add custom_path

README.md

@@ -6,6 +6,7 @@ We are happy to announce that Xplace 2.0 is now released. Compared to [Xplace 1.
 - Support deterministic mode with only 5~25% extra GP runtime overhead.
 - Implement an extremely fast GPU-accelerated detailed-routability-driven placement algorithm.
 - Integrate with a GPU-accelerated detailed placer and a GPU-accelerated global router.
+- Support a superfast **GPU-accelerated place and global route flow** ([Xplace](https://dl.acm.org/doi/abs/10.1145/3489517.3530485) + [GGR](https://dl.acm.org/doi/10.1145/3508352.3549474))! Input your LEF/DEF, the flow will output the **placement DEF** and the **global routing guide**! 
 - Provide benchmark download and preprocess scripts, and three routability evaluation scripts. 
 - Code refactoring.
 
@@ -50,7 +51,7 @@ cmake -DPYTHON_EXECUTABLE=$(which python) ..
 make -j40 && make install
 ```
 
-## Prepare Data
+## Prepare data
 The following script will automatically download `ispd2005`, `ispd2015`, and `iccad2019` benchmarks in `./data/raw`. It also preprocesses `ispd2015` benchmark to fix some errors when routing them by Innovus®.
 ```bash
 cd $XPLACE_HOME/data
@@ -95,15 +96,23 @@ In ./result/exp_id
 ## Parameters
 Please refer to `main.py`.
 
+## Run custom dataset
+You can use the argument `--custom_path` to run your custom LEF/DEF or bookshelf benchmark.
+
+Suppose there is a LEF/DEF benchmark named `toy` in `data/raw`, you can use the following command line to run the GP + DP flow:
+```bash
+python main.py --custom_path lef:data/raw/toy_input.lef,def:data/raw/toy_input.def,design_name:toy,benchmark:test --load_from_raw True --detail_placement True
+```
+
 
 ## Load design from preprocessed `pt` file (Optional)
 The following script will dump the parsed design into a single torch `pt` file so Xplace can load the design from the `pt` file instead of parsing the input file from scratch. 
 
 ```bash
 cd $XPLACE_HOME/data
-python utils/convert_design_to_torch_data.py --dataset ispd2005
-python utils/convert_design_to_torch_data.py --dataset ispd2015_fix
-python utils/convert_design_to_torch_data.py --dataset iccad2019
+python convert_design_to_torch_data.py --dataset ispd2005
+python convert_design_to_torch_data.py --dataset ispd2015_fix
+python convert_design_to_torch_data.py --dataset iccad2019
 ```
 Preprocessed data is saved in `./data/cad`.
 
@@ -116,16 +125,26 @@ python main.py --dataset ispd2005 --run_all True --load_from_raw False
 **NOTE**: 
 1. Please remember to use the raw mode (set `--load_from_raw True`) when measuring the total running time.
 2. We currently do not support `pt` mode in the routability-driven global placement.
+3. If you want to run `pt` mode for the custom dataset, you need to add the custom dataset path in `utils/get_design_params.py`.
 
-## Evaluate the Routability of Xplace's Solution 
+## GPU-accelerated place and global route flow (Xplace + GGR)
+Set `--final_route_eval True` in Python arguments to invoke the internal global router [GGR](https://dl.acm.org/doi/10.1145/3508352.3549474) to run GPU-accelerated PnR flow. The flow will output the **placement DEF** and the **global routing guide** in `./result/exp_id/output`. Besides, GR metrics are reported in the log and recorded in `./result/exp_id/log/route.csv`. 
+
+- To run Place and Global Route flow for ISPD2015 dataset:
+```bash
+python main.py --dataset ispd2015_fix --run_all True --load_from_raw True --detail_placement True --use_cell_inflate True --final_route_eval True
+```
+
+More details about using GGR in Xplace can be found in [cpp_to_py/gpugr/README.md](cpp_to_py/gpugr/README.md).
+
+## Evaluate theroutability of Xplace's solution 
 We provide three ways to evaluate the routability of a placement solution:
 
-1. Set `--final_route_eval True` in Python arguments to invoke the internal global router [GGR](https://dl.acm.org/doi/10.1145/3508352.3549474) to evaluate the placement solution. The evaluation metrics are reported in the log and recorded in `./result/exp_id/log/route.csv`. Besides, the route guide file is written in `./result/exp_id/output/design_name.guide`.  
-More details about using GGR in Xplace can be found in [cpp_to_py/gpugr](cpp_to_py/gpugr).
+1. Set `--final_route_eval True` to invoke [GGR](https://dl.acm.org/doi/10.1145/3508352.3549474) to evaluate the placement solution.
 
