fix numerical bug and update json mode

cpp_to_py/gpudp/check/legality_check.cpp

@@ -51,7 +51,7 @@ bool siteAlignmentCheck(const float* x,
         float node_yl = y[i];
 
         float row_id_f = (node_yl - yl) / row_height;
-        int row_id = floorDiv(node_yl - yl, row_height);
+        int row_id = floorDiv(node_yl - yl, row_height, 1e-3);
         float row_yl = yl + row_height * row_id;
         float row_yh = row_yl + row_height;
 
@@ -186,8 +186,8 @@ bool overlapCheck(const float* x,
 
     // add a box to row
     auto addBox2Row = [&](int id, float bxl, float byl, float bxh, float byh) {
-        int row_idxl = floorDiv(byl - yl, row_height);
+        int row_idxl = floorDiv(byl - yl, row_height, 1e-3);
-        int row_idxh = ceilDiv(byh - yl, row_height);
+        int row_idxh = ceilDiv(byh - yl, row_height, 1e-3);
         row_idxl = std::max(row_idxl, 0);
         row_idxh = std::min(row_idxh, num_rows);
 

cpp_to_py/gpudp/lg/greedy_legalize.cpp

@@ -89,10 +89,10 @@ void distributeFixedCells2Bins(const LegalizationData& db,
     for (int i = 0; i < num_nodes; i += 1) {
         if (db.is_dummy_fixed(i) || i >= num_movable_nodes) {
             int node_id = i;
-            int bin_id_xl = std::max((int)floorDiv(x[node_id] - xl, bin_size_x), 0);
+            int bin_id_xl = std::max((int)floorDiv(x[node_id] - xl, bin_size_x, 0), 0);
-            int bin_id_xh = std::min((int)ceilDiv((x[node_id] + node_size_x[node_id] - xl), bin_size_x), num_bins_x);
+            int bin_id_xh = std::min((int)ceilDiv((x[node_id] + node_size_x[node_id] - xl), bin_size_x, 0), num_bins_x);
-            int bin_id_yl = std::max((int)floorDiv(y[node_id] - yl, bin_size_y), 0);
+            int bin_id_yl = std::max((int)floorDiv(y[node_id] - yl, bin_size_y, 0), 0);
-            int bin_id_yh = std::min((int)ceilDiv((y[node_id] + node_size_y[node_id] - yl), bin_size_y), num_bins_y);
+            int bin_id_yh = std::min((int)ceilDiv((y[node_id] + node_size_y[node_id] - yl), bin_size_y, 0), num_bins_y);
 
             for (int bin_id_x = bin_id_xl; bin_id_x < bin_id_xh; ++bin_id_x) {
                 for (int bin_id_y = bin_id_yl; bin_id_y < bin_id_yh; ++bin_id_y) {

src/detail_placement.py

@@ -326,6 +326,7 @@ def run_lg(node_pos: torch.Tensor, data: PlaceData, args, logger):
     num_bins_x, num_bins_y = 1, 64
     if not is_high_util:
         gpudp.greedyLegalization(lg_rawdb, num_bins_x, num_bins_y, True)
+    logger.info("Start checking...")
     if is_high_util or not lg_rawdb.check(get_ori_scale_factor(data)):
         logger.warning("Check failed in Greedy Legalization. Re-try by Greedy + Filler Legalization.")
 
@@ -335,6 +336,7 @@ def run_lg(node_pos: torch.Tensor, data: PlaceData, args, logger):
         # NOTE: filler legalization only legalizes movable unconnected cells (fillers)
         logger.info("Start Filler Legalization...")
         gpudp.fillerLegalization(lg_rawdb)
+        logger.info("Start checking...")
         if not lg_rawdb.check(get_ori_scale_factor(data)):
             logger.error("Check failed in Greedy + Filler Legalization.")
         logger.info("Finish Greedy + Filler Legalization. Time: %.4f" % (time.time() - gl_time))
@@ -352,6 +354,7 @@ def run_lg(node_pos: torch.Tensor, data: PlaceData, args, logger):
     logger.info("Start running Abacus Legalization...")
     al_time = time.time()
     gpudp.abacusLegalization(lg_rawdb, num_bins_x, num_bins_y)
+    logger.info("Start checking...")
     if not lg_rawdb.check(get_ori_scale_factor(data)):
         logger.error("Check failed in Abacus Legalization")
     logger.info("Finish Abacus Legalization. Time: %.4f" % (time.time() - al_time))
@@ -401,8 +404,6 @@ def trace_ops(func, *args):
 def run_dp(node_pos: torch.Tensor, data: PlaceData, args, logger):
     # GPU Detailed Placement
     dp_rawdb = setup_detailed_rawdb(node_pos, False, data, args, logger)
-    # CPU Legality Check
-    check_rawdb = setup_detailed_rawdb(node_pos, True, data, args, logger)
 
     num_bins_x = data.num_bin_x
     num_bins_y = data.num_bin_y
@@ -430,11 +431,12 @@ def run_dp(node_pos: torch.Tensor, data: PlaceData, args, logger):
             dp_rawdb.scale(scalar, False)
         # commit lpos for legality check
         torch.cuda.synchronize(node_pos.device)
-        check_rawdb.commit_from(dp_rawdb.get_curr_lposx().cpu(), dp_rawdb.get_curr_lposy().cpu())
+        logger.info("Start checking...")
-        if not check_rawdb.check(get_ori_scale_factor(data)):
+        if not dp_rawdb.check(get_ori_scale_factor(data)):
             dp_rawdb.rollback()
             logger.error("Check failed in %s. Rollback to previous DP iteration." % func_name)
             return
+        logger.info("Check Pass. Commit solution...")
         # update dp_rawdb for next step dp_func and update the final solution
         dp_rawdb.commit()
         commit_to_node_pos(node_pos, data, dp_rawdb)
@@ -450,7 +452,7 @@ def run_dp(node_pos: torch.Tensor, data: PlaceData, args, logger):
     if args.scale_design:
         node_pos /= data.die_scale
 
-    del check_rawdb, dp_rawdb
+    del dp_rawdb
 
     return node_pos
 

utils/get_design_params.py

@@ -187,7 +187,7 @@ def get_custom_design_params(args):
     return params
 
 
-def get_custom_json_params(args):
+def get_custom_json_params(args, logger):
     import json
     with open(args.custom_json, 'r') as f:
         params = json.load(f)
@@ -197,4 +197,15 @@ def get_custom_json_params(args):
         raise ValueError("Cannot find 'design_name' in args.custom_path")
     args.dataset = params["benchmark"]
     args.design_name = params["design_name"]
+    if "lefs" in params.keys():
+        logger.info("Detect json LEF/DEF mode. Please make sure that tech_lef are included first.")
+        lefs = params["lefs"]
+        for i in range(len(lefs)):
+            # Simple heuristic to find tech_lef (Only for ASAP7, Nangate45, Sky130, GF180)
+            if i == 0:
+                continue
+            if "tech" in lefs[i] or ".tlef" in lefs[i]:
+                lefs[i], lefs[0] = lefs[0], lefs[i]
+                break
+        params["lefs"] = lefs
     return params

utils/setup_dataset.py

@@ -5,8 +5,7 @@ def find_design_params(args, logger, placement=None):
     if args.custom_path != "":
         params = get_custom_design_params(args)
     elif args.custom_json != "":
-        logger.info("Detect json mode. Please make sure that tech_lef are included first.")
+        params = get_custom_json_params(args, logger)
-        params = get_custom_json_params(args)
     else:
         params = get_single_design_params(
             args.dataset_root, args.dataset, args.design_name, placement