mirror of
https://gitlab.kitware.com/vtk/vtk-m
synced 2024-07-06 07:17:25 +00:00
dcdda3065a
In order to compile the contour filter more efficiently, we split the contour filter into two separate translation units, corresponding to the new filters ContourFlyingEdges and ContourMarchingCells. The API for Contour filter is left totally unchanged, and tries to use flying edges if the dataset is structured and uniform. All three contour filters inherit from the `AbstractContour` class, providing utility methods used in the implementations.
1112 lines
36 KiB
C++
1112 lines
36 KiB
C++
//==========================================================================
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// Copyright (c) Kitware, Inc.
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// All rights reserved.
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// See LICENSE.txt for details.
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//
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// This software is distributed WITHOUT ANY WARRANTY; without even
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// the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
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// PURPOSE. See the above copyright notice for more information.
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//==========================================================================
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#include "Benchmarker.h"
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#include <cstddef>
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#include <random>
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#include <sstream>
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#include <unordered_map>
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#include <vtkm/ImplicitFunction.h>
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#include <vtkm/Particle.h>
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#include <vtkm/cont/Algorithm.h>
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#include <vtkm/cont/ArrayCopy.h>
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#include <vtkm/cont/BoundsCompute.h>
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#include <vtkm/cont/DataSet.h>
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#include <vtkm/cont/FieldRangeCompute.h>
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#include <vtkm/cont/Initialize.h>
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#include <vtkm/cont/Logging.h>
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#include <vtkm/cont/RuntimeDeviceTracker.h>
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#include <vtkm/cont/Timer.h>
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#include <vtkm/cont/internal/OptionParser.h>
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#include <vtkm/filter/contour/Contour.h>
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#include <vtkm/filter/contour/Slice.h>
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#include <vtkm/filter/flow/Streamline.h>
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#include <vtkm/filter/geometry_refinement/Tetrahedralize.h>
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#include <vtkm/filter/geometry_refinement/Tube.h>
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#include <vtkm/filter/vector_analysis/Gradient.h>
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#include <vtkm/rendering/Actor.h>
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#include <vtkm/rendering/CanvasRayTracer.h>
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#include <vtkm/rendering/MapperRayTracer.h>
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#include <vtkm/rendering/MapperVolume.h>
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#include <vtkm/rendering/MapperWireframer.h>
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#include <vtkm/rendering/Scene.h>
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#include <vtkm/rendering/View3D.h>
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#include <vtkm/source/PerlinNoise.h>
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namespace
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{
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const vtkm::Id DEFAULT_DATASET_DIM = 128;
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const vtkm::Id DEFAULT_IMAGE_SIZE = 1024;
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// Hold configuration state (e.g. active device):
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vtkm::cont::InitializeResult Config;
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// Input dataset dimensions:
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vtkm::Id DataSetDim;
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// Image size:
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vtkm::Id ImageSize;
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// The input datasets we'll use on the filters:
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vtkm::cont::DataSet InputDataSet;
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vtkm::cont::PartitionedDataSet PartitionedInputDataSet;
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// The point scalars to use:
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std::string PointScalarsName;
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// The point vectors to use:
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std::string PointVectorsName;
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// Global counters for number of cycles
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// These are globals because google benchmarks restarts the test for every
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// repetition when using --benchmark_repetitions
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// Additionlly, we need this global flag for when not doing repetitions,
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// as benchmark will repeatedly drop in and out of the measured function
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// and report the number of iterations for the last run of the function.
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// Thus, we'll have way more output images than what the iteration number
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// would lead you to believe (maybe fixed in > 1.7 with warmup time specifier)
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bool benchmark_repetitions = false;
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inline void hash_combine(std::size_t& vtkmNotUsed(seed)) {}
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template <typename T, typename... Rest>
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inline void hash_combine(std::size_t& seed, const T& v, Rest... rest)
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{
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std::hash<T> hasher;
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seed ^= hasher(v) + 0x9e3779b9 + (seed << 6) + (seed >> 2);
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hash_combine(seed, rest...);
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}
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std::unordered_map<size_t, int> bench_cycles;
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enum class RenderingMode
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{
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None = 0,
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Mesh = 1,
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RayTrace = 2,
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Volume = 3,
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};
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std::vector<vtkm::cont::DataSet> ExtractDataSets(const vtkm::cont::PartitionedDataSet& partitions)
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{
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return partitions.GetPartitions();
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}
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// Mirrors ExtractDataSet(ParitionedDataSet), to keep code simple at use sites
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std::vector<vtkm::cont::DataSet> ExtractDataSets(vtkm::cont::DataSet& dataSet)
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{
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return std::vector<vtkm::cont::DataSet>{ dataSet };
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}
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void BuildInputDataSet(uint32_t cycle, bool isStructured, bool isMultiBlock, vtkm::Id dim)
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{
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vtkm::cont::PartitionedDataSet partitionedInputDataSet;
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vtkm::cont::DataSet inputDataSet;
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PointScalarsName = "perlinnoise";
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PointVectorsName = "perlinnoisegrad";
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// Generate uniform dataset(s)
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vtkm::source::PerlinNoise noise;
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noise.SetPointDimensions({ dim, dim, dim });
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noise.SetSeed(static_cast<vtkm::IdComponent>(cycle));
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if (isMultiBlock)
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{
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for (auto i = 0; i < 2; ++i)
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{
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for (auto j = 0; j < 2; ++j)
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{
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for (auto k = 0; k < 2; ++k)
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{
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noise.SetOrigin({ static_cast<vtkm::FloatDefault>(i),
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static_cast<vtkm::FloatDefault>(j),
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static_cast<vtkm::FloatDefault>(k) });
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const auto dataset = noise.Execute();
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partitionedInputDataSet.AppendPartition(dataset);
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}
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}
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}
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}
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else
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{
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inputDataSet = noise.Execute();
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}
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// Generate Perln Noise Gradient point vector field
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vtkm::filter::vector_analysis::Gradient gradientFilter;
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gradientFilter.SetActiveField(PointScalarsName, vtkm::cont::Field::Association::Points);
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gradientFilter.SetComputePointGradient(true);
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gradientFilter.SetOutputFieldName(PointVectorsName);
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gradientFilter.SetFieldsToPass(
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vtkm::filter::FieldSelection(vtkm::filter::FieldSelection::Mode::All));
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if (isMultiBlock)
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{
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partitionedInputDataSet = gradientFilter.Execute(partitionedInputDataSet);
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}
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else
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{
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inputDataSet = gradientFilter.Execute(inputDataSet);
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}
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// Run Tetrahedralize filter to convert uniform dataset(s) into unstructured ones
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if (!isStructured)
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{
