arrayfire · WilliamTambellini · Mar 11, 2019 · Mar 13, 2019 · Mar 13, 2019 · Mar 28, 2019
diff --git a/examples/machine_learning/CMakeLists.txt b/examples/machine_learning/CMakeLists.txt
@@ -11,6 +11,7 @@ project(ArrayFire-Example-Linear-Algebra
  LANGUAGES CXX)

 find_package(ArrayFire)
+find_package(Threads)

 add_definitions("-DASSETS_DIR=\"${ASSETS_DIR}\"")

@@ -41,7 +42,8 @@ if(ArrayFire_CPU_FOUND)

  # Neural Network example
  add_executable(neural_network_cpu neural_network.cpp)
-  target_link_libraries(neural_network_cpu ArrayFire::afcpu)
+  set_target_properties(neural_network_cpu PROPERTIES CXX_STANDARD 11)
+  target_link_libraries(neural_network_cpu ArrayFire::afcpu Threads::Threads)

  # Preceptron example
  add_executable(perceptron_cpu perceptron.cpp)
@@ -76,7 +78,9 @@ if(ArrayFire_CUDA_FOUND)
  target_link_libraries(naive_bayes_cuda ArrayFire::afcuda)

  add_executable(neural_network_cuda neural_network.cpp)
-  target_link_libraries(neural_network_cuda ArrayFire::afcuda)
+  set_target_properties(neural_network_cuda PROPERTIES CXX_STANDARD 11)
+  target_link_libraries(neural_network_cuda
+    ArrayFire::afcuda  Threads::Threads)

  add_executable(perceptron_cuda perceptron.cpp)
  target_link_libraries(perceptron_cuda ArrayFire::afcuda)
@@ -108,7 +112,9 @@ if(ArrayFire_OpenCL_FOUND)
  target_link_libraries(naive_bayes_opencl ArrayFire::afopencl)

  add_executable(neural_network_opencl neural_network.cpp)
-  target_link_libraries(neural_network_opencl ArrayFire::afopencl)
+  set_target_properties(neural_network_opencl PROPERTIES CXX_STANDARD 11)
+  target_link_libraries(neural_network_opencl
+    ArrayFire::afopencl Threads::Threads)

  add_executable(perceptron_opencl perceptron.cpp)
  target_link_libraries(perceptron_opencl ArrayFire::afopencl)

diff --git a/examples/machine_learning/neural_network.cpp b/examples/machine_learning/neural_network.cpp
@@ -11,7 +11,9 @@
 #include <math.h>
 #include <stdio.h>
 #include <af/util.h>
+#include <list>
 #include <string>
+#include <thread>
 #include <vector>
 #include "mnist_common.h"

@@ -155,14 +157,15 @@ double ann::train(const array &input, const array &target, double alpha,

        if (verbose) {
            if ((i + 1) % 10 == 0)
-                printf("Epoch: %4d, Error: %0.4f\n", i + 1, err);
+                printf("Device: %d, Epoch: %4d, Error: %0.4f\n",
+                       af::getDevice(), i + 1, err);
        }
    }
    return err;
 }

 int ann_demo(bool console, int perc) {
-    printf("** ArrayFire ANN Demo **\n\n");
+    printf("Starting training on device %d ...\n\n", af::getDevice());

    array train_images, test_images;
    array train_target, test_target;
@@ -214,16 +217,16 @@ int ann_demo(bool console, int perc) {
    af::sync();
    double test_time = timer::stop() / 100;

-    printf("\nTraining set:\n");
-    printf("Accuracy on training data: %2.2f\n",
-           accuracy(train_output, train_target));
+    printf("\nAccuracy on training data: %2.2f device: %d\n",
+           accuracy(train_output, train_target), af::getDevice());

-    printf("\nTest set:\n");
-    printf("Accuracy on testing  data: %2.2f\n",
-           accuracy(test_output, test_target));
+    printf("Accuracy on testing  data: %2.2f device: %d\n",
+           accuracy(test_output, test_target), af::getDevice());

-    printf("\nTraining time: %4.4lf s\n", train_time);
-    printf("Prediction time: %4.4lf s\n\n", test_time);
+    printf("\nTraining time on device %d: %4.4lf s\n", af::getDevice(),
+           train_time);
+    printf("Prediction time on device %d: %4.4lf s\n\n", af::getDevice(),
+           test_time);

    if (!console) {
        // Get 20 random test images.
@@ -234,16 +237,48 @@ int ann_demo(bool console, int perc) {
    return 0;
 }

+class learner {
+   public:
+    void learn(const unsigned d, const bool console, const int perc) {
+        printf("Starting new learner thread on device %d\n", d);
+        af::setDevice(d);
+        af::array r = af::randu(10);
+        ann_demo(console, perc);
+    }
+};
+
 int main(int argc, char **argv) {
    int device   = argc > 1 ? atoi(argv[1]) : 0;
    bool console = argc > 2 ? argv[2][0] == '-' : false;
-    int perc     = argc > 3 ? atoi(argv[3]) : 60;
-
+    int perc = argc > 3 ? atoi(argv[3]) : 60;  // percentage training/test data
+    af::info();
+    const unsigned dc = af::getDeviceCount();
+    printf("** ArrayFire ANN Demo **\n\n");
+    printf("Usage: %s deviceId console percentage\n", argv[0]);
+    printf(
+        "- deviceId: either a device id (>= 0). If -1, 1 training will be "
+        "triggered per device\n");
+    printf("- console: console mode\n");
+    printf(
+        "- percentage: percent of training/testing data, default 60\% used for "
+        "training\n");
+    af::info();
+
+    std::list<learner> ls;
+    std::list<std::thread> ts;
    try {
-        af::setDevice(device);
-        af::info();
-        return ann_demo(console, perc);
-
+        if (device < 0) {
+            for (unsigned i = 0; i < dc; ++i) {
+                ls.push_back(learner());
+                ts.push_back(
+                    std::thread(&learner::learn, ls.back(), i, console, perc));
+            }
+        } else {
+            ls.push_back(learner());
+            ts.push_back(
+                std::thread(&learner::learn, ls.back(), device, console, perc));
+        }
+        for (auto &t : ts) t.join();
    } catch (af::exception &ae) { std::cerr << ae.what() << std::endl; }

    return 0;