add SA + FD

CodeElements/SimulatedAnnealing/config.json

+{
+    "netlist" : "./ariane133/ariane.pb.txt",
+    "plc_file" : "./ariane133/ariane.plc",
+    "action_probs" :[[0.2, 0.2, 0.2, 0.2, 0.2]],
+    "num_actions(xn)" : [2, 3, 4, 5],
+    "max_temperature" : [5e-5, 7e-5, 1e-4, 5e-4, 1e-3],
+    "num_iters" : [10],
+    "seed" : [0, 1],
+    "num_cores" : 8,
+    "spiral_flag" : [ "True", "False"]
+}

CodeElements/SimulatedAnnealing/sa_multicore.py

+# ---------------------------------------------------------------------------
+# Run Simulated Annealing in parallel with multiple cores
+# You must set up the environment correctly before you run this script
+# Please check Circuit Training for environment setup
+# --------------------------------------------------------------------------
+import sys
+import os
+import subprocess
+import multiprocessing
+import time
+from datetime import datetime
+import json
+import glob
+
+from SA import  SimulatedAnnealing
+
+### Wrapper function for calling Simulated Annealing
+def RunSA(run_id, dir, netlist, plc_file, action_probs, num_actions, max_temperature, num_iters, seed, spiral_flag):
+    run_dir = dir + "/run_" + str(run_id)
+    os.mkdir(run_dir)
+
+    # create param_map
+    param_map = { }
+    param_map["id"] = run_id
+    param_map["dir"] = dir
+    param_map["netlist"] = netlist
+    param_map["plc_file"] = plc_file
+    param_map["action_probs"] = action_probs
+    param_map["num_actions"] = num_actions
+    param_map["max_temperature"] = max_temperature
+    param_map["num_iters"] = num_iters
+    param_map["seed"] = seed
+    param_map["spiral_flag"] = spiral_flag
+
+    param_file = run_dir + "/params.json"
+    f = open(param_file, "w")
+    f.write(json.dumps(param_map, indent = 4))
+    f.close()
+
+    design = netlist.split('/')[-1].split('.')[0]
+    sa = SimulatedAnnealing(design, run_dir, netlist, plc_file, action_probs, num_actions, max_temperature, num_iters, seed, spiral_flag)
+
+
+### Run Simulated Annealing with multiple threads
+def RunParallelSA(config_json_file):
+    # parse the configuration json file
+    f = open(config_json_file)
+    params = json.load(f)
+    f.close()
+
+    netlist = params["netlist"]
+    plc_file = params["plc_file"]
+    action_probs_list = params["action_probs"]
+    num_actions_list = params["num_actions(xn)"]
+    max_temperature_list = params["max_temperature"]
+    num_iters_list = params["num_iters"]
+    seed_list = params["seed"]
+    num_cores = params["num_cores"]
+    spiral_flag_list = params["spiral_flag"]
+
+    result_dir ="./result_" + str(datetime.fromtimestamp(time.time()))
+    os.mkdir(result_dir)
+    params_file = result_dir + "/params.json"
+    f = open(params_file, "w")
+    f.write(json.dumps(params, indent = 4))
+    f.close()
+
+    param_list = []
+    for action_probs in action_probs_list:
+        for num_actions in num_actions_list:
+            for max_temperature in max_temperature_list:
+                for num_iters in num_iters_list:
+                    for seed in seed_list:
+                        for spiral_flag in spiral_flag_list:
+                            param_map = { }
+                            param_map["id"] = len(param_list)
+                            param_map["dir"] = result_dir
+                            param_map["netlist"] = netlist
+                            param_map["plc_file"] = plc_file
+                            param_map["action_probs"] =  action_probs
+                            param_map["num_actions"] = num_actions
+                            param_map["max_temperature"] = max_temperature
+                            param_map["num_iters"] = num_iters
+                            param_map["seed"] = seed
+                            param_map["spiral_flag"] = (spiral_flag == 'True' or spiral_flag == 'TRUE')
+                            param_list.append(param_map)
+
+    with multiprocessing.Manager() as manager:
+        # create lists in server memory
+        runtime_list = manager.list([])
+        cut_list = manager.list([])
+        remaining_runs = len(param_list)
+        run_id = 0
+        while (remaining_runs > 0):
+            num_thread = min(num_cores, remaining_runs)
+            process_list = []
+            for i in range(num_thread):
+                param_map = param_list[run_id]
+                p = multiprocessing.Process(target = RunSA,
+                                            args = (param_map["id"],
+                                                    param_map["dir"],
+                                                    param_map["netlist"],
+                                                    param_map["plc_file"],
+                                                    param_map["action_probs"],
+                                                    param_map["num_actions"],
+                                                    param_map["max_temperature"],
+                                                    param_map["num_iters"],
+                                                    param_map["seed"],
+                                                    param_map["spiral_flag"]))
+                run_id = run_id + 1
+                p.start()
+                process_list.append(p)
+
+            for process in process_list:
+                process.join()
+
+            remaining_runs -= num_thread
+
+    summary_files = glob.glob(result_dir + "/*/*.summary")
+    cost_list = []
+    for summary_file in summary_files:
+        with open(summary_file) as f:
+            content = f.read().splitlines()
+        f.close()
+        # find the start_idx
+        start_idx = 0
+        for i in range(len(content)):
+            items = content[i].split()
+            if (len(items) == 1):
+                start_idx = i
+                break
+
+        if (len(cost_list) == 0):
+            for i in range(start_idx, len(content)):
+                cost_list.append(float(content[i]))
+        else:
+            for i in range(start_idx, len(content)):
+                idx = i - start_idx
+                if (idx >= len(cost_list)):
+                    cost_list.append(float(content[i]))
+                else:
+                    cost_list[idx] = min(cost_list[idx], float(content[i]))
+
+    f = open(result_dir + "/cost_summary.txt", "w")
+    for cost in cost_list:
+        f.write(str(cost) + "\n")
+    f.close()
+
+if __name__ == "__main__":
+    config_file  = "config.json"
+    RunParallelSA(config_file)
+
+
+
+
+
+
+
+
+
+