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vtkm::filter::geometry_refinement::Tetrahedralize destructizer;
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destructizer.SetFieldsToPass(
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vtkm::filter::FieldSelection(vtkm::filter::FieldSelection::Mode::All));
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if (isMultiBlock)
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{
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partitionedInputDataSet = destructizer.Execute(partitionedInputDataSet);
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}
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else
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{
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inputDataSet = destructizer.Execute(inputDataSet);
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}
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}
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// Release execution resources to simulate in-situ workload, where the data is
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// not present in the execution environment
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std::vector<vtkm::cont::DataSet> dataSets =
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isMultiBlock ? ExtractDataSets(partitionedInputDataSet) : ExtractDataSets(inputDataSet);
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for (auto& dataSet : dataSets)
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{
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dataSet.GetCellSet().ReleaseResourcesExecution();
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dataSet.GetCoordinateSystem().ReleaseResourcesExecution();
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dataSet.GetField(PointScalarsName).ReleaseResourcesExecution();
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dataSet.GetField(PointVectorsName).ReleaseResourcesExecution();
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}
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PartitionedInputDataSet = partitionedInputDataSet;
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InputDataSet = inputDataSet;
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}
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vtkm::rendering::Canvas* RenderDataSets(const std::vector<vtkm::cont::DataSet>& dataSets,
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RenderingMode mode,
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std::string fieldName)
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{
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vtkm::rendering::Scene scene;
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vtkm::cont::ColorTable colorTable("inferno");
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if (mode == RenderingMode::Volume)
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{
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colorTable.AddPointAlpha(0.0f, 0.03f);
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colorTable.AddPointAlpha(1.0f, 0.01f);
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}
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for (auto& dataSet : dataSets)
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{
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scene.AddActor(vtkm::rendering::Actor(dataSet.GetCellSet(),
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dataSet.GetCoordinateSystem(),
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dataSet.GetField(fieldName),
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colorTable));
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}
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auto bounds = std::accumulate(dataSets.begin(),
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dataSets.end(),
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vtkm::Bounds(),
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[=](const vtkm::Bounds& val, const vtkm::cont::DataSet& partition) {
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return val + vtkm::cont::BoundsCompute(partition);
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});
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vtkm::Vec3f_64 totalExtent(bounds.X.Length(), bounds.Y.Length(), bounds.Z.Length());
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vtkm::Float64 mag = vtkm::Magnitude(totalExtent);
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vtkm::Normalize(totalExtent);
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// setup a camera and point it to towards the center of the input data
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vtkm::rendering::Camera camera;
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camera.SetFieldOfView(60.f);
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camera.ResetToBounds(bounds);
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camera.SetLookAt(totalExtent * (mag * .5f));
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camera.SetViewUp(vtkm::make_Vec(0.f, 1.f, 0.f));
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camera.SetPosition(totalExtent * (mag * 1.5f));
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vtkm::rendering::CanvasRayTracer canvas(ImageSize, ImageSize);
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auto mapper = [=]() -> std::unique_ptr<vtkm::rendering::Mapper> {
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switch (mode)
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{
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case RenderingMode::Mesh:
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{
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return std::unique_ptr<vtkm::rendering::Mapper>(new vtkm::rendering::MapperWireframer());
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}
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case RenderingMode::RayTrace:
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{
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return std::unique_ptr<vtkm::rendering::Mapper>(new vtkm::rendering::MapperRayTracer());
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}
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case RenderingMode::Volume:
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{
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return std::unique_ptr<vtkm::rendering::Mapper>(new vtkm::rendering::MapperVolume());
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}
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case RenderingMode::None:
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default:
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{
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return std::unique_ptr<vtkm::rendering::Mapper>(new vtkm::rendering::MapperRayTracer());
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}
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}
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}();
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vtkm::rendering::View3D view(scene,
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*mapper,
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canvas,
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camera,
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vtkm::rendering::Color(0.8f, 0.8f, 0.6f),
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vtkm::rendering::Color(0.2f, 0.4f, 0.2f));
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view.Paint();
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return view.GetCanvas().NewCopy();
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}
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void WriteToDisk(const vtkm::rendering::Canvas& canvas,
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RenderingMode mode,
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std::string bench,
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bool isStructured,
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bool isMultiBlock,
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uint32_t cycle)
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{
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std::ostringstream nameBuilder;
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nameBuilder << "insitu_" << bench << "_"
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<< "cycle_" << cycle << "_" << (isStructured ? "structured_" : "unstructured_")
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<< (isMultiBlock ? "multi_" : "single_")
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<< (mode == RenderingMode::Mesh ? "mesh"
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: (mode == RenderingMode::Volume ? "volume" : "ray"))
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<< ".png";
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canvas.SaveAs(nameBuilder.str());
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}
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template <typename DataSetType>
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DataSetType RunContourHelper(vtkm::filter::contour::Contour& filter,
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vtkm::Id numIsoVals,
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const DataSetType& input)
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{
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// Set up some equally spaced contours, with the min/max slightly inside the
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// scalar range:
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const vtkm::Range scalarRange =
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vtkm::cont::FieldRangeCompute(input, PointScalarsName).ReadPortal().Get(0);
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const auto step = scalarRange.Length() / static_cast<vtkm::Float64>(numIsoVals + 1);
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const auto minIsoVal = scalarRange.Min + (step * 0.5f);
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filter.SetNumberOfIsoValues(numIsoVals);
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for (vtkm::Id i = 0; i < numIsoVals; ++i)
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{
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filter.SetIsoValue(i, minIsoVal + (step * static_cast<vtkm::Float64>(i)));
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}
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return filter.Execute(input);
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}
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void BenchContour(::benchmark::State& state)
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{
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const vtkm::cont::DeviceAdapterId device = Config.Device;
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const vtkm::Id numIsoVals = static_cast<vtkm::Id>(state.range(0));
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const bool isStructured = static_cast<bool>(state.range(1));
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const bool isMultiBlock = static_cast<bool>(state.range(2));
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const RenderingMode renderAlgo = static_cast<RenderingMode>(state.range(3));
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vtkm::cont::Timer totalTimer{ device };
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vtkm::cont::Timer filterTimer{ device };
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vtkm::cont::Timer renderTimer{ device };
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vtkm::cont::Timer writeTimer{ device };
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size_t hash_val = 0;
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hash_combine(hash_val, std::string("BenchContour"), isStructured, isMultiBlock, renderAlgo);
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int* cycles = &(bench_cycles[hash_val]);
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if (!benchmark_repetitions)
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*cycles = 0;
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for (auto _ : state)
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{
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(void)_;
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totalTimer.Start();
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// Disable the benchmark timers for the updating/creation of the datasets
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state.PauseTiming(); // Stop timers.
