Awesome
SALT
SALT (Steiner shAllow-Light Tree) is for generating VLSI routing topology. It trades off between path length (shallowness) and wirelength (lightness). More details are in ICCAD'17 paper.
Shallow | Light | SALT (shallow-light) |
---|---|---|
Quick Start
The simplest way to build and run SALT is as follows.
$ git clone https://github.com/chengengjie/salt
$ cd salt
$ ./scripts/build.py -o release
$ cd run
$ ./minimal_salt ../toys/toy1.net 1.0
To have a light installation of SALT in your own project, you only need to download folder src/salt
.
See the example for the usage.
Building SALT
Step 1: Download the source codes. For example,
$ git clone https://github.com/chengengjie/salt
Step 2: Go to the project root and build by
$ cd salt
$ ./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
.
Dependencies
- g++ (version >= 5.4.0) or other working c++ compliers
- CMake (version >= 3.5.1)
- Boost (version >= 1.58)
- Python (version 3, optional, for utility scripts)
Runing SALT
Toy
Go to the run
directory and run binary minimal_salt
with a toy net:
$ cd run
$ ./minimal_salt ../toys/toy1.net <epsilon>
The epsilon is the parameter controlling the trade-off between shallowness and lightness.
The output will be stored in file SALT_toy1.tree
.
You can visualize it by
$ ../scripts/draw.py SALT_toy1.tree
Besides, to compare with some other methods (e.g., FLUTE, KRY, BRBC, PD, etc) as well as some other variants of SALT (e.g., without post processing), you may run binary eval_single_salt
:
$ cd run
$ ./eval_single_salt -net ../toys/toy1.net -eps <epsilon>
Batch Test
First, a file of input nets is needed.
The nets extracted from ICCAD'15 Contest Problem B can be downloaded via Dropbox.
For an input file, run binary eval_batch_salt
:
$ cd run
$ ./eval_batch_salt <nets_file> <eval_file_suffix>
It constructs routing trees by several methods and epsilon values for each input net. The evaluation statistics will be written into several files. Each file summarizes the results for a specific range of # pins and a specific method, under various epsilon values and metrics (e.g., lightness, shallowness, delay, runtime, etc).
Unit Test
Run the build.py
with flag -u
at the project root:
$ ./scripts/build.py -u
Modules
scripts
: utility python scriptssrc
: c++ source codesexamples
: example application codesother_methods
: implemetation of other routing topology generation methodssalt
: implementation of SALTunittest
: unit test
toys
: toy benchmarks
File Formats
Net
Net <net_id> <net_name> <pin_num> [-cap]
0 x0 y0 [cap0]
1 x1 y1 [cap1]
...
An example is here.
Tree
Tree <net_id> <net_name> <pin_num> [-cap]
0 x0 y0 -1 [cap0]
1 x1 y1 parent_idx1 [cap1]
2 x2 y2 parent_idx2 [cap2]
...
k xk yk parent_idxk
...
An example is here. Note that tree nodes with indexes smaller than pin_num are pins, others are Steiner. Also, Steiner nodes have no capacitance.