Benchmark parallel and fusion variants

Author: allnes

app/Graph/CMakeLists.txt

@@ -19,6 +19,7 @@ target_include_directories(BuildGraph PUBLIC ${CMAKE_SOURCE_DIR}/3rdparty/Json/i
 
 add_executable(Graph_Build graph_build.cpp)
 target_link_libraries(Graph_Build BuildGraph)
+target_link_libraries(Graph_Build graphT_lib)
 
 add_executable(ACC acc_check.cpp)
 target_link_libraries(ACC BuildGraph)

app/Graph/graph_build.cpp

@@ -3,13 +3,55 @@
 #include <unordered_map>
 
 #include "build.hpp"
+#include "graph_transformations/graph_transformations.hpp"
+#include "layers_fused/ConvRelu.hpp"
 
 namespace fs = std::filesystem;
 using namespace it_lab_ai;
 
+namespace {
+
+enum class FusionMode { kOff, kPostops, kConvRelu };
+
+FusionMode parse_fusion_mode(const std::string& value) {
+  if (value == "off") {
+    return FusionMode::kOff;
+  }
+  if (value == "postops") {
+    return FusionMode::kPostops;
+  }
+  if (value == "convrelu") {
+    return FusionMode::kConvRelu;
+  }
+  throw std::invalid_argument("Unknown fusion mode: " + value);
+}
+
+void apply_conv_relu_fusion(Graph& graph, Tensor& output,
+                            const RuntimeOptions& options) {
+  if (options.backend == Backend::kOneDnn) {
+    throw std::invalid_argument(
+        "convrelu fusion is not supported with oneDNN backend");
+  }
+
+  Graph subgraph;
+  Tensor dummy_input = make_tensor(std::vector<int>({0}));
+  auto conv = std::make_shared<ConvolutionalLayer>();
+  auto relu = std::make_shared<EWLayer>("relu");
+  subgraph.setInput(conv, dummy_input);
+  subgraph.makeConnection(conv, relu);
+
+  Graph fused_graph;
+  auto fused_layer = std::make_shared<ConvReluLayer>();
+  changed_subgraphs(graph, subgraph, fused_layer, fused_graph, output, options);
+  graph = std::move(fused_graph);
+}
+
+}  // namespace
+
 int main(int argc, char* argv[]) {
   std::string model_name = "alexnet_mnist";
   RuntimeOptions options;
+  FusionMode fusion_mode = FusionMode::kPostops;
 
   for (int i = 1; i < argc; ++i) {
     if (std::string(argv[i]) == "--model" && i + 1 < argc) {
@@ -47,6 +89,8 @@ int main(int argc, char* argv[]) {
       }
     } else if (std::string(argv[i]) == "--threads" && i + 1 < argc) {
       options.threads = std::stoi(argv[++i]);
+    } else if (std::string(argv[i]) == "--fusion" && i + 1 < argc) {
+      fusion_mode = parse_fusion_mode(argv[++i]);
     }
   }
 
@@ -92,7 +136,11 @@ int main(int argc, char* argv[]) {
         std::vector<float> vec(75, 3);
         it_lab_ai::Tensor output = it_lab_ai::make_tensor(vec, sh1);
         Graph graph;
-        build_graph_linear(graph, input, output, options, true);
+        build_graph_linear(graph, input, output, options, true,
+                           fusion_mode == FusionMode::kPostops);
+        if (fusion_mode == FusionMode::kConvRelu) {
+          apply_conv_relu_fusion(graph, output, options);
+        }
 
         std::cout << "Starting inference..." << '\n';
         try {
@@ -133,6 +181,9 @@ int main(int argc, char* argv[]) {
 