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vtkm::cont::Timer inputGenTimer{ device };
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inputGenTimer.Start();
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BuildInputDataSet(*cycles, isStructured, isMultiBlock, DataSetDim);
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inputGenTimer.Stop();
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vtkm::filter::contour::Contour filter;
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filter.SetActiveField(PointScalarsName, vtkm::cont::Field::Association::Points);
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filter.SetMergeDuplicatePoints(true);
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filter.SetGenerateNormals(true);
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filter.SetComputeFastNormals(true);
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state.ResumeTiming(); // And resume timers.
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filterTimer.Start();
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std::vector<vtkm::cont::DataSet> dataSets;
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if (isMultiBlock)
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{
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auto input = PartitionedInputDataSet;
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auto result = RunContourHelper(filter, numIsoVals, input);
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dataSets = ExtractDataSets(result);
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}
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else
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{
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auto input = InputDataSet;
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auto result = RunContourHelper(filter, numIsoVals, input);
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dataSets = ExtractDataSets(result);
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}
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filterTimer.Stop();
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renderTimer.Start();
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auto canvas = RenderDataSets(dataSets, renderAlgo, PointScalarsName);
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renderTimer.Stop();
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writeTimer.Start();
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WriteToDisk(*canvas, renderAlgo, "contour", isStructured, isMultiBlock, *cycles);
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writeTimer.Stop();
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totalTimer.Stop();
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(*cycles)++;
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state.SetIterationTime(totalTimer.GetElapsedTime());
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state.counters.insert(
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{ { "InputGenTime", static_cast<uint32_t>(inputGenTimer.GetElapsedTime() * 1000) },
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{ "FilterTime", static_cast<uint32_t>(filterTimer.GetElapsedTime() * 1000) },
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{ "RenderTime", static_cast<uint32_t>(renderTimer.GetElapsedTime() * 1000) },
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{ "WriteTime", static_cast<uint32_t>(writeTimer.GetElapsedTime() * 1000) } });
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}
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}
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void BenchContourGenerator(::benchmark::internal::Benchmark* bm)
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{
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bm->ArgNames({ "NIsos", "IsStructured", "IsMultiBlock", "RenderingMode" });
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std::vector<uint32_t> isStructureds{ false, true };
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std::vector<uint32_t> isMultiBlocks{ false, true };
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std::vector<RenderingMode> renderingModes{ RenderingMode::RayTrace };
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for (auto& isStructured : isStructureds)
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{
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for (auto& isMultiBlock : isMultiBlocks)
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{
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for (auto& mode : renderingModes)
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{
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size_t hash_val = 0;
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hash_combine(hash_val, std::string("BenchContour"), isStructured, isMultiBlock, mode);
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auto search = bench_cycles.find(hash_val);
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// If we can't find the hash, or we're not doing repetitions, reset to 0
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if (search == bench_cycles.end())
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bench_cycles[hash_val] = 0;
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bm->Args({ 10, isStructured, isMultiBlock, static_cast<int>(mode) });
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}
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}
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}
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}
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VTKM_BENCHMARK_APPLY(BenchContour, BenchContourGenerator);
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void MakeRandomSeeds(vtkm::Id seedCount,
