     std::cout << std::setw(30) << "Times" << std::endl;
     std::cout << std::setfill('-') << std::setw(190) << "-" << std::endl;
     std::cout << std::setfill(' ');
-    std::cout << "   w      h      c      n      k      r      s    pad_w  pad_h    stride_w  stride_h    precision  fwd_time (usec)  ";
+    std::cout << "   w      h      c      n      k      f_w    f_h  pad_w  pad_h    stride_w  stride_h    precision  fwd_time (usec)  ";
 
     if (!inference) {
         std::cout << "bwd_inputs_time (usec)  bwd_params_time (usec)  ";

    for (const auto &problem : (inference ? inference_server_set : training_set)) {

        // Filter parameters
        int k, c, r, s;

        // Input parameters
        int n, w, h;

    if (!inference) {
        // Allocate memory for backward pass wrt weights
        auto delta = rand<T1>(cnn.get_output_dims(), curand_gen);
        auto dW = zeros<T1>(std::vector<int>{s, r, c, k});

        // Warm up backward
        cnn.backward_params(input, delta, dW);
