implement score calculation module (used for tune/sweep)

Signed-off-by: Jack Luar <jluar@precisioninno.com>

Author: luarss

tools/AutoTuner/src/autotuner/distributed.py

@@ -92,15 +92,15 @@
     read_config,
     read_metrics,
     prepare_ray_server,
+    calculate_score,
+    ERROR_METRIC,
     CONSTRAINTS_SDC,
     FASTROUTE_TCL,
 )
 from autotuner.tensorboard_logger import TensorBoardLogger
 
 # Name of the final metric
 METRIC = "metric"
-# The worst of optimized metric
-ERROR_METRIC = 9e99
 # Path to the FLOW_HOME directory
 ORFS_FLOW_DIR = os.path.abspath(
     os.path.join(os.path.dirname(__file__), "../../../../flow")
@@ -173,16 +173,7 @@ def evaluate(self, metrics):
         It can change in any form to minimize the score (return value).
         Default evaluation function optimizes effective clock period.
         """
-        error = "ERR" in metrics.values()
-        not_found = "N/A" in metrics.values()
-        if error or not_found:
-            return (ERROR_METRIC, "-", "-", "-")
-        effective_clk_period = metrics["clk_period"] - metrics["worst_slack"]
-        num_drc = metrics["num_drc"]
-        gamma = effective_clk_period / 10
-        score = effective_clk_period
-        score = score * (100 / self.step_) + gamma * num_drc
-        return (score, effective_clk_period, num_drc, metrics["die_area"])
+        return calculate_score(metrics, step=self.step_)
 
     def _is_valid_config(self, config):
         """

tools/AutoTuner/src/autotuner/utils.py

@@ -69,6 +69,24 @@
 # Name of the TCL script run before routing
 FASTROUTE_TCL = "fastroute.tcl"
 DATE = datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
+# The worst of optimized metric
+ERROR_METRIC = 9e99
+
+
+def calculate_score(metrics, step=1):
+    """Calculate optimization score from metrics."""
+    error = "ERR" in metrics.values()
+    not_found = "N/A" in metrics.values()
+
+    if error or not_found:
+        return (ERROR_METRIC, "-", "-", "-")
+
+    effective_clk_period = metrics["clk_period"] - metrics["worst_slack"]
+    num_drc = metrics["num_drc"]
+    gamma = effective_clk_period / 10
+    score = effective_clk_period * (100 / step) + gamma * num_drc
+
+    return (score, effective_clk_period, num_drc, metrics["die_area"])
 
 
 def write_sdc(variables, path, sdc_original, constraints_sdc):
@@ -708,21 +726,16 @@ def consumer(queue):
         print(f"[INFO TUN-0008] Finished run for parameter {config}.")
 
         metrics = read_metrics(metric_file, args.stop_stage)
-        effective_clk_period = (
-            metrics["clk_period"] - metrics["worst_slack"]
-            if metrics["worst_slack"] not in ("ERR", "N/A")
-            else "-"
-        )
-        score = effective_clk_period if effective_clk_period != "-" else 999999.0
+        score, effective_clk_period, num_drc, die_area = calculate_score(metrics)
 
         ray.get(
             tb_logger.log_sweep_metrics.remote(
                 params=config,
                 metrics=metrics,
                 score=score,
                 effective_clk_period=effective_clk_period,
-                num_drc=metrics.get("num_drc", "-"),
-                die_area=metrics.get("die_area", "-"),
+                num_drc=num_drc,
+                die_area=die_area,
             )
         )