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vtkm::Bounds& bounds,
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vtkm::cont::ArrayHandle<vtkm::Particle>& seeds)
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{
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std::default_random_engine generator(static_cast<vtkm::UInt32>(255));
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vtkm::FloatDefault zero(0), one(1);
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std::uniform_real_distribution<vtkm::FloatDefault> distribution(zero, one);
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std::vector<vtkm::Particle> points;
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points.resize(0);
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for (vtkm::Id i = 0; i < seedCount; i++)
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{
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vtkm::FloatDefault rx = distribution(generator);
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vtkm::FloatDefault ry = distribution(generator);
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vtkm::FloatDefault rz = distribution(generator);
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vtkm::Vec3f p;
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p[0] = static_cast<vtkm::FloatDefault>(bounds.X.Min + rx * bounds.X.Length());
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p[1] = static_cast<vtkm::FloatDefault>(bounds.Y.Min + ry * bounds.Y.Length());
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p[2] = static_cast<vtkm::FloatDefault>(bounds.Z.Min + rz * bounds.Z.Length());
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points.push_back(vtkm::Particle(p, static_cast<vtkm::Id>(i)));
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}
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vtkm::cont::ArrayHandle<vtkm::Particle> tmp =
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vtkm::cont::make_ArrayHandle(points, vtkm::CopyFlag::Off);
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vtkm::cont::ArrayCopy(tmp, seeds);
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}
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vtkm::Id GetNumberOfPoints(const vtkm::cont::DataSet& input)
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{
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return input.GetCoordinateSystem().GetNumberOfPoints();
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}
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vtkm::Id GetNumberOfPoints(const vtkm::cont::PartitionedDataSet& input)
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{
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return input.GetPartition(0).GetCoordinateSystem().GetNumberOfPoints();
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}
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void AddField(vtkm::cont::DataSet& input,
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std::string fieldName,
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std::vector<vtkm::FloatDefault>& field)
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{
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input.AddPointField(fieldName, field);
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}
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void AddField(vtkm::cont::PartitionedDataSet& input,
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std::string fieldName,
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std::vector<vtkm::FloatDefault>& field)
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{
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for (auto i = 0; i < input.GetNumberOfPartitions(); ++i)
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{
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auto partition = input.GetPartition(i);
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AddField(partition, fieldName, field);
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input.ReplacePartition(i, partition);
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}
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}
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template <typename DataSetType>
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DataSetType RunStreamlinesHelper(vtkm::filter::flow::Streamline& filter, const DataSetType& input)
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{
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auto dataSetBounds = vtkm::cont::BoundsCompute(input);
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vtkm::cont::ArrayHandle<vtkm::Particle> seedArray;
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MakeRandomSeeds(100, dataSetBounds, seedArray);
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filter.SetSeeds(seedArray);
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auto result = filter.Execute(input);
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auto numPoints = GetNumberOfPoints(result);
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std::vector<vtkm::FloatDefault> colorMap(
|
|
static_cast<std::vector<vtkm::FloatDefault>::size_type>(numPoints));
|
|
for (std::vector<vtkm::FloatDefault>::size_type i = 0; i < colorMap.size(); i++)
|
|
{
|
|
colorMap[i] = static_cast<vtkm::FloatDefault>(i);
|
|
}
|
|
|
|
AddField(result, "pointvar", colorMap);
|
|
return result;
|
|
}
|
|
|
|
void BenchStreamlines(::benchmark::State& state)
|
|
{
|
|
const vtkm::cont::DeviceAdapterId device = Config.Device;
|
|
|
|
const bool isStructured = static_cast<bool>(state.range(0));
|
|
const bool isMultiBlock = static_cast<bool>(state.range(1));
|
|
const RenderingMode renderAlgo = static_cast<RenderingMode>(state.range(2));
|
|
|
|
