[Build] calculate stable_throughput metric as part of step_measure_rtlsim_performance

src/finn/builder/build_dataflow_steps.py

@@ -667,7 +667,6 @@ def step_measure_rtlsim_performance(model: ModelWrapper, cfg: DataflowBuildConfi
             )
         rtlsim_bs = int(cfg.rtlsim_batch_size)
         if force_python_rtlsim:
-            # run with single input to get latency
             orig_rtlsim_trace_depth = get_rtlsim_trace_depth()
             assert rtlsim_bs > 0, "rtlsim batch size must be >0"
             if cfg.verify_save_rtlsim_waveforms:
@@ -680,9 +679,11 @@ def step_measure_rtlsim_performance(model: ModelWrapper, cfg: DataflowBuildConfi
             rtlsim_model.set_metadata_prop(
                 "extra_verilator_args", str(["-CFLAGS", "-O3"])
             )
+            # run with single input to get latency
+            rtlsim_latency_dict = throughput_test_rtlsim(rtlsim_model, 1)
+            # run with batch to get stable-state throughput
             rtlsim_perf_dict = throughput_test_rtlsim(rtlsim_model, rtlsim_bs)
-            rtlsim_latency = rtlsim_perf_dict["cycles"]
-            rtlsim_perf_dict["latency_cycles"] = rtlsim_latency
+            rtlsim_perf_dict["latency_cycles"] = rtlsim_latency_dict["cycles"]
         else:
             rtlsim_perf_dict = verilator_fifosim(model, rtlsim_bs)
             # keep keys consistent between the Python and C++-styles
@@ -696,6 +697,19 @@ def step_measure_rtlsim_performance(model: ModelWrapper, cfg: DataflowBuildConfi
             for (key, val) in rtlsim_perf_dict.items():
                 if "max_count" in key:
                     del rtlsim_perf_dict[key]
+        # estimate stable-state throughput based on latency+throughput
+        if rtlsim_bs == 1:
+            rtlsim_perf_dict["stable_throughput[images/s]"] = rtlsim_perf_dict[
+                "throughput[images/s]"
+            ]
+        else:
+            total_cycles = rtlsim_perf_dict["cycles"]
+            latency_cycles = rtlsim_perf_dict["latency_cycles"]
+            stablestate_cycles = total_cycles - latency_cycles
+            clk_ns = float(model.get_metadata_prop("clk_ns"))
+            fclk_mhz = 1 / (clk_ns * 0.001)
+            runtime_s = (stablestate_cycles * clk_ns) * (10**-9)
+            rtlsim_perf_dict["stable_throughput[images/s]"] = rtlsim_bs / runtime_s
 
         with open(report_dir + "/rtlsim_performance.json", "w") as f:
             json.dump(rtlsim_perf_dict, f, indent=2)