Multi stream pyramid

CMakeLists.txt

@@ -184,3 +184,8 @@ endif()
 if(EXISTS ${CMAKE_SOURCE_DIR}/samples/CMakeLists.txt)
     add_subdirectory(samples)
 endif()
+
+# add apps if available
+if(EXISTS ${CMAKE_SOURCE_DIR}/apps/CMakeLists.txt)
+    add_subdirectory(apps)
+endif()

LICENSE

@@ -1,3 +1,4 @@
+Copyright (c) 2020, University of Erlangen-Nuremberg
 Copyright (c) 2014, Saarland University
 Copyright (c) 2012, University of Erlangen-Nuremberg
 Copyright (c) 2012, Siemens AG

README.md

@@ -1,3 +1,8 @@
+This is a fork of the [Hipacc](http://hipacc-lang.org) project, with primarily experiential features:
+* Asynchronous runtime APIs
+* Multi-stream implementation for multiresolution filters in CUDA
+
+
 # Hipacc
 A domain-specific language and compiler for image processing
 

_clang-format

@@ -0,0 +1,121 @@
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+  - Q_FOREACH
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+UseTab:          Never
+...
+

apps/6_Multiresolution_Filters/Laplacian_Pyramid_Encoding/src/main.cpp

@@ -0,0 +1,212 @@
+//
+// Copyright (c) 2020, University of Erlangen-Nuremberg
+// Copyright (c) 2012, University of Erlangen-Nuremberg
+// Copyright (c) 2012, Siemens AG
+// All rights reserved.
+//
+// Redistribution and use in source and binary forms, with or without
+// modification, are permitted provided that the following conditions are met:
+//
+// 1. Redistributions of source code must retain the above copyright notice, this
+//    list of conditions and the following disclaimer.
+// 2. Redistributions in binary form must reproduce the above copyright notice,
+//    this list of conditions and the following disclaimer in the documentation
+//    and/or other materials provided with the distribution.
+//
+// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+// ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+// WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+// DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+// ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+// (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+// LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+// ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+//
+
+#include "hipacc.hpp"
+#include <iostream>
+#include <hipacc_helper.hpp>
+
+#define SIZE_X 3
+#define SIZE_Y 3
+#define WIDTH 1024
+#define HEIGHT 1024
+
+using namespace hipacc;
+using namespace hipacc::math;
+
+
+class Gaussian : public Kernel<char> {
+  private:
+    Accessor<char> &input;
+    Mask<float> &mask;
+
+  public:
+    Gaussian(IterationSpace<char> &iter, Accessor<char> &input,
+             Mask<float> &mask)
+          : Kernel(iter), input(input), mask(mask) {
+        add_accessor(&input);
+    }
+
+    void kernel() {
+        output() = convolve(mask, Reduce::SUM, [&] () {
+            return input(mask) * mask();
+        });
+    }
+
+    void _operatePyramidReduce() {}
+};
+
+class DifferenceOfGaussian : public Kernel<char> {
+  private:
+    Accessor<char> &input1;
+    Accessor<char> &input2;
+
+  public:
+    DifferenceOfGaussian(IterationSpace<char> &iter, Accessor<char> &input1,
+                         Accessor<char> &input2)
+          : Kernel(iter), input1(input1), input2(input2) {
+        add_accessor(&input1);
+        add_accessor(&input2);
+    }
+
+    void kernel() {
+        output() = input1() - input2();
+    }
+
+    void _operatePyramidFilter() {}
+};
+
+class Blend : public Kernel<char> {
+  private:
+    Accessor<char> &input1;
+    Accessor<char> &input2;
+
+  public:
+    Blend(IterationSpace<char> &iter, Accessor<char> &input1,
+          Accessor<char> &input2)
+        : Kernel(iter), input1(input1), input2(input2) {
+      add_accessor(&input1);
+      add_accessor(&input2);
+    }
+
+    void kernel() {
+        output() = (short)input1() + (short)input2() / 2;
+    }
+
+    void _operatePyramidExpand() {}
+};
+
+
+/*************************************************************************
+ * Main function                                                         *
+ *************************************************************************/
+int main(int argc, const char **argv) {
+    const int width = WIDTH;
+    const int height = HEIGHT;
+    const int size_x = SIZE_X;
+    const int size_y = SIZE_Y;
+    float timing = 0;
+
+    // only filter kernel sizes 3x3, 5x5, and 7x7 implemented
+    if (size_x != size_y || !(size_x == 3 || size_x == 5 || size_x == 7)) {
+        std::cout << "Wrong filter kernel size. "
+                  << "Currently supported values: 3x3, 5x5, and 7x7!"
+                  << std::endl;
+        exit(EXIT_FAILURE);
+    }
+
+    // convolution filter mask
+    const float coef[SIZE_Y][SIZE_X] = {
+#if SIZE_X == 3
+        { 0.057118f, 0.124758f, 0.057118f },
+        { 0.124758f, 0.272496f, 0.124758f },
+        { 0.057118f, 0.124758f, 0.057118f }
+#endif
+#if SIZE_X == 5
+        { 0.005008f, 0.017300f, 0.026151f, 0.017300f, 0.005008f },
+        { 0.017300f, 0.059761f, 0.090339f, 0.059761f, 0.017300f },
+        { 0.026151f, 0.090339f, 0.136565f, 0.090339f, 0.026151f },
+        { 0.017300f, 0.059761f, 0.090339f, 0.059761f, 0.017300f },
+        { 0.005008f, 0.017300f, 0.026151f, 0.017300f, 0.005008f }
+#endif
+#if SIZE_X == 7
+        { 0.000841f, 0.003010f, 0.006471f, 0.008351f, 0.006471f, 0.003010f, 0.000841f },
+        { 0.003010f, 0.010778f, 0.023169f, 0.029902f, 0.023169f, 0.010778f, 0.003010f },
+        { 0.006471f, 0.023169f, 0.049806f, 0.064280f, 0.049806f, 0.023169f, 0.006471f },
+        { 0.008351f, 0.029902f, 0.064280f, 0.082959f, 0.064280f, 0.029902f, 0.008351f },
+        { 0.006471f, 0.023169f, 0.049806f, 0.064280f, 0.049806f, 0.023169f, 0.006471f },
+        { 0.003010f, 0.010778f, 0.023169f, 0.029902f, 0.023169f, 0.010778f, 0.003010f },
+        { 0.000841f, 0.003010f, 0.006471f, 0.008351f, 0.006471f, 0.003010f, 0.000841f }
+#endif
+    };
+
+    // host memory for random generated image of width x height pixels
+    char *input = new char[width * height];
+    for (int y = 0; y < height; ++y) {
+      for (int x = 0; x < width; ++x) {
+        input[y * width + x] = (char)((y * width + x) % 19);
+      }
+    }
+
+    std::cout << "Calculating Hipacc Gaussian Laplacian pyramid ..." << std::endl;
+
+    //************************************************************************//
+
+    // input and output image of width x height pixels
+    Image<char> gaus(width, height);
+    Image<char> lap(width, height);
+    Mask<float> mask(coef);
+
+    const int depth = 10;
+    Pyramid<char> pgaus(gaus, depth);
+    Pyramid<char> plap(lap, depth);
+
+    gaus = input;
+    traverse(pgaus, plap, [&] () {
+        if (!pgaus.is_top_level()) {
+            // construct Gaussian pyramid
+            BoundaryCondition<char> bound(pgaus(-1), mask, Boundary::CLAMP);
+            Accessor<char> acc1(bound);
+            IterationSpace<char> iter1(pgaus(0));
+            Gaussian blur(iter1, acc1, mask);
+            blur.execute();
+
+            // construct Laplacian pyramid
+            Accessor<char> acc3(pgaus(-1));
+            Accessor<char> acc4(pgaus(0), Interpolate::LF);
+            IterationSpace<char> iter3(plap(-1));
+            DifferenceOfGaussian DoG(iter3, acc3, acc4);
+            DoG.execute();
+        }
+
+        traverse();
+
+        // collapse pyramids
+        if (!pgaus.is_bottom_level()) {
+            // blend final output image from Laplacian pyramid
+            Accessor<char> acc3(plap(1), Interpolate::LF);
+            Accessor<char> acc4(plap(0));
+            IterationSpace<char> iter2(plap(0));
+            Blend blend(iter2, acc3, acc4);
+            blend.execute();
+        }
+    });
+
+    // get pointer to result data
+    char *output = lap.data();
+
+    //************************************************************************//
+
+    // convert to uchar for visualization
+    for (int p = 0; p < width*height; ++p) {
+        output[p] = (char)(output[p] + 127);
+    }
+
+    // free memory
+    delete[] input;
+
+    return EXIT_SUCCESS;
+}

apps/CMakeLists.txt

@@ -0,0 +1,19 @@
+file(GLOB SAMPLE_DIRS RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_SOURCE_DIR}/[0-9]*)
+foreach(SAMPLE_DIR IN LISTS SAMPLE_DIRS)
+    # install samples
+    install(DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/${SAMPLE_DIR} DESTINATION samples COMPONENT samples)
+
+    # deploy build tool for samples
+    file(GLOB SAMPLES RELATIVE ${CMAKE_CURRENT_SOURCE_DIR}/${SAMPLE_DIR} ${CMAKE_CURRENT_SOURCE_DIR}/${SAMPLE_DIR}/*)
+    foreach(SAMPLE IN LISTS SAMPLES)
+        if(IS_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/${SAMPLE_DIR}/${SAMPLE})
+            if(UNIX)
+                install(FILES ${CMAKE_BINARY_DIR}/samples/buildtools/unix/Makefile DESTINATION samples/${SAMPLE_DIR}/${SAMPLE} COMPONENT samples)
+            elseif(WIN32)
+                file(GLOB NMAKE_FILES ${CMAKE_CURRENT_SOURCE_DIR}/buildtools/nmake/*)
+                file(GLOB VS2015_FILES ${CMAKE_CURRENT_SOURCE_DIR}/buildtools/vs2015/*)
+                install(FILES ${NMAKE_FILES} ${VS2015_FILES} DESTINATION samples/${SAMPLE_DIR}/${SAMPLE} COMPONENT samples)
+            endif()
+        endif()
+    endforeach()
+endforeach()

apps/readme.txt

@@ -0,0 +1,7 @@
+Application folder for new samples
+
+How to enable stream-based code generation for apps:
+1 follow the standard getting started guide at (https://hipacc-lang.org/install.html)
+2 the apps should be copied automatically to the same directory as samples  
+3 enable the Hipacc flag `-use-stream n` in cuda.conf
+4 `-use-stream 1` for single-stream and `-use-stream 2` for multi-stream