CPULauncher.h

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// -                        Open3D: www.open3d.org                            -
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// The MIT License (MIT)
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// Copyright (c) 2018 www.open3d.org
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#pragma once

#include <cassert>
#include <vector>

#include "open3d/core/AdvancedIndexing.h"
#include "open3d/core/Indexer.h"
#include "open3d/core/Tensor.h"
#include "open3d/core/kernel/ParallelUtil.h"
#include "open3d/utility/Console.h"

namespace open3d {
namespace core {
namespace kernel {

class CPULauncher {
public:
    template <typename func_t>
    static void LaunchIndexFillKernel(const Indexer& indexer,
                                      func_t element_kernel) {
#pragma omp parallel for schedule(static)
        for (int64_t workload_idx = 0; workload_idx < indexer.NumWorkloads();
             ++workload_idx) {
            element_kernel(indexer.GetInputPtr(0, workload_idx), workload_idx);
        }
    }

    template <typename func_t>
    static void LaunchUnaryEWKernel(const Indexer& indexer,
                                    func_t element_kernel) {
#pragma omp parallel for schedule(static)
        for (int64_t workload_idx = 0; workload_idx < indexer.NumWorkloads();
             ++workload_idx) {
            element_kernel(indexer.GetInputPtr(0, workload_idx),
                           indexer.GetOutputPtr(workload_idx));
        }
    }

    template <typename func_t>
    static void LaunchBinaryEWKernel(const Indexer& indexer,
                                     func_t element_kernel) {
#pragma omp parallel for schedule(static)
        for (int64_t workload_idx = 0; workload_idx < indexer.NumWorkloads();
             ++workload_idx) {
            element_kernel(indexer.GetInputPtr(0, workload_idx),
                           indexer.GetInputPtr(1, workload_idx),
                           indexer.GetOutputPtr(workload_idx));
        }
    }

    template <typename func_t>
    static void LaunchAdvancedIndexerKernel(const AdvancedIndexer& indexer,
                                            func_t element_kernel) {
#pragma omp parallel for schedule(static)
        for (int64_t workload_idx = 0; workload_idx < indexer.NumWorkloads();
             ++workload_idx) {
            element_kernel(indexer.GetInputPtr(workload_idx),
                           indexer.GetOutputPtr(workload_idx));
        }
    }

    template <typename scalar_t, typename func_t>
    static void LaunchReductionKernelSerial(const Indexer& indexer,
                                            func_t element_kernel) {
        for (int64_t workload_idx = 0; workload_idx < indexer.NumWorkloads();
             ++workload_idx) {
            element_kernel(indexer.GetInputPtr(0, workload_idx),
                           indexer.GetOutputPtr(workload_idx));
        }
    }

    template <typename scalar_t, typename func_t>
    static void LaunchReductionKernelTwoPass(const Indexer& indexer,
                                             func_t element_kernel,
                                             scalar_t identity) {
        if (indexer.NumOutputElements() > 1) {
            utility::LogError(
                    "Internal error: two-pass reduction only works for "
                    "single-output reduction ops.");
        }
        int64_t num_workloads = indexer.NumWorkloads();
        int64_t num_threads = GetMaxThreads();
        int64_t workload_per_thread =
                (num_workloads + num_threads - 1) / num_threads;
        std::vector<scalar_t> thread_results(num_threads, identity);

#pragma omp parallel for schedule(static)
        for (int64_t thread_idx = 0; thread_idx < num_threads; ++thread_idx) {
            int64_t start = thread_idx * workload_per_thread;
            int64_t end = std::min(start + workload_per_thread, num_workloads);
            for (int64_t workload_idx = start; workload_idx < end;
                 ++workload_idx) {
                element_kernel(indexer.GetInputPtr(0, workload_idx),
                               &thread_results[thread_idx]);
            }
        }
        void* output_ptr = indexer.GetOutputPtr(0);
        for (int64_t thread_idx = 0; thread_idx < num_threads; ++thread_idx) {
            element_kernel(&thread_results[thread_idx], output_ptr);
        }
    }

    template <typename scalar_t, typename func_t>
    static void LaunchReductionParallelDim(const Indexer& indexer,
                                           func_t element_kernel) {
        // Prefers outer dimension >= num_threads.
        const int64_t* indexer_shape = indexer.GetMasterShape();
        const int64_t num_dims = indexer.NumDims();
        int64_t num_threads = GetMaxThreads();

        // Init best_dim as the outer-most non-reduction dim.
        int64_t best_dim = num_dims - 1;
        while (best_dim >= 0 && indexer.IsReductionDim(best_dim)) {
            best_dim--;
        }
        for (int64_t dim = best_dim; dim >= 0 && !indexer.IsReductionDim(dim);
             --dim) {
            if (indexer_shape[dim] >= num_threads) {
                best_dim = dim;
                break;
            } else if (indexer_shape[dim] > indexer_shape[best_dim]) {
                best_dim = dim;
            }
        }
        if (best_dim == -1) {
            utility::LogError(
                    "Internal error: all dims are reduction dims, use "
                    "LaunchReductionKernelTwoPass instead.");
        }

#pragma omp parallel for schedule(static)
        for (int64_t i = 0; i < indexer_shape[best_dim]; ++i) {
            Indexer sub_indexer(indexer);
            sub_indexer.ShrinkDim(best_dim, i, 1);
            LaunchReductionKernelSerial<scalar_t>(sub_indexer, element_kernel);
        }
    }

    template <typename func_t>
    static void LaunchGeneralKernel(int64_t n, func_t element_kernel) {
#pragma omp parallel for schedule(static)
        for (int64_t workload_idx = 0; workload_idx < n; ++workload_idx) {
            element_kernel(workload_idx);
        }
    }
};

}  // namespace kernel
}  // namespace core
}  // namespace open3d