#441: add scalene optimization suggestions

DARMA-tasking · Oct 10, 2023 · b213f5c · b213f5c
1 parent 9a9f218
commit b213f5c
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Showing 2 changed files with 15 additions and 23 deletions.
diff --git a/src/lbaf/Applications/LBAF_app.py b/src/lbaf/Applications/LBAF_app.py
@@ -462,10 +462,6 @@ def run(self):
                     self.__logger, phase_id, reader=reader)
                 phase.populate_from_log(phase_id)
                 phases[phase_id] = phase
-                phase = Phase(
-                    self.__logger, phase_id, reader=reader)
-                phase.populate_from_log(phase_id)
-                phases[phase_id] = phase
         else:
             n_ranks = self.__parameters.n_ranks
             phase_id = 0
@@ -523,7 +519,7 @@ def run(self):
                     self.__logger.warning(
                         "No rebalancing took place for offline load-balancing")
                 else:
-                    # Determine if a phase with same index was present
+                    # Determine if a phase with the same index was present
                     if _existing_phase := phases.get(p_id := rebalanced_phase.get_id()):
                         # Apply object timings to rebalanced phase
                         self.__logger.info(
@@ -555,13 +551,11 @@ def run(self):
                 raise SystemExit(1)
 
             # Look for prescribed QOI bounds
-            qoi_request = [self.__parameters.rank_qoi]
-            qoi_request.append(
-                self.__parameters.work_model.get(
-                    "parameters").get(
-                    "upper_bounds", {}).get(
-                    self.__parameters.rank_qoi))
-            qoi_request.append(self.__parameters.object_qoi)
+            qoi_request = [
+                self.__parameters.rank_qoi,
+                self.__parameters.work_model.get("parameters", {}).get("upper_bounds", {}).get(self.__parameters.rank_qoi),
+                self.__parameters.object_qoi
+            ]
 
             # Instantiate and execute visualizer
             visualizer = Visualizer(

diff --git a/src/lbaf/Execution/lbsInformAndTransferAlgorithm.py b/src/lbaf/Execution/lbsInformAndTransferAlgorithm.py
@@ -185,7 +185,7 @@ def execute(self, p_id: int, phases: list, distributions: dict, statistics: dict
         # Set phase to be used by transfer criterion
         self.__transfer_criterion.set_phase(self._rebalanced_phase)
 
-        # Retrieve totat work from computed statistics
+        # Retrieve total work from computed statistics
         total_work = statistics["total work"][-1]
 
         # Perform requested number of load-balancing iterations
@@ -214,20 +214,19 @@ def execute(self, p_id: int, phases: list, distributions: dict, statistics: dict
 
             # Compute and report iteration work statistics
             stats = print_function_statistics(
-                        self._rebalanced_phase.get_ranks(),
-                        lambda x: self._work_model.compute(x),  # pylint:disable=W0108:unnecessary-lambda
-                        f"iteration {i + 1} rank work",
-                        self._logger)
+                self._rebalanced_phase.get_ranks(),
+                self._work_model.compute,
+                f"iteration {i + 1} rank work",
+                self._logger)
 
             # Update run distributions and statistics
             self._update_distributions_and_statistics(distributions, statistics)
 
             # Compute current arrangement
-            arrangement = tuple(
-                v for _, v in sorted(
-                    {o.get_id(): p.get_id()
-                     for p in self._rebalanced_phase.get_ranks()
-                     for o in p.get_objects()}.items()))
+            arrangement = tuple(sorted(
+                {o.get_id(): p.get_id()
+                for p in self._rebalanced_phase.get_ranks()
+                for o in p.get_objects()}.values()))
             self._logger.debug(f"Iteration {i + 1} arrangement: {arrangement}")
 
             # Report minimum Hamming distance when minimax optimum is available
@@ -241,7 +240,6 @@ def execute(self, p_id: int, phases: list, distributions: dict, statistics: dict
             if stats.statistics["imbalance"] <= self.__target_imbalance:
                 self._logger.info(f"Reached target imbalance of {self.__target_imbalance} after {i + 1} iterations.")
                 break
-            end_time = time.time()
 
             # Calculate the duration of the iteration
             end_time = time.time()