vtkm::cont::Timer totalTimer{ device };
|
|
vtkm::cont::Timer filterTimer{ device };
|
|
vtkm::cont::Timer renderTimer{ device };
|
|
vtkm::cont::Timer writeTimer{ device };
|
|
|
|
size_t hash_val = 0;
|
|
hash_combine(hash_val, std::string("BenchStreamlines"), isStructured, isMultiBlock, renderAlgo);
|
|
|
|
int* cycles = &(bench_cycles[hash_val]);
|
|
if (!benchmark_repetitions)
|
|
*cycles = 0;
|
|
|
|
for (auto _ : state)
|
|
{
|
|
(void)_;
|
|
totalTimer.Start();
|
|
|
|
// Disable the benchmark timers for the updating/creation of the datasets
|
|
state.PauseTiming(); // Stop timers.
|
|
vtkm::cont::Timer inputGenTimer{ device };
|
|
inputGenTimer.Start();
|
|
BuildInputDataSet(*cycles, isStructured, isMultiBlock, DataSetDim);
|
|
inputGenTimer.Stop();
|
|
|
|
vtkm::filter::flow::Streamline streamline;
|
|
streamline.SetStepSize(0.1f);
|
|
streamline.SetNumberOfSteps(1000);
|
|
streamline.SetActiveField(PointVectorsName);
|
|
state.ResumeTiming(); // And resume timers.
|
|
|
|
filterTimer.Start();
|
|
|
|
std::vector<vtkm::cont::DataSet> dataSets;
|
|
if (isMultiBlock)
|
|
{
|
|
auto input = PartitionedInputDataSet;
|
|
auto result = RunStreamlinesHelper(streamline, input);
|
|
dataSets = ExtractDataSets(result);
|
|
}
|
|
else
|
|
{
|
|
auto input = InputDataSet;
|
|
auto result = RunStreamlinesHelper(streamline, input);
|
|
dataSets = ExtractDataSets(result);
|
|
}
|
|
filterTimer.Stop();
|
|
|
|
renderTimer.Start();
|
|
auto canvas = RenderDataSets(dataSets, renderAlgo, "pointvar");
|
|
renderTimer.Stop();
|
|
|
|
writeTimer.Start();
|
|
WriteToDisk(*canvas, renderAlgo, "streamlines", isStructured, isMultiBlock, *cycles);
|
|
writeTimer.Stop();
|
|
|
|
totalTimer.Stop();
|
|
|
|
(*cycles)++;
|
|
|
|
state.SetIterationTime(totalTimer.GetElapsedTime());
|
|
state.counters.insert(
|
|
{ { "InputGenTime", static_cast<uint32_t>(inputGenTimer.GetElapsedTime() * 1000) },
|
|
{ "FilterTime", static_cast<uint32_t>(filterTimer.GetElapsedTime() * 1000) },
|
|
{ "RenderTime", static_cast<uint32_t>(renderTimer.GetElapsedTime() * 1000) },
|
|
{ "WriteTime", static_cast<uint32_t>(writeTimer.GetElapsedTime() * 1000) } });
|
|
}
|
|
}
|
|
|
|
void BenchStreamlinesGenerator(::benchmark::internal::Benchmark* bm)
|
|
{
|
|
bm->ArgNames({ "IsStructured", "IsMultiBlock", "RenderingMode" });
|
|
|
|
std::vector<uint32_t> isStructureds{ false, true };
|
|
std::vector<uint32_t> isMultiBlocks{ false, true };
|
|
std::vector<RenderingMode> renderingModes{ RenderingMode::Mesh };
|
|
for (auto& isStructured : isStructureds)
|
|
{
|
|
for (auto& isMultiBlock : isMultiBlocks)
|
|
{
|
|
for (auto& mode : renderingModes)
|
|
{
|
|
size_t hash_val = 0;
|
|
hash_combine(hash_val, std::string("BenchStreamlines"), isStructured, isMultiBlock, mode);
|
|
auto search = bench_cycles.find(hash_val);
|
|
// If we can't find the hash, or we're not doing repetitions, reset to 0
|
|
if (search == bench_cycles.end())
|
|
bench_cycles[hash_val] = 0;
|
|
bm->Args({ isStructured, isMultiBlock, static_cast<int>(mode) });
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
VTKM_BENCHMARK_APPLY(BenchStreamlines, BenchStreamlinesGenerator);
|
|
|
|
vtkm::Vec3f GetSlicePlaneOrigin(const bool isMultiBlock)
|
|
{
|
|
if (isMultiBlock)
|
|
{
|
|
auto data = PartitionedInputDataSet;
|
|
vtkm::Bounds global;
|
|
global = data.GetPartition(0).GetCoordinateSystem().GetBounds();
|
|
for (auto i = 1; i < data.GetNumberOfPartitions(); ++i)
|
|
{
|
|
auto dataset = data.GetPartition(i);
|
|
vtkm::Bounds bounds = dataset.GetCoordinateSystem().GetBounds();
|
|
global.X.Min = vtkm::Min(global.X.Min, bounds.X.Min);
|
|
global.Y.Min = vtkm::Min(global.Y.Min, bounds.Y.Min);
|
|
global.Z.Min = vtkm::Min(global.Z.Min, bounds.Z.Min);
|
|
global.X.Max = vtkm::Min(global.X.Max, bounds.X.Max);
|
|
global.Y.Max = vtkm::Min(global.Y.Max, bounds.Y.Max);
|
|
global.Z.Max = vtkm::Min(global.Z.Max, bounds.Z.Max);
|
|
}
|
|
return vtkm::Vec3f{ static_cast<vtkm::FloatDefault>((global.X.Max - global.X.Min) / 2.),
|
|
static_cast<vtkm::FloatDefault>((global.Y.Max - global.Y.Min) / 2.),
|
|
static_cast<vtkm::FloatDefault>((global.Z.Max - global.Z.Min) / 2.) };
|
|
}
|
|
else
|
|
{
|
|
auto data = InputDataSet;
|
|
vtkm::Bounds bounds = data.GetCoordinateSystem().GetBounds();
|
|
return vtkm::Vec3f{ static_cast<vtkm::FloatDefault>((bounds.X.Max - bounds.X.Min) / 2.),
|
|
static_cast<vtkm::FloatDefault>((bounds.Y.Max - bounds.Y.Min) / 2.),
|
|
static_cast<vtkm::FloatDefault>((bounds.Z.Max - bounds.Z.Min) / 2.) };
|
|
}
|
|
}
|
|
|
|
void BenchSlice(::benchmark::State& state)
|
|
{
|
|
const vtkm::cont::DeviceAdapterId device = Config.Device;
|
|
|
|
const bool isStructured = static_cast<bool>(state.range(0));
|
|
const bool isMultiBlock = static_cast<bool>(state.range(1));
|
|
const RenderingMode renderAlgo = static_cast<RenderingMode>(state.range(2));
|
|
|
|
vtkm::filter::contour::Slice filter;
|
|
|
|
vtkm::cont::Timer totalTimer{ device };
|
|
vtkm::cont::Timer filterTimer{ device };
|
|
vtkm::cont::Timer renderTimer{ device };
|
|
vtkm::cont::Timer writeTimer{ device };
|
|
|
|
size_t hash_val = 0;
|
|
hash_combine(hash_val, std::string("BenchSlice"), isStructured, isMultiBlock, renderAlgo);
|
|
|
|
int* cycles = &(bench_cycles[hash_val]);
|
|
if (!benchmark_repetitions)
|
|
*cycles = 0;
|
|
|
|
for (auto _ : state)
|
|
{
|
|
(void)_;
|
|
totalTimer.Start();
|
|
|
|
// Disable the benchmark timers for the updating/creation of the datasets
|
|
state.PauseTiming(); // Stop timers.
|
|
vtkm::cont::Timer inputGenTimer{ device };
|
|
inputGenTimer.Start();
|
|
BuildInputDataSet(*cycles, isStructured, isMultiBlock, DataSetDim);
|
|
inputGenTimer.Stop();
|
|
state.ResumeTiming(); // And resume timers.
|
|
|
|
filterTimer.Start();
|
|
std::vector<vtkm::cont::DataSet> dataSets;
|
|
if (isMultiBlock)
|
|
{
|
|
auto input = PartitionedInputDataSet;
|
|
vtkm::Vec3f origin = GetSlicePlaneOrigin(isMultiBlock);
|
|
// Set-up implicit function
|
|
vtkm::Plane plane(origin, vtkm::Plane::Vector{ 1, 1, 1 });
|
|
filter.SetImplicitFunction(plane);
|
|
auto result = filter.Execute(input);
|
|
dataSets = ExtractDataSets(result);
|
|
}
|
|
else
|
|
{
|
|
auto input = InputDataSet;
|
|
vtkm::Vec3f origin = GetSlicePlaneOrigin(isMultiBlock);
|
|
// Set-up implicit function
|
|
vtkm::Plane plane(origin, vtkm::Plane::Vector{ 1, 1, 1 });
|
|
filter.SetImplicitFunction(plane);
|
|
auto result = filter.Execute(input);
|
|
dataSets = ExtractDataSets(result);
|
|
}
|
|
filterTimer.Stop();
|
|
|
|
renderTimer.Start();
|
|
auto canvas = RenderDataSets(dataSets, renderAlgo, PointScalarsName);
|
|
renderTimer.Stop();
|
|
|
|
writeTimer.Start();
|
|
WriteToDisk(*canvas, renderAlgo, "slice", isStructured, isMultiBlock, *cycles);
|
|
writeTimer.Stop();
|
|
|
|
totalTimer.Stop();
|
|
|
|
(*cycles)++;
|
|
|
|
state.SetIterationTime(totalTimer.GetElapsedTime());
|
|
state.counters.insert(
|
|
{ { "InputGenTime", static_cast<uint32_t>(inputGenTimer.GetElapsedTime() * 1000) },
|
|
{ "FilterTime", static_cast<uint32_t>(filterTimer.GetElapsedTime() * 1000) },
|
|
{ "RenderTime", static_cast<uint32_t>(renderTimer.GetElapsedTime() * 1000) },
|
|
{ "WriteTime", static_cast<uint32_t>(writeTimer.GetElapsedTime() * 1000) } });
|
|
}
|
|
}
|
|
|
|
void BenchSliceGenerator(::benchmark::internal::Benchmark* bm)
|
|
{
|
|
bm->ArgNames({ "IsStructured", "IsMultiBlock", "RenderingMode" });
|
|
|
|
std::vector<uint32_t> isStructureds{ false, true };
|
|
std::vector<uint32_t> isMultiBlocks{ false, true };
|
|
std::vector<RenderingMode> renderingModes{ RenderingMode::RayTrace };
|
|
for (auto& isStructured : isStructureds)
|
|
{
|
|
for (auto& isMultiBlock : isMultiBlocks)
|
|
{
|
|
for (auto& mode : renderingModes)
|
|
{
|
|
size_t hash_val = 0;
|
|
hash_combine(hash_val, std::string("BenchSlice"), isStructured, isMultiBlock, mode);
|
|
auto search = bench_cycles.find(hash_val);
|
|
// If we can't find the hash, or we're not doing repetitions, reset to 0
|
|
if (search == bench_cycles.end())
|
|
bench_cycles[hash_val] = 0;
|
|
bm->Args({ isStructured, isMultiBlock, static_cast<int>(mode) });
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
VTKM_BENCHMARK_APPLY(BenchSlice, BenchSliceGenerator);
|
|
|
|
void BenchMeshRendering(::benchmark::State& state)
|
|
{
|
|
const vtkm::cont::DeviceAdapterId device = Config.Device;
|
|
|
|
const bool isStructured = static_cast<bool>(state.range(0));
|
|
const bool isMultiBlock = static_cast<bool>(state.range(1));
|
|
|
|
vtkm::cont::Timer inputGenTimer{ device };
|
|
vtkm::cont::Timer renderTimer{ device };
|
|
vtkm::cont::Timer writeTimer{ device };
|
|
|
|
vtkm::cont::Timer totalTimer{ device };
|
|
|
|
size_t hash_val = 0;
|
|
hash_combine(hash_val, std::string("BenchMeshRendering"), isStructured, isMultiBlock);
|
|
|
|
int* cycles = &(bench_cycles[hash_val]);
|
|
if (!benchmark_repetitions)
|
|
*cycles = 0;
|
|
|
|
for (auto _ : state)
|
|
{
|
|
(void)_;
|
|
|
|
totalTimer.Start();
|
|
|
|
// Disable the benchmark timers for the updating/creation of the datasets
|
|
state.PauseTiming(); // Stop timers.
|
|
inputGenTimer.Start();
|
|
BuildInputDataSet(*cycles, isStructured, isMultiBlock, DataSetDim);
|
|
inputGenTimer.Stop();
|
|
state.ResumeTiming(); // And resume timers.
|
|
|
|
std::vector<vtkm::cont::DataSet> dataSets =
|
|
isMultiBlock ? ExtractDataSets(PartitionedInputDataSet) : ExtractDataSets(InputDataSet);
|
|
|
|
renderTimer.Start();
|
|
auto canvas = RenderDataSets(dataSets, RenderingMode::Mesh, PointScalarsName);
|
|
renderTimer.Stop();
|
|
|
|
writeTimer.Start();
|
|
WriteToDisk(*canvas, RenderingMode::Mesh, "mesh", isStructured, isMultiBlock, *cycles);
|
|
writeTimer.Stop();
|
|
|
|
totalTimer.Stop();
|
|
|
|
(*cycles)++;
|
|
|
|
state.SetIterationTime(totalTimer.GetElapsedTime());
|
|
state.counters.insert(
|
|
{ { "InputGenTime", static_cast<uint32_t>(inputGenTimer.GetElapsedTime() * 1000) },
|
|
{ "FilterTime", 0 },
|
|
{ "RenderTime", static_cast<uint32_t>(renderTimer.GetElapsedTime() * 1000) },
|
|
{ "WriteTime", static_cast<uint32_t>(writeTimer.GetElapsedTime() * 1000) } });
|
|
}
|
|
}
|
|
|
|
void BenchMeshRenderingGenerator(::benchmark::internal::Benchmark* bm)
|
|
{
|
|
bm->ArgNames({ "IsStructured", "IsMultiBlock" });
|
|
|
|
std::vector<uint32_t> isStructureds{ false, true };
|
|
std::vector<uint32_t> isMultiBlocks{ false, true };
|
|
for (auto& isStructured : isStructureds)
|
|
{
|
|
for (auto& isMultiBlock : isMultiBlocks)
|
|
{
|
|
size_t hash_val = 0;
|
|
hash_combine(hash_val, std::string("BenchMeshRendering"), isStructured, isMultiBlock);
|
|
auto search = bench_cycles.find(hash_val);
|
|
// If we can't find the hash, or we're not doing repetitions, reset to 0
|
|
if (search == bench_cycles.end())
|
|
bench_cycles[hash_val] = 0;
|
|
bm->Args({ isStructured, isMultiBlock });
|
|
}
|
|
}
|
|
}
|
|
|
|
VTKM_BENCHMARK_APPLY(BenchMeshRendering, BenchMeshRenderingGenerator);
|
|
|
|
void BenchVolumeRendering(::benchmark::State& state)
|
|
{
|
|
const vtkm::cont::DeviceAdapterId device = Config.Device;
|
|
|
|
const bool isStructured = true;
|
|
const bool isMultiBlock = static_cast<bool>(state.range(0));
|
|
|
|
vtkm::cont::Timer totalTimer{ device };
|
|
vtkm::cont::Timer renderTimer{ device };
|
|
vtkm::cont::Timer writeTimer{ device };
|
|
|
|
size_t hash_val = 0;
|
|
hash_combine(hash_val, std::string("BenchVolumeRendering"), isMultiBlock);
|
|
|
|
int* cycles = &(bench_cycles[hash_val]);
|
|
if (!benchmark_repetitions)
|
|
*cycles = 0;
|
|
|
|
for (auto _ : state)
|
|
{
|
|
(void)_;
|
|
totalTimer.Start();
|
|
|
|
// Disable the benchmark timers for the updating/creation of the datasets
|
|
state.PauseTiming(); // Stop timers.
