update to include gp cmd option

main.py

@@ -9,6 +9,7 @@ def get_option():
     parser.add_argument('--design_name', type=str, default='mgc_superblue12', help='design name')
     parser.add_argument('--custom_path', type=str, default='', help='custom design path, set it as token1:path1,token2:path2 e.g. lef:data/test.lef,def:data/test.def,design_name:mydesign,benchmark:mybenchmark')
     parser.add_argument('--custom_json', type=str, default='', help='custom json path, support multi-lefs.')
+    parser.add_argument('--given_solution', type=str, default='', help='Given placement solution. Will overwrite other given .pl and .def.')
     parser.add_argument('--load_from_raw', type=str2bool, default=True, help='If True, parse and load from benchmark files. If False, load from pt')
     parser.add_argument('--run_all', type=str2bool, default=False, help='If True, run all designs in the given dataset. If False, run the given design_name only.')
     parser.add_argument('--seed', type=int, default=0, help='seed to initialize all the random modules')
@@ -17,6 +18,7 @@ def get_option():
     parser.add_argument('--deterministic', type=str2bool, default=True, help='use deterministic mode')
 
     # global placement params
+    parser.add_argument('--global_placement', type=str2bool, default=True, help='perform gp') 
     parser.add_argument('--lr', type=float, default=0.01, help='learning rate')
     parser.add_argument('--inner_iter', type=int, default=10000, help='#inner iters')
     parser.add_argument('--wa_coeff', type=float, default=4.0, help='wa coeff')

src/run_placement_nesterov.py

@@ -10,24 +10,22 @@ def get_trunc_node_pos_fn(mov_node_size, data):
         return x
     return trunc_node_pos_fn
 
-def run_placement_main_nesterov(args, logger):
-    total_start = time.time()
-    params = find_design_params(args, logger)
-    data, rawdb, gpdb = load_dataset(args, logger, params)
-    device = torch.device(
-        "cuda:{}".format(args.gpu) if torch.cuda.is_available() else "cpu"
-    )
-    assert args.use_eplace_nesterov
-    logger.info("Start place %s/%s" % (args.dataset , args.design_name))
-    logger.info("Use Nesterov optimizer!")
-    data = data.to(device)
-    data = data.preprocess()
-    logger.info(data)
-    logger.info(data.node_type_indices)
-    # args.num_bin_x = args.num_bin_y = 2 ** math.ceil(math.log2(max(data.die_info).item() // 25))
+def global_placement_main(gpdb, rawdb, ps: ParamScheduler, data: PlaceData, args, logger):
+    init_density_map = data.init_density_map
+    if not args.global_placement:
+        logger.info("Global placement is switched off. Please make sure the input "
+                    "placement solution is already placed globally.")
+        node_pos, iteration = data.node_pos, 0
+        hpwl, overflow = evaluate_placement(node_pos, init_density_map, ps, data, args)
+        hpwl, overflow = hpwl.item(), overflow.item()
+        info = ("%d_gp" % (iteration + 1), hpwl, data.design_name)
+        if args.draw_placement:
+            draw_fig_with_cairo_cpp(node_pos, data.node_size, data, info, args)
+        logger.info("Input solution, exact HPWL: %.6E exact Overflow: %.4f" % (hpwl, overflow))
+        gp_hpwl, overflow, gp_time, gp_per_iter = hpwl, overflow, 0, -1
+        return node_pos, iteration, gp_hpwl, overflow, gp_time, gp_per_iter
 
-    init_density_map = get_init_density_map(rawdb, gpdb, data, args, logger)
-    data.init_filler()
+    device = data.device
     mov_lhs, mov_rhs = data.movable_index
     mov_node_pos, mov_node_size, expand_ratio = data.get_mov_node_info()
     mov_node_pos = mov_node_pos.requires_grad_(True)
@@ -45,7 +43,6 @@ def run_placement_main_nesterov(args, logger):
         return overflow_sum / data.total_mov_area_without_filler
     overflow_helper = (mov_lhs, mov_rhs, overflow_fn)
 
-    ps = ParamScheduler(data, args, logger)
     density_map_layer = ElectronicDensityLayer(
         unit_len=data.unit_len,
         num_bin_x=data.num_bin_x,
@@ -391,6 +388,33 @@ def run_placement_main_nesterov(args, logger):
     gp_time = gp_end_time - gp_start_time
     iteration += 1 # increase 1 For DP drawing
 
+    return node_pos, iteration, gp_hpwl, overflow, gp_time, gp_per_iter
+
+
+def run_placement_main_nesterov(args, logger):
+    total_start = time.time()
+    params = find_design_params(args, logger)
+    data, rawdb, gpdb = load_dataset(args, logger, params)
+    device = torch.device(
+        "cuda:{}".format(args.gpu) if torch.cuda.is_available() else "cpu"
+    )
+    assert args.use_eplace_nesterov
+    logger.info("Start place %s/%s" % (args.dataset , args.design_name))
+    logger.info("Use Nesterov optimizer!")
+    data = data.to(device)
+    data = data.preprocess()
+    logger.info(data)
+    logger.info(data.node_type_indices)
+    # args.num_bin_x = args.num_bin_y = 2 ** math.ceil(math.log2(max(data.die_info).item() // 25))
+    get_init_density_map(rawdb, gpdb, data, args, logger)
+    data.init_filler()
+
+    ps = ParamScheduler(data, args, logger)
+
+    # global placement
+    node_pos, iteration, gp_hpwl, overflow, gp_time, gp_per_iter = global_placement_main(
+        gpdb, rawdb, ps, data, args, logger
+    )
     # detail placement
     node_pos, dp_hpwl, top5overflow, lg_time, dp_time = detail_placement_main(
         node_pos, gpdb, rawdb, ps, data, args, logger

utils/io_parser.py

@@ -77,6 +77,9 @@ class IOParser(object):
             if "pl" in params.keys() and not os.path.exists(params["pl"]):
                 print("pl %s not exists." % params["pl"])
                 return False
+            if "bookshelf_variety" not in params.keys():
+                print("Not specify bookshelf_variety. Set to ispd2005.")
+                params["bookshelf_variety"] = "ispd2005"
             if "output" in params.keys():
                 if "pl" != params["output"].split(".")[-1]:
                     print("output format should be .pl")

utils/setup_dataset.py

@@ -10,11 +10,28 @@ def find_design_params(args, logger, placement=None):
         params = get_single_design_params(
             args.dataset_root, args.dataset, args.design_name, placement
         )
+    setup_given_solution(args, logger, params, placement)
     log_design_params(logger, params)
     setup_design_args(args)
     return params
 
 
+def setup_given_solution(args, logger, params, placement=None):
+    if placement is not None:
+        args.given_solution = placement
+    if args.given_solution != "":
+        placement = args.given_solution
+        logger.info("Find given placement solution: %s" % placement)
+        if ".pl" in placement:
+            if "pl" in params.keys():
+                logger.info("Overwrite pl file %s by %s" % (params["pl"], placement))
+            params["pl"] = placement
+        elif ".def" in placement:
+            if "def" in params.keys():
+                logger.info("Overwrite def file %s by %s" % (params["def"], placement))
+            params["def"] = placement
+
+
 def log_design_params(logger, params: dict):
     content = "Design Info:\n"
     num_items = 0