AccCoo))
                return execute_sp2dn(ctx);
            if (mask->is_valid(FormatVector::AccDense))
                return execute_dn2dn(ctx);
 
            return execute_sp2dn(ctx);
        }
 
    private:
        Status execute_dn2dn(const DispatchContext& ctx) {
            TIME_PROFILE_SCOPE("opencl/vector_assign_dense2dense");
 
            auto t = ctx.task.template cast_safe<ScheduleTask_v_assign_masked>();
 
            auto r         = t->r.template cast_safe<TVector<T>>();
            auto mask      = t->mask.template cast_safe<TVector<T>>();
            auto value     = t->value.template cast_safe<TScalar<T>>();
            auto op_assign = t->op_assign.template cast_safe<TOpBinary<T, T, T>>();
            auto op_select = t->op_select.template cast_safe<TOpSelect<T>>();
 
            r->validate_rwd(FormatVector::AccDense);
            mask->validate_rw(FormatVector::AccDense);
 
            std::shared_ptr<CLProgram> program;
            if (!ensure_kernel(op_assign, op_select, program)) return Status::CompilationError;
 
            auto*       p_cl_r_dense    = r->template get<CLDenseVec<T>>();
            const auto* p_cl_mask_dense = mask->template get<CLDenseVec<T>>();
            auto*       p_cl_acc        = get_acc_cl();
            auto&       queue           = p_cl_acc->get_queue_default();
 
            auto kernel_dense_to_dense = program->make_kernel("assign_dense_to_dense");
            kernel_dense_to_dense.setArg(0, p_cl_r_dense->Ax);
            kernel_dense_to_dense.setArg(1, p_cl_mask_dense->Ax);
            kernel_dense_to_dense.setArg(2, value->get_value());
            kernel_dense_to_dense.setArg(3, r->get_n_rows());
 
            uint n_groups_to_dispatch = div_up_clamp(r->get_n_rows(), m_block_size, 1, 256);
 
            cl::NDRange global(m_block_size * n_groups_to_dispatch);
            cl::NDRange local(m_block_size);
            queue.enqueueNDRangeKernel(kernel_dense_to_dense, cl::NDRange(), global, local);
 
            return Status::Ok;
        }
 
        Status execute_sp2dn(const DispatchContext& ctx) {
            TIME_PROFILE_SCOPE("opencl/vector_assign_sparse2dense");
 
            auto t = ctx.task.template cast_safe<ScheduleTask_v_assign_masked>();
 
            auto r         = t->r.template cast_safe<TVector<T>>();
            auto mask      = t->mask.template cast_safe<TVector<T>>();
            auto value     = t->value.template cast_safe<TScalar<T>>();
            auto op_assign = t->op_assign.template cast_safe<TOpBinary<T, T, T>>();
            auto op_select = t->op_select.template cast_safe<TOpSelect<T>>();
 
            r->validate_rwd(FormatVector::AccDense);
            mask->validate_rw(FormatVector::AccCoo);
 
            auto*       p_cl_r_dense  = r->template get<CLDenseVec<T>>();
            const auto* p_cl_mask_coo = mask->template get<CLCooVec<T>>();
            auto*       p_cl_acc      = get_acc_cl();
            auto&       queue         = p_cl_acc->get_queue_default();
 
            if (p_cl_mask_coo->values == 0) {
                LOG_MSG(Status::Ok, "nothing to do");
                return Status::Ok;
            }
 
            std::shared_ptr<CLProgram> program;
            if (!ensure_kernel(op_assign, op_select, program)) return Status::CompilationError;
 
            auto kernel_sparse_to_dense = program->make_kernel("assign_sparse_to_dense");
            kernel_sparse_to_dense.setArg(0, p_cl_r_dense->Ax);
            kernel_sparse_to_dense.setArg(1, p_cl_mask_coo->Ai);
            kernel_sparse_to_dense.setArg(2, p_cl_mask_coo->Ax);
            kernel_sparse_to_dense.setArg(3, value->get_value());
            kernel_sparse_to_dense.setArg(4, p_cl_mask_coo->values);
 
            uint n_groups_to_dispatch = div_up_clamp(p_cl_mask_coo->values, m_block_size, 1, 256);
 
            cl::NDRange global(m_block_size * n_groups_to_dispatch);
            cl::NDRange local(m_block_size);
            queue.enqueueNDRangeKernel(kernel_sparse_to_dense, cl::NDRange(), global, local);
 
            return Status::Ok;
        }
 
        bool ensure_kernel(const ref_ptr<TOpBinary<T, T, T>>& op_assign, const ref_ptr<TOpSelect<T>>& op_select, std::shared_ptr<CLProgram>& program) {
            m_block_size = get_acc_cl()->get_default_wgs();
 
            CLProgramBuilder program_builder;
            program_builder
                    .set_name("vector_assign")
                    .add_type("TYPE", get_ttype<T>().template as<Type>())
                    .add_op("OP_BINARY", op_assign.template as<OpBinary>())
                    .add_op("OP_SELECT", op_select.template as<OpSelect>())
                    .set_source(source_vector_assign)
                    .acquire();
 
            program = program_builder.get_program();
 
            return true;
        }
 
    private:
        uint m_block_size = 0;
    };
 
}// namespace spla
 
#endif//SPLA_CL_V_ASSIGN_HPP