|
|
vtkm::cont::Timer inputGenTimer{ device };
|
|
inputGenTimer.Start();
|
|
BuildInputDataSet(*cycles, isStructured, isMultiBlock, DataSetDim);
|
|
inputGenTimer.Stop();
|
|
state.ResumeTiming(); // And resume timers.
|
|
|
|
renderTimer.Start();
|
|
std::vector<vtkm::cont::DataSet> dataSets =
|
|
isMultiBlock ? ExtractDataSets(PartitionedInputDataSet) : ExtractDataSets(InputDataSet);
|
|
auto canvas = RenderDataSets(dataSets, RenderingMode::Volume, PointScalarsName);
|
|
renderTimer.Stop();
|
|
|
|
writeTimer.Start();
|
|
WriteToDisk(*canvas, RenderingMode::Volume, "volume", isStructured, isMultiBlock, *cycles);
|
|
writeTimer.Stop();
|
|
|
|
totalTimer.Stop();
|
|
|
|
(*cycles)++;
|
|
|
|
state.SetIterationTime(totalTimer.GetElapsedTime());
|
|
state.counters.insert(
|
|
{ { "InputGenTime", static_cast<uint32_t>(inputGenTimer.GetElapsedTime() * 1000) },
|
|
{ "FilterTime", 0 },
|
|
{ "RenderTime", static_cast<uint32_t>(renderTimer.GetElapsedTime() * 1000) },
|
|
{ "WriteTime", static_cast<uint32_t>(writeTimer.GetElapsedTime() * 1000) } });
|
|
}
|
|
}
|
|
|
|
void BenchVolumeRenderingGenerator(::benchmark::internal::Benchmark* bm)
|
|
{
|
|
bm->ArgNames({ "IsMultiBlock" });
|
|
|
|
std::vector<uint32_t> isMultiBlocks{ false };
|
|
for (auto& isMultiBlock : isMultiBlocks)
|
|
{
|
|
size_t hash_val = 0;
|
|
hash_combine(hash_val, std::string("BenchVolumeRendering"), isMultiBlock);
|
|
auto search = bench_cycles.find(hash_val);
|
|
// If we can't find the hash, or we're not doing repetitions, reset to 0
|
|
if (search == bench_cycles.end())
|
|
bench_cycles[hash_val] = 0;
|
|
bm->Args({ isMultiBlock });
|
|
}
|
|
}
|
|
|
|
VTKM_BENCHMARK_APPLY(BenchVolumeRendering, BenchVolumeRenderingGenerator);
|
|
|
|
struct Arg : vtkm::cont::internal::option::Arg
|
|
{
|
|
static vtkm::cont::internal::option::ArgStatus Number(
|
|
const vtkm::cont::internal::option::Option& option,
|
|
bool msg)
|
|
{
|
|
bool argIsNum = ((option.arg != nullptr) && (option.arg[0] != '\0'));
|
|
const char* c = option.arg;
|
|
while (argIsNum && (*c != '\0'))
|
|
{
|
|
argIsNum &= static_cast<bool>(std::isdigit(*c));
|
|
++c;
|
|
}
|
|
|
|
if (argIsNum)
|
|
{
|
|
return vtkm::cont::internal::option::ARG_OK;
|
|
}
|
|
else
|
|
{
|
|
if (msg)
|
|
{
|
|
std::cerr << "Option " << option.name << " requires a numeric argument." << std::endl;
|
|
}
|
|
|
|
return vtkm::cont::internal::option::ARG_ILLEGAL;
|
|
}
|
|
}
|
|
};
|
|
|
|
enum OptionIndex
|
|
{
|
|
UNKNOWN,
|
|
HELP,
|
|
DATASET_DIM,
|
|
IMAGE_SIZE,
|
|
};
|
|
|
|
void ParseBenchmarkOptions(int& argc, char** argv)
|
|
{
|
|
namespace option = vtkm::cont::internal::option;
|
|
|
|
std::vector<option::Descriptor> usage;
|
|
std::string usageHeader{ "Usage: " };
|
|
usageHeader.append(argv[0]);
|
|
usageHeader.append("[input data options] [benchmark options]");
|
|
usage.push_back({ UNKNOWN, 0, "", "", Arg::None, usageHeader.c_str() });
|
|
usage.push_back({ UNKNOWN, 0, "", "", Arg::None, "Input data options are:" });
|
|
usage.push_back({ HELP, 0, "h", "help", Arg::None, " -h, --help\tDisplay this help." });
|
|
usage.push_back({ UNKNOWN, 0, "", "", Arg::None, Config.Usage.c_str() });
|
|
usage.push_back({ DATASET_DIM,
|
|
0,
|
|
"s",
|
|
"size",
|
|
Arg::Number,
|
|
" -s, --size <N> \tSpecify dataset dimension and "
|
|
"dataset with NxNxN dimensions is created. "
|
|
"If not specified, N=128" });
|
|
usage.push_back({ IMAGE_SIZE,
|
|
0,
|
|
"i",
|
|
"image-size",
|
|
Arg::Number,
|
|
" -i, --image-size <N> \tSpecify size of the rendered image."
