RXPSC

This should just work after you run nix-shell.

Be careful to read through any of the files before you run them, e.g. bram_based_8bit.py has a hardcoded output path.

Workflow:

1. You need the software in shell.nix. It requires some of the scripts in my j-c-w/config.

Getting ANML files. This software works using ANML files, which seem hard to get directly from PCRE files. I provide a process below from which to generate MNRL and ANML files from PCRE files:

1. Create a PCRE (.regex) file. This is a format of one regex per line, e.g. '//'

2. Turn the pattern into a MNRL file: pcre2mnrl <inputfile> <outputfile (.mnrl)>

3. Turn MNRL into ANML: vasim <mnrl file> -a

#Running The run script is rxpsc.py, run that with --help to see the options.

##Modes There are several important modes, briefly described here (see the rxpsc help for more up to date detail)

1. Compression: Given a folder of folders, where each sub-folder contains an anml file, try to compress the regexes assuming that all the regexes in each folder must be run at the same time as the others in the same folder, but that they /do not/ have to run at the same time as regexes in different folders.
2. Addition: Given a set of regexes that have been implemented in hardware (possibly with prefix splitting), try to add another regex to that pre-compiled set
3. Various experimental modes. These modes are designed to help recreate published (or unpublished) experiments.

#Benchmarking Benchmarking scripts are in the temp_scripts/FCCM/benchmark_scripts/ folder. See the local README for more information in that folder for more information.

#On the Eddie Cluster Eddie sadly does not support nix super well. There is a script to setup a partial environment --- not good enough to do the whole setup, but good enough to run the python. Try eddie_setup.sh

Reference:

Jackson Woodruff and Michael F P O'Boyle. "New Regular Expressions on Old Accelerators." The 58th Design Automation Conference (DAC) 2021.

APSim

APSim is an automata processing simulator, implemented in python. It supports many essential automata compiling features such as automata minimization, automata transformation, fan in/out constraint, connected components extraction, static and run-time analysis, etc. APSim uses NetworkX as its underlying data straucture to maintain the automataon as a graph and run automaton processing algorithms to reshape the underlying graph.

Requirements

External dependencies: g++, swig, python OS: Linux, mac OS

1. Clone a fresh copy of the git APSim repository (git clone -b ASPLOS_AE https://github.com/gr-rahimi/APSim.git).

2. Download and Install Anaconda (python 2.7)

3. Install the following python packages using all available in Anaconda repositories:

   sortedcontainers, numpy, matplotlib, pathos, networkx, deap, tqdm, Jinja2, pygraphviz

   conda install -c conