diff --git a/unsupported/test/cxx11_tensor_contract_gpu.cu b/unsupported/test/cxx11_tensor_contract_gpu.cu
index 575bdc1f9..5abf2131d 100644
--- a/unsupported/test/cxx11_tensor_contract_gpu.cu
+++ b/unsupported/test/cxx11_tensor_contract_gpu.cu
@@ -25,10 +25,6 @@ typedef Tensor<float, 1>::DimensionPair DimPair;
 template<int DataLayout>
 void test_gpu_contraction(int m_size, int k_size, int n_size)
 {
-  std::cout << "Testing for (" << m_size << "," << k_size << "," << n_size << ")" << std::endl;
-  // with these dimensions, the output has 300 * 140 elements, which is
-  // more than 30 * 1024, which is the number of threads in blocks on
-  // a 15 SM GK110 GPU
   Tensor<float, 2, DataLayout> t_left(m_size, k_size);
   Tensor<float, 2, DataLayout> t_right(k_size, n_size);
   Tensor<float, 2, DataLayout> t_result(m_size, n_size);
@@ -171,25 +167,45 @@ void test_gpu_contraction_n() {
 
 template<int DataLayout>
 void test_gpu_contraction_sizes() {
-  int m_sizes[] = { 31,  39,   63,   64,   65,
-                   127, 129,  255,  257 , 511,
-                   512, 513, 1023, 1024, 1025};
+  int m_sizes[3][5] = {{ 31,  39,   63,   64,   65},
+                       {127, 129,  255,  257 , 511},
+                       {512, 513, 1023, 1024, 1025}};
 
-  int n_sizes[] = { 31,  39,   63,   64,   65,
-                   127, 129,  255,  257,  511,
-                   512, 513, 1023, 1024, 1025};
+  int n_sizes[3][5] = {{ 31,  39,   63,   64,   65},
+                       {127, 129,  255,  257,  511},
+                       {512, 513, 1023, 1024, 1025}};
 
-  int k_sizes[] = {  31,   39,  63,  64,   65,
-                     95,   96, 127, 129,  255,
-                    257,  511, 512, 513, 1023,
-                   1024, 1025};
+  int k_sizes[3][6] = {{ 31,   39,  63,  64,   65,   95},
+                       { 96, 127, 129,  255,  257,  511},
+                       {512, 513, 725, 1023, 1024, 1025}};
 
-  for (int i = 0; i < 15; i++) {
-    for (int j = 0; j < 15; j++) {
-      for (int k = 0; k < 17; k++) {
-        test_gpu_contraction<DataLayout>(m_sizes[i], n_sizes[j], k_sizes[k]);
+  // Some selection of specific cases.
+  //  - m changes rows each iteration
+  //  - n changes rows each 3 iterations
+  //  - k changes rows each 9 iterations
+  //  - within a row, advance once column each iteration
+  const int m_cols = 5;
+  const int n_cols = 5;
+  const int k_cols = 6;
+  int m_offset = 0;
+  int n_offset = 1;
+  int k_offset = 2;
+  for (int i = 0; i < 3; ++i) {
+    for (int j = 0; j < 3; ++j) {
+      for (int l = 0; l < 3; ++l) {
+        int m = m_sizes[l][m_offset];
+        int n = n_sizes[j][n_offset];
+        int k = k_sizes[i][k_offset];
+        test_gpu_contraction<DataLayout>(m, n, k);
+        n_offset = (n_offset + 1) % n_cols;
+        k_offset = (k_offset + 1) % k_cols;
+      }
+      m_offset = (m_offset + 1) % m_cols;
+      if (j < 2) {
+        n_offset = (n_offset + n_cols - 3) % n_cols;  // Rewind 3.
       }
     }
+    k_offset = (k_offset + 2 * k_cols - 9) % k_cols;  // Rewind 9.
   }
 }