Index: test-suite/trunk/MultiSource/Benchmarks/Rodinia/CMakeLists.txt
===================================================================
--- test-suite/trunk/MultiSource/Benchmarks/Rodinia/CMakeLists.txt
+++ test-suite/trunk/MultiSource/Benchmarks/Rodinia/CMakeLists.txt
@@ -1,3 +1,4 @@
 add_subdirectory(hotspot)
 add_subdirectory(srad)
+add_subdirectory(backprop)
 add_subdirectory(pathfinder)
Index: test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/CMakeLists.txt
===================================================================
--- test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/CMakeLists.txt
+++ test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/CMakeLists.txt
@@ -0,0 +1,9 @@
+set(PROG backprop)
+list(APPEND CFLAGS -I${CMAKE_CURRENT_SOURCE_DIR}/../Common)
+list(APPEND LDFLAGS -lm)
+set(FP_ABSTOLERANCE 0.00001)
+llvm_multisource(backprop 
+  main.c 
+  backpropKernel.c 
+  ../Common/glibc_compat_rand.c
+)
Index: test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/backprop.h
===================================================================
--- test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/backprop.h
+++ test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/backprop.h
@@ -0,0 +1,17 @@
+#ifndef _BACKPROP_H_
+#define _BACKPROP_H_
+
+#define ETA 0.3
+#define MOMENTUM 0.3
+
+#define LAYERSIZE 50000
+#define HIDDEN_SIZE 16
+#define OUTPUT_SIZE 1
+
+// GAP Between array index, which we want to compare
+// Otherwise very big reference output
+#define GAP 1000
+#define ITERATIONS 100
+#define SEED 7
+
+#endif
Index: test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/backprop.reference_output
===================================================================
--- test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/backprop.reference_output
+++ test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/backprop.reference_output
@@ -0,0 +1,854 @@
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+exit 0
Index: test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/backpropKernel.c
===================================================================
--- test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/backpropKernel.c
+++ test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/backpropKernel.c
@@ -0,0 +1,84 @@
+/*
+ ******************************************************************
+ * HISTORY
+ * 15-Oct-94  Jeff Shufelt (js), Carnegie Mellon University
+ * Prepared for 15-681, Fall 1994.
+ * Modified by Shuai Che
+ * 28-May-2018: Modified by Pankaj Kukreja,
+ * Indian Institute of Technology Hyderabad, India
+ ******************************************************************
+ */
+#include "backprop.h"
+#include <math.h>
+#include <stdio.h>
+
+float bpnn_train_kernel(
+    int in, int hid, int out, float input_units[static const restrict in + 1],
+    float hidden_units[static const restrict hid + 1],
+    float output_units[static const restrict out + 1],
+    float hidden_delta[static const restrict hid + 1],
+    float output_delta[static const restrict out + 1],
+    float target[static const restrict out + 1],
+    float input_weights[static const restrict in + 1][1 + hid],
+    float hidden_weights[static const restrict hid + 1][out + 1],
+    float input_prev_weights[static const restrict in + 1][hid + 1],
+    float hidden_prev_weights[static const restrict hid + 1][out + 1],
+    int iterations) {
+
+  float output_error = 0.0;
+
+  for (int iteration = 0; iteration < iterations; iteration++) {
+    double sum;
+    int j, k;
+
+    input_units[0] = 1.0;
+    for (j = 1; j <= hid; j++) {
+      sum = 0.0;
+      for (k = 0; k <= in; k++) {
+        sum += input_weights[k][j] * input_units[k];
+      }
+      hidden_units[j] = (1.0 / (1.0 + exp(-1 * sum)));
+    }
+
+    hidden_units[0] = 1.0;
+    for (j = 1; j <= out; j++) {
+      sum = 0.0;
+      for (k = 0; k <= hid; k++) {
+        sum += hidden_weights[k][j] * hidden_units[k];
+      }
+      output_units[j] = (1.0 / (1.0 + exp(-sum)));
+    }
+
+    float o, t;
+    output_error = 0.0;
+    for (j = 1; j <= out; j++) {
+      o = output_units[j];
+      t = target[j];
+      output_delta[j] = o * (1.0 - o) * (t - o);
+      output_error += fabs(output_delta[j]);
+    }
+
+    float new_dw;
+    hidden_units[0] = 1.0;
+    for (j = 1; j <= out; j++) {
+      for (k = 0; k <= hid; k++) {
+        new_dw = ((ETA * output_delta[j] * hidden_units[k]) +
+                  (MOMENTUM * hidden_prev_weights[k][j]));
+        hidden_weights[k][j] += new_dw;
+        hidden_prev_weights[k][j] = new_dw;
+      }
+    }
+
+    input_units[0] = 1.0;
+    for (j = 1; j <= hid; j++) {
