Merge remote-tracking branch 'origin/smail' into lbaumberger

main.cpp

@@ -41,6 +41,14 @@ int main(int argc, const char *argv[]) {
   int n_p = atoi(argv[1]);
   int n_iter = atoi(argv[2]);
 
+  // Logic to get/dump the simulation data
+  const int dump_interval = 50; // dump every 5 iterations -> 20 fps (since dt = 0.01)
+  const char *dump_path = (argc >= 4) ? argv[3] : nullptr;
+
+  std::vector<std::tuple<int, int, double, double, int>> samples; // t, id, x, y, color
+  if (dump_path)
+    samples.reserve((size_t)n_iter / dump_interval * n_p);
+
   Pedestrian *pedestrians = init_pedestrians(n_p);
 
   for (int t = 0; t < n_iter; t++) {
@@ -51,41 +59,88 @@ int main(int argc, const char *argv[]) {
 
       p.F_i.reset();
 
+      // # 8 flops
       //
       // $\vec{F}_\alpha(\vec{v}_\alpha, v^0_\alpha \vec{e}_\alpha) \vec{e}_\alpha(t) = \frac{1}{\tau_\alpha}(v^0_\alpha \vec{e}_\alpha - \vec{v}_\alpha)$
       //
       compute_acceleration_term(&p);
 
+      // # 55N - 55 flops
       //
       // $\sum_{\beta} \vec{F}_{\alpha\beta}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{\beta})$
       //
       compute_repulsive_effects_from_pedestrians(pedestrians, &p, n_p);
 
+      // # 192 flops
       //
       // $\sum_{B} \vec{F}_{\alpha B}(\vec{e}_{\alpha}, \vec{r}_{\alpha} - \vec{r}_{B})$
       //
-      compute_repulsive_effects_from_borders(B, &p);
+      compute_repulsive_effects_from_borders(board, &p);
+    }
+    // Pass2: integrate the forces and update the current state
+    for (int i = 0; i < n_p; i++) {
+      Pedestrian &p = pedestrians[i];
+      // # 4 flops = 2 ADDs, 2 MULTs
+      // integrate preferred velocity:  dw/dt = F           (Eq. 10)
+      p.w = p.w + p.f_i * dt;
+      // Vector2d w_alpha = p.curr_vel + p.f_i * dt; // commented since this was using p.curr_vel instead of p.w (different from paper)
 
-      //
-      // $\vec{w}_i = \vec{v}_i + \vec{F}_idt$
-      //
-      p.w_alpha = p.curr_vel + p.F_i * delta_t;
-
-      //
-      // $\vec{v}_i^{t+1} = \vec{w}_ig(\frac{v^{max}_i}{\Arrowvert \vec{w}_i \Arrowvert}) $
-      //
-      p.next_vel = p.w_alpha * g(p.v_max, p.w_alpha.norm());
+      // # 8 flops = 2 MULTs, 2 DIVs, 1 SQRT, 2 MULTs, 1 ADD
+      p.curr_vel = p.w * g(p.v_max, p.w.norm());
 
+      // # 4 flops = 2 ADDs, 2 MULTs
       //
       // $\vec{r}_i^{t+1} += \vec{r}^t_i + v^t_idt$
       //
-      p.curr_pos = p.curr_pos + p.curr_vel * delta_t;
-    }
+      p.curr_pos = p.curr_pos + p.curr_vel * dt;
 
-    for (int i = 0; i < n_p; i++) {
-      pedestrians[i].update();
+      // how to handle if a pedestrian reached the end of our simulation/end of the hallway
+      // The option we do here is to just "teleport" the person back to the beginning
+      // the good thing is we will have a constant flow of pedestrians and in the simulation we should see how lines build up
+      if (p.color == WHITE && p.curr_pos.x > (BOARD_LENGTH - 1.5)) {
+        // basically just keep the y position and reset the x
+        p.curr_pos.x = 1.0;
+        // p.destination.y = p.curr_pos.y;
+      }
+      if (p.color == BLACK && p.curr_pos.x < 1.5) {
+        p.curr_pos.x = BOARD_LENGTH - 1.0;
+        // p.destination.y = p.curr_pos.y;
+      }
+
+      // # 10 flops = 5 ADDs, 2 DIVs, 1 SQRT, 2 MULTs
+      p.e = (p.destination - p.curr_pos) / (p.destination - p.curr_pos).norm();
+
+      // if we have a dump path/file we wanna save the data for visualisation
+      if (dump_path && (t % dump_interval == 0)) {
+        samples.emplace_back(t, i, p.curr_pos.x, p.curr_pos.y, p.color);
+      }
+    }
+  }
+  long long W = (long long)(8 + 55 * n_p - 55 + 192 + 4 + 8 + 4 + 10) * n_p * n_iter;
+  std::cout << "W(n): ";
+  std::cout << W;
+  std::cout << " flops\n";
+
+  double T = stop_tsc(start);
+  std::cout << "T(n): ";
+  std::cout << T;
+  std::cout << " cycles\n";
+
+  double P = W / T;
+
+  std::cout << "P(n): ";
+  std::cout << P;
+  std::cout << " flops/cycle\n";
+
+  // now we wanna save the data to a csv
+  if (dump_path) {
+    std::ofstream out(dump_path);
+    out << "time,id,x,y,color\n";
+    for (auto &[t, id, x, y, c] : samples) {
+      out << t << ',' << id << ',' << x << ',' << y << ',' << c << '\n';
     }
   }
 
+  delete[] pedestrians;
   return 0;
 }