Geometry Nodes: Uniform mode in Shortest Edge Paths node #114733

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Iliya Katushenock wants to merge 9 commits from mod_moder:tmp_speedup_uniform_shortest_edge_paths into main

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If Weight input is single, speed of node can be improved due to reduce random-memory reads in hot loop.
Impact is depends on memory bandwidth, my results is 885.95 ms -> 675.35 ms.

If `Weight` input is single, speed of node can be improved due to reduce random-memory reads in hot loop. Impact is depends on memory bandwidth, my results is `885.95 ms` -> `675.35 ms`.
Iliya Katushenock added the
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Geometry Nodes
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Iliya Katushenock added 1 commit 2023-11-11 11:28:38 +01:00
Iliya Katushenock added 1 commit 2023-11-11 11:29:09 +01:00
Iliya Katushenock added this to the Nodes & Physics project 2023-11-11 11:29:13 +01:00
Iliya Katushenock requested review from Hans Goudey 2023-11-11 11:30:55 +01:00
Iliya Katushenock added 1 commit 2023-11-11 11:40:30 +01:00
Iliya Katushenock added 1 commit 2023-11-11 17:43:43 +01:00
Iliya Katushenock added 1 commit 2023-11-13 16:07:24 +01:00
Iliya Katushenock added 1 commit 2023-11-14 12:58:23 +01:00
Hans Goudey requested changes 2024-01-19 20:04:14 +01:00
Hans Goudey left a comment
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It looks like we could move forward with this now, right? I'll just request changes because the branch needs to have main merged in.

It looks like we could move forward with this now, right? I'll just request changes because the branch needs to have main merged in.
Iliya Katushenock added 2 commits 2024-01-19 22:03:57 +01:00
Iliya Katushenock requested review from Hans Goudey 2024-01-19 22:04:35 +01:00
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Hmm, unfortunately I can't reproduce the speedup here:

Random value
BEFORE Timer 'shortest_paths': (Average: 29.33 ms, Min: 28.27 ms, Last: 28.59 ms)
AFTER  Timer 'shortest_paths': (Average: 28.39 ms, Min: 27.33 ms, Last: 27.84 ms)
Single value
BEFORE Timer 'shortest_paths': (Average: 26.88 ms, Min: 26.03 ms, Last: 26.55 ms)
AFTER  Timer 'shortest_paths': (Average: 25.92 ms, Min: 25.07 ms, Last: 25.38 ms)
Hmm, unfortunately I can't reproduce the speedup here: ``` Random value BEFORE Timer 'shortest_paths': (Average: 29.33 ms, Min: 28.27 ms, Last: 28.59 ms) AFTER Timer 'shortest_paths': (Average: 28.39 ms, Min: 27.33 ms, Last: 27.84 ms) Single value BEFORE Timer 'shortest_paths': (Average: 26.88 ms, Min: 26.03 ms, Last: 26.55 ms) AFTER Timer 'shortest_paths': (Average: 25.92 ms, Min: 25.07 ms, Last: 25.38 ms) ```
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Initially i made other version of function (which is works with int-weights and bypass some things (like std::max(0, weight)), result was wrapped in garray-converter). Now, to simplify things, i change implementation to simply use devirtualize_varray. And it seems, now change just 25%. Though it is still a enough.
I think it really depend on memory bandwidth, not sure how to reproduce this results on machine with faster ram.
I also changed test file (10x more mesh) to make results more different.

Initially i made other version of function (which is works with int-weights and bypass some things (like `std::max(0, weight)`), result was wrapped in garray-converter). Now, to simplify things, i change implementation to simply use `devirtualize_varray`. And it seems, now change just `25%`. Though it is still a enough. I think it really depend on memory bandwidth, not sure how to reproduce this results on machine with faster ram. I also changed test file (10x more mesh) to make results more different.
Iliya Katushenock added 1 commit 2024-01-21 13:55:07 +01:00
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Tried other ways to reduce memory bounds in hot loop and it seems there is no way to make it visibly faster.

  devirtualize_varray(input_cost, [&](auto input_cost) {
    while (!queue.empty()) {
      const float cost_i = queue.top().first;
      const int vert_i = queue.top().second;
      queue.pop();
      if (visited[vert_i]) {
        continue;
      }
      visited[vert_i] = true;
      for (const auto [other_vert, edge] : edge_paths[vert_i]) {
        if (visited[other_vert]) {
          continue;
        }
        const float edge_cost = std::max(0.0f, input_cost[edge]);
        const float new_neighbor_cost = cost_i + edge_cost;
        if (new_neighbor_cost < next_and_cost[other_vert].second) {
          queue.emplace(new_neighbor_cost, other_vert);
        }
      }
      for (const auto [other_vert, edge] : edge_paths[vert_i]) {
        if (visited[other_vert]) {
          continue;
        }
        const float edge_cost = std::max(0.0f, input_cost[edge]);
        const float new_neighbor_cost = cost_i + edge_cost;
        if (new_neighbor_cost < next_and_cost[other_vert].second) {
          next_and_cost[other_vert] = {vert_i, new_neighbor_cost};
        }
      }
    }
  });

Probably, next investigations should be in direction of using multithreaded A*.

Tried other ways to reduce memory bounds in hot loop and it seems there is no way to make it visibly faster. ```Cpp devirtualize_varray(input_cost, [&](auto input_cost) { while (!queue.empty()) { const float cost_i = queue.top().first; const int vert_i = queue.top().second; queue.pop(); if (visited[vert_i]) { continue; } visited[vert_i] = true; for (const auto [other_vert, edge] : edge_paths[vert_i]) { if (visited[other_vert]) { continue; } const float edge_cost = std::max(0.0f, input_cost[edge]); const float new_neighbor_cost = cost_i + edge_cost; if (new_neighbor_cost < next_and_cost[other_vert].second) { queue.emplace(new_neighbor_cost, other_vert); } } for (const auto [other_vert, edge] : edge_paths[vert_i]) { if (visited[other_vert]) { continue; } const float edge_cost = std::max(0.0f, input_cost[edge]); const float new_neighbor_cost = cost_i + edge_cost; if (new_neighbor_cost < next_and_cost[other_vert].second) { next_and_cost[other_vert] = {vert_i, new_neighbor_cost}; } } } }); ``` Probably, next investigations should be in direction of using multithreaded A*.
Iliya Katushenock deleted branch tmp_speedup_uniform_shortest_edge_paths 2024-04-06 00:01:14 +02:00

Pull request closed

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Reference: blender/blender#114733
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