         Graph graph;
         build_graph(graph, input, output, json_path, options, false);
+        if (fusion_mode == FusionMode::kConvRelu) {
+          apply_conv_relu_fusion(graph, output, options);
+        }
 
         std::cout << "Starting inference..." << '\n';
         try {

benchmarks/README.md

@@ -42,8 +42,7 @@ Run selected models and variants:
 ```bash
 python3 benchmarks/model_performance.py \
   --model googlenet,resnet \
-  --variant seq \
-  --variant parallel-tbb \
+  --variant target \
   --repeat 3 \
   --warmup 1
 ```
@@ -52,5 +51,10 @@ The JSON report includes `memory_samples` for every run. PNG plots are written
 to `benchmark_results/memory_plots` by default. Use `--samples-csv-out` to export
 the memory timeline to CSV and `--plots-dir` to choose another plot directory.
 
+Use `--variant target` for the full target matrix: every supported parallel
+backend with fusion off/on, plus oneDNN with fusion off/on. Fusion-on uses the
+existing `Conv+Relu` fused layer for naive/parallel backends and existing
+post-ops mode for oneDNN.
+
 Use `--strict-assets` to fail when a model JSON or input image directory is
 missing instead of skipping that model.

benchmarks/model_performance.py

@@ -57,6 +57,46 @@
     "parallel-threads": ["--parallel", "threads"],
     "parallel-omp": ["--parallel", "omp"],
     "parallel-kokkos": ["--parallel", "kokkos"],
+    "seq-fusion-off": ["--fusion", "off"],
+    "seq-fusion-on": ["--fusion", "convrelu"],
+    "parallel-tbb-fusion-off": ["--parallel", "tbb", "--fusion", "off"],
+    "parallel-tbb-fusion-on": ["--parallel", "tbb", "--fusion", "convrelu"],
+    "parallel-threads-fusion-off": ["--parallel", "threads", "--fusion", "off"],
+    "parallel-threads-fusion-on": [
+        "--parallel",
+        "threads",
+        "--fusion",
+        "convrelu",
+    ],
+    "parallel-omp-fusion-off": ["--parallel", "omp", "--fusion", "off"],
+    "parallel-omp-fusion-on": ["--parallel", "omp", "--fusion", "convrelu"],
+    "parallel-kokkos-fusion-off": ["--parallel", "kokkos", "--fusion", "off"],
+    "parallel-kokkos-fusion-on": [
+        "--parallel",
+        "kokkos",
+        "--fusion",
+        "convrelu",
+    ],
+    "onednn-fusion-off": ["--onednn", "--fusion", "off"],
+    "onednn-fusion-on": ["--onednn", "--fusion", "postops"],
+}
+
+VARIANT_GROUPS = {
+    "all": list(VARIANT_ARGS),
+    "target": [
+        "seq-fusion-off",
+        "seq-fusion-on",
+        "parallel-tbb-fusion-off",
+        "parallel-tbb-fusion-on",
+        "parallel-threads-fusion-off",
+        "parallel-threads-fusion-on",
+        "parallel-omp-fusion-off",
+        "parallel-omp-fusion-on",
+        "parallel-kokkos-fusion-off",
+        "parallel-kokkos-fusion-on",
+        "onednn-fusion-off",
+        "onednn-fusion-on",
+    ],
 }
 
 
@@ -142,10 +182,15 @@ def expand_choices(values: Sequence[str], choices: dict[str, object], default: s
                 continue
             if item == "all":
                 expanded.extend(choices)
+            elif item in VARIANT_GROUPS and choices is VARIANT_ARGS:
+                expanded.extend(VARIANT_GROUPS[item])
             elif item in choices:
                 expanded.append(item)
             else:
-                raise SystemExit(f"Unknown value '{item}'. Valid: all, {', '.join(choices)}")
+                valid = ["all", *choices]
+                if choices is VARIANT_ARGS:
+                    valid.extend(name for name in VARIANT_GROUPS if name != "all")
+                raise SystemExit(f"Unknown value '{item}'. Valid: {', '.join(valid)}")
     return dedupe(expanded)