CUGR is a VLSI global routing tool developed by the research team supervised by Prof. Evangeline F. Y. Young at The Chinese University of Hong Kong (CUHK). Different from previous global routers whose quality is usually measured by wirelength and resource overflow, CUGR is a detailed routability-driven global router and its solution quality is solely determined by the final detailed routing results. In particular, our global router adopts several efficient and effective methods to generate a set of connected rectangles to guide the detailed router:
- A sophisticated probability-based cost scheme
- An optimal 3D pattern routing technique that combines 2D pattern routing and layer assignment
- A multi-level maze routing utilizes two levels of routing
- A patching technique that adds useful route guides to further improve the detailed routability.
- ...
More details are in the following paper:
- Jinwei Liu, Chak-Wa Pui, Fangzhou Wang, Evangeline F. Y. Young, "CUGR: Detailed-Routability-Driven 3D Global Routing with Probabilistic Resource Model", ACM/IEEE Design Automation Conference (DAC), San Francisco, CA, USA, July 19-23, 2020.
(CUGR supports ICCAD'19 benchmarks (v2, hidden). This version of code is consistent with the DAC paper.)
Step 1: Download the source code. For example,
$ git clone https://github.com/cuhk-eda/cu-gr
Step 2: Go to the project root and build by
$ cd cu-gr
$ scripts/build.py -o release
Note that this will generate two folders under the root, build
and run
(build
contains intermediate files for build/compilation, while run
contains binaries and auxiliary files).
More details are in scripts/build.py
.
- GCC (version >= 5.5.0) or other working c++ compliers
- CMake (version >= 2.8)
- Boost (version >= 1.58)
- Python (version 3, optional, for utility scripts)
- Innovus® (version 18.1, optional, for design rule checking and evaluation)
- Rsyn (a trimmed version is used, already added under folder
rsyn
) - Dr. CU (v4.1.1, optional, official detailed router for ICCAD'19 Contest, binary is already included under the root)
Go to the run
directory and run the binary iccad19gr
with a toy case ispd18_sample
:
$ cd run
$ ./iccad19gr -lef ../toys/iccad2019c/ispd18_sample/ispd18_sample.input.lef -def ../toys/iccad2019c/ispd18_sample/ispd18_sample.input.def -output ispd18_sample.solution.guide -threads 8
Instead of running the binary directly, you may also use a wrapping script run.py
to save typing and do more:
$ cd run
$ ./run.py 8s -p ../toys/
If Innovus® has been properly installed in your OS, an evaluation can be launched by
$ ./run.py 8s -s eval -p ../toys/
In the end, a result table will be printed in the terminal.
Furthermore, the solution can be visualized by
$ ./run.py 8s -s view -p ../toys/
which gives:
The three steps, route
, eval
and view
of run.py
can also be invoked in a single line:
$ ./run.py 8s -s route eval view -p ../toys/
More usage about run.py
can be known by the option -h
.
The benchmarks can be downloaded from the hompage of ISPD'18 Contest .
You may let run.py
know the benchmark path by setting OS environmental variable BENCHMARK_PATH
or specifying it under option -p
.
Then,
$ cd run
$ ./run.py <benchmark_name...|all> -s route eval [option...]
ispd18eval
: scripts and other files for evaluation, provided by ICCAD'19 Contestispd19eval
: scripts and other files for evaluation, provided by ICCAD'19 Contestrsyn
: code from Rsyn for file IOscripts
: utility python scriptssrc
: C++ source codedb
: database, including the global grid graph and the net informationsingle_net
: routing a single net, including querying the global grid graph, building the local grid graph, running maze routing, and some post processingmulti_net
: routing all nets with "rip-up and rereoute" and multithreadingutils
: some utility code
toys
: toy test casesdrcu
: default detailed router for evaluation
Experiments are performed on a 64-bit Linux workstation with Intel Xeon Silver 4114 CPU (2.20GHz, 40 cores) and 256GB memory. Consistent with the contest, eight threads are used.
Design | Wire Length & Via | Non-Preferred Usage | Short | Min-Area & Spacing | DR Score | GR Runtime (sec) |
---|---|---|---|---|---|---|
ispd2018_test5 |
15613663 | 166994 | 330425 | 288500 | 16089196 | 68 |
ispd2018_test5_metal5 |
15807997 | 135293 | 261150 | 224000 | 16210303 | 85 |
ispd2018_test8 |
37441058 | 269993 | 209470 | 144000 | 37908815 | 236 |
ispd2018_test8_metal5 |
36746610 | 336768 | 194510 | 129500 | 37293962 | 300 |
ispd2018_test10 |
39061258 | 882371 | 669965 | 471000 | 40600501 | 334 |
ispd2018_test10_metal5 |
40246090 | 1413120 | 4021620 | 685500 | 46300610 | 373 |
ispd2019_test7 |
77286072 | 1428396 | 9680620 | 6883000 | 88577731 | 506 |
ispd2019_test7_metal5 |
70848996 | 1535876 | 9943260 | 6686000 | 82169293 | 377 |
ispd2019_test8 |
119199593 | 1338449 | 7780220 | 6103000 | 128412302 | 365 |
ispd2019_test8_metal5 |
116062781 | 1493314 | 8561400 | 6089000 | 126429212 | 588 |
ispd2019_test9 |
184246497 | 2181774 | 14765850 | 10847000 | 201270655 | 528 |
ispd2019_test9_metal5 |
179242111 | 2323850 | 16020280 | 10948000 | 197937335 | 658 |
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License Agreement for CUGR
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