|
|
" The image is rendered as a square of size NxN. "
|
|
"If not specified, N=1024" });
|
|
usage.push_back({ 0, 0, nullptr, nullptr, nullptr, nullptr });
|
|
|
|
option::Stats stats(usage.data(), argc - 1, argv + 1);
|
|
std::unique_ptr<option::Option[]> options{ new option::Option[stats.options_max] };
|
|
std::unique_ptr<option::Option[]> buffer{ new option::Option[stats.buffer_max] };
|
|
option::Parser commandLineParse(usage.data(), argc - 1, argv + 1, options.get(), buffer.get());
|
|
|
|
if (options[HELP])
|
|
{
|
|
option::printUsage(std::cout, usage.data());
|
|
// Print google benchmark usage too
|
|
const char* helpstr = "--help";
|
|
char* tmpargv[] = { argv[0], const_cast<char*>(helpstr), nullptr };
|
|
int tmpargc = 2;
|
|
VTKM_EXECUTE_BENCHMARKS(tmpargc, tmpargv);
|
|
exit(0);
|
|
}
|
|
if (options[DATASET_DIM])
|
|
{
|
|
std::istringstream parse(options[DATASET_DIM].arg);
|
|
parse >> DataSetDim;
|
|
}
|
|
else
|
|
{
|
|
DataSetDim = DEFAULT_DATASET_DIM;
|
|
}
|
|
if (options[IMAGE_SIZE])
|
|
{
|
|
std::istringstream parse(options[IMAGE_SIZE].arg);
|
|
parse >> ImageSize;
|
|
}
|
|
else
|
|
{
|
|
ImageSize = DEFAULT_IMAGE_SIZE;
|
|
}
|
|
|
|
std::cerr << "Using data set dimensions = " << DataSetDim << std::endl;
|
|
std::cerr << "Using image size = " << ImageSize << "x" << ImageSize << std::endl;
|
|
|
|
// Now go back through the arg list and remove anything that is not in the list of
|
|
// unknown options or non-option arguments.
|
|
int destArg = 1;
|
|
// This is copy/pasted from vtkm::cont::Initialize(), should probably be abstracted eventually:
|
|
for (int srcArg = 1; srcArg < argc; ++srcArg)
|
|
{
|
|
std::string thisArg{ argv[srcArg] };
|
|
bool copyArg = false;
|
|
|
|
// Special case: "--" gets removed by optionparser but should be passed.
|
|
if (thisArg == "--")
|
|
{
|
|
copyArg = true;
|
|
}
|
|
for (const option::Option* opt = options[UNKNOWN]; !copyArg && opt != nullptr;
|
|
opt = opt->next())
|
|
{
|
|
if (thisArg == opt->name)
|
|
{
|
|
copyArg = true;
|
|
}
|
|
if ((opt->arg != nullptr) && (thisArg == opt->arg))
|
|
{
|
|
copyArg = true;
|
|
}
|
|
// Special case: optionparser sometimes removes a single "-" from an option
|
|
if (thisArg.substr(1) == opt->name)
|
|
{
|
|
copyArg = true;
|
|
}
|
|
}
|
|
for (int nonOpt = 0; !copyArg && nonOpt < commandLineParse.nonOptionsCount(); ++nonOpt)
|
|
{
|
|
if (thisArg == commandLineParse.nonOption(nonOpt))
|
|
{
|
|
copyArg = true;
|
|
}
|
|
}
|
|
if (copyArg)
|
|
{
|
|
if (destArg != srcArg)
|
|
{
|
|
argv[destArg] = argv[srcArg];
|
|
}
|
|
++destArg;
|
|
}
|
|
}
|
|
argc = destArg;
|
|
}
|
|
|
|
// Adding a const char* or std::string to a vector of char* is harder than it sounds.
|
|
void AddArg(int& argc, std::vector<char*>& args, const std::string newArg)
|
|
{
|
|
// This object will be deleted when the program exits
|
|
static std::vector<std::vector<char>> stringPool;
|
|
|
|
// Add a new vector of chars to the back of stringPool
|
|
stringPool.emplace_back();
|
|
std::vector<char>& newArgData = stringPool.back();
|
|
|
|
// Copy the string to the std::vector.
|
|
// Yes, something like malloc or strdup would be easier. But that would technically create
|
|
// a memory leak that could be reported by a memory analyzer. By copying this way, the
|
|
// memory will be deleted on program exit and no leak will be reported.
|
|
newArgData.resize(newArg.length() + 1);
|
|
std::copy(newArg.begin(), newArg.end(), newArgData.begin());
|
|
newArgData.back() = '\0'; // Don't forget the terminating null character.
|
|
|
|
// Add the argument to the list.
|
|
if (args.size() <= static_cast<std::size_t>(argc))
|
|
{
|
|
args.resize(static_cast<std::size_t>(argc + 1));
|
|
}
|
|
args[static_cast<std::size_t>(argc)] = newArgData.data();
|
|
|
|
++argc;
|
|
}
|
|
|
|
} // end anon namespace
|
|
|
|
int main(int argc, char* argv[])
|
|
{
|
|
auto opts = vtkm::cont::InitializeOptions::RequireDevice;
|
|
|
|
std::vector<char*> args(argv, argv + argc);
|
|
vtkm::bench::detail::InitializeArgs(&argc, args, opts);
|
|
|
|
// Parse VTK-m options
|
|
Config = vtkm::cont::Initialize(argc, args.data(), opts);
|
|
ParseBenchmarkOptions(argc, args.data());
|
|
|
|
// This opts chances when it is help
|
|
if (opts != vtkm::cont::InitializeOptions::None)
|
|
{
|
|
vtkm::cont::GetRuntimeDeviceTracker().ForceDevice(Config.Device);
|
|
}
|
|
|
|
bool benchmark_min_time = false;
|
|
bool benchmark_report_aggregates_only = false;
|
|
for (auto i = 0; i <= argc; i++)
|
|
if (!strncmp(args[i], "--benchmark_repetitions", 23))
|
|
benchmark_repetitions = true;
|
|
else if (!strncmp(args[i], "--benchmark_min_time", 20))
|
|
benchmark_min_time = true;
|
|
else if (!strncmp(args[i], "--benchmark_report_aggregates_only", 34))
|
|
benchmark_report_aggregates_only = true;
|
|
|
|
// If repetitions are explicitly set without also specifying a minimum_time,
|
|
// force the minimum time to be fairly small so that in all likelyhood, benchmarks
|
|
// will only run 1 iteration for each test
|
|
//
|
|
// And, for good measure, only output the accumulated statistics
|
|
if (benchmark_repetitions)
|
|
{
|
|
if (!benchmark_min_time)
|
|
{
|
|
AddArg(argc, args, "--benchmark_min_time=0.00000001");
|
|
}
|
|
|
|
if (!benchmark_report_aggregates_only)
|
|
{
|
|
AddArg(argc, args, "--benchmark_report_aggregates_only=true");
|
|
}
|
|
}
|
|
|
|
VTKM_EXECUTE_BENCHMARKS(argc, args.data());
|
|
}
|