-2. Use [CU-GR](https://github.com/cuhk-eda/cu-gr) to evaluate the placement solution by global routing. Please refer to [tool/cugr_ispd2015_fix](tool/cugr_ispd2015_fix) for instructions.
+2. Use [CU-GR](https://github.com/cuhk-eda/cu-gr) to evaluate the placement solution by global routing. Please refer to [tool/cugr_ispd2015_fix/README.md](tool/cugr_ispd2015_fix/README.md) for instructions.
 
-3. (Optional). If Innovus® has been properly installed in your OS, you may try to use Innovus® to detailedly route the placement solution. Please refer to [tool/innovus_ispd2015_fix](tool/innovus_ispd2015_fix) for instructions.
+3. (Optional). If Innovus® has been properly installed in your OS, you may try to use Innovus® to detailedly route the placement solution. Please refer to [tool/innovus_ispd2015_fix/README.md](tool/innovus_ispd2015_fix/README.md) for instructions.
 
 
 ## Citation

main.py

@@ -7,6 +7,7 @@ def get_option():
     parser.add_argument('--dataset_root', type=str, default='data/raw', help='the parent folder of dataset')
     parser.add_argument('--dataset', type=str, default='ispd2015_fix', help='dataset name')
     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('--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')
@@ -75,6 +76,9 @@ def get_option():
         print("We haven't yet support fence region in ispd2015, use ispd2015_fix instead")
         args.dataset = "ispd2015_fix"
 
+    if args.custom_path != "":
+        get_custom_design_params(args)
+
     return args
 
 def main():

src/database.py

@@ -1,25 +1,18 @@
-"""
-Adapted from torch_geometric/data/data.py
-"""
 import torch
 import collections
 import copy
 import math
 from utils import *
 
-def get_dataset(args, logger):
-    with open("./data/cad/%s/datalist.csv" % (args.dataset), "r") as f:
-        all_files = f.readlines()
-        all_files = [line[:-1] for line in all_files]
-    for cur_file in all_files:
-        yield cur_file
-
 
 def load_dataset(args, logger, placement=None):
     rawdb, gpdb = None, None
-    params = get_single_design_params(
-        args.dataset_root, args.dataset, args.design_name, placement
-    )
+    if args.custom_path != "":
+        params = get_custom_design_params(args)
+    else:
+        params = get_single_design_params(
+            args.dataset_root, args.dataset, args.design_name, placement
+        )
     parser = IOParser()
     if args.load_from_raw:
         logger.info("loading from original benchmark...")

src/param_scheduler.py

@@ -525,7 +525,7 @@ class ParamScheduler:
 
 
     def visualize(self, args, logger):
-        file_prefix = "%s/%s_ms_" % (args.dataset, args.design_name)
+        file_prefix = "%s_" % args.design_name
         res_root = os.path.join(args.result_dir, args.exp_id)
         prefix = os.path.join(res_root, args.eval_dir, file_prefix)
         if not os.path.exists(os.path.dirname(prefix)):

utils/__init__.py

@@ -3,5 +3,5 @@ from .timer import Timer
 from .logger import setup_logger
 from .visualization import *
 from .tools import *
-from .get_design_params import get_single_design_params, get_multiple_design_params
+from .get_design_params import get_single_design_params, get_multiple_design_params, get_custom_design_params
 from .setup_dataset import setup_dataset_args

utils/get_design_params.py

@@ -131,3 +131,17 @@ def single_iccad2019(dataset_root, design_name, placement=None):
         "design_name": design_name,
     }
     return params
+
+
+def get_custom_design_params(args):
+    params = dict([
+        [item.strip() for item in token.strip().split(":")] 
+        for token in args.custom_path.split(",") if len(token) > 0
+    ])
+    if "benchmark" not in params.keys():
+        raise ValueError("Cannot find 'benchmark' in args.custom_path")
+    if "design_name" not in params.keys():
+        raise ValueError("Cannot find 'design_name' in args.custom_path")
+    args.dataset = params["benchmark"]
+    args.design_name = params["design_name"]
+    return params