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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)
rsa flute salt

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 scripts
  • src: c++ source codes
    • examples: example application codes
    • other_methods: implemetation of other routing topology generation methods
    • salt: implementation of SALT
    • unittest: 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.

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