+      for (k = 0; k <= in; k++) {
+        new_dw = ((ETA * hidden_delta[j] * input_units[k]) +
+                  (MOMENTUM * input_prev_weights[k][j]));
+        input_weights[k][j] += new_dw;
+        input_prev_weights[k][j] = new_dw;
+      }
+    }
+  }
+  return (output_error);
+  printf("%f\n", output_error);
+}
Index: test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/main.c
===================================================================
--- test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/main.c
+++ test-suite/trunk/MultiSource/Benchmarks/Rodinia/backprop/main.c
@@ -0,0 +1,125 @@
+#include "backprop.h"
+#include "glibc_compat_rand.h"
+#include <limits.h> // INT_MAX
+#include <stdio.h>  // printf
+#include <stdlib.h> // malloc, free
+float bpnn_train_kernel(int in, int hid, int out, float *input_units,
+                        float *hidden_units, float *output_units,
+                        float *hidden_delta, float *output_delta, float *target,
+                        float *input_weights, float *hidden_weights,
+                        float *input_prev_weights, float *hidden_prev_weights,
+                        int iterations);
+
+void bpnn_dump(int in, int hid, int out, float *input_weights,
+               float *hidden_weights, float error);
+
+////////////////////////////////////////////////////////////////////////////////
+// Program main
+////////////////////////////////////////////////////////////////////////////////
+
+int main() {
+  glibc_compat_srand(SEED);
+  float *input_weights =
+      malloc(sizeof(float) * (1 + LAYERSIZE) * (1 + HIDDEN_SIZE));
+  float *input_prev_weights =
+      malloc(sizeof(float) * (1 + LAYERSIZE) * (1 + HIDDEN_SIZE));
+  float *hidden_weights =
+      malloc(sizeof(float) * (1 + HIDDEN_SIZE) * (1 + OUTPUT_SIZE));
+  float *hidden_prev_weights =
+      malloc(sizeof(float) * (1 + HIDDEN_SIZE) * (1 + OUTPUT_SIZE));
+  float *input_units = malloc(sizeof(float) * (LAYERSIZE + 1));
+  float *hidden_units = malloc(sizeof(float) * (HIDDEN_SIZE + 1));
+  float *hidden_delta = malloc(sizeof(float) * (HIDDEN_SIZE + 1));
+  float *output_units = malloc(sizeof(float) * (OUTPUT_SIZE + 1));
+  float *output_delta = malloc(sizeof(float) * (OUTPUT_SIZE + 1));
+  float *target = malloc(sizeof(float) * (OUTPUT_SIZE + 1));
+
+  // Initializing input and hidden weights to random
+  int i, j;
+  for (i = 0; i <= LAYERSIZE; i++) {
+    for (j = 0; j <= HIDDEN_SIZE; j++) {
+      input_weights[i * (1 + HIDDEN_SIZE) + j] =
+          (float)glibc_compat_rand() / INT_MAX;
+    }
+  }
+
+  for (i = 0; i <= HIDDEN_SIZE; i++) {
+    for (j = 0; j <= OUTPUT_SIZE; j++) {
+      hidden_weights[i * (1 + OUTPUT_SIZE) + j] =
+          (float)glibc_compat_rand() / INT_MAX;
+    }
+  }
+
+  for (i = 0; i <= LAYERSIZE; i++) {
+    for (j = 0; j <= HIDDEN_SIZE; j++) {
+      input_prev_weights[i * (1 + HIDDEN_SIZE) + j] = 0.0;
+    }
+  }
+
+  for (i = 0; i <= HIDDEN_SIZE; i++) {
+    for (j = 0; j <= OUTPUT_SIZE; j++) {
+      hidden_prev_weights[i * (1 + OUTPUT_SIZE) + j] = 0.0;
+    }
+  }
+
+  for (i = 0; i <= OUTPUT_SIZE; i++) {
+    target[i] = 0.1;
+    output_units[i] = 0.0;
+    output_delta[i] = 0.0;
+  }
+
+  // Random input
+  input_units[0] = 0;
+  for (int i = 0; i <= LAYERSIZE; i++) {
+    input_units[i] = (float)glibc_compat_rand() / INT_MAX;
+  }
+
+  for (i = 0; i <= HIDDEN_SIZE; i++) {
+    hidden_units[i] = 0.0;
+    hidden_delta[i] = 0.0;
+  }
+
+  float error = 0.0;
+  // entering the training kernel
+  error = bpnn_train_kernel(
+      LAYERSIZE, HIDDEN_SIZE, OUTPUT_SIZE, input_units, hidden_units,
+      output_units, hidden_delta, output_delta, target, input_weights,
+      hidden_weights, input_prev_weights, hidden_prev_weights, ITERATIONS);
+
+  bpnn_dump(LAYERSIZE, HIDDEN_SIZE, OUTPUT_SIZE, input_weights, hidden_weights,
+            error);
+
+  free(input_weights);
+  free(hidden_weights);
+  free(input_prev_weights);
+  free(hidden_prev_weights);
+  free(input_units);
+  free(hidden_units);
+  free(output_units);
+  free(hidden_delta);
+  free(output_delta);
+  free(target);
+  return 0;
+}
+
+void bpnn_dump(int in, int hid, int out, float *input_weights,
+               float *hidden_weights, float error) {
+  int i, j;
+
+  fflush(stdout);
+  for (i = 0; i <= in; i++) {
+    for (j = 0; j <= hid; j++) {
+      if ((i * (1 + hid) + j) % GAP == 0) {
+        printf("%.6f\n", input_weights[i * (1 + hid) + j]);
+      }
+    }
+  }
+  for (i = 0; i <= hid; i++) {
+    for (j = 0; j <= out; j++) {
+      if ((i * (out + 1) + j) % GAP == 0) {
+        printf("%.6f\n", hidden_weights[i * (1 + out) + j]);
+      }
+    }
+  }
+  printf("%f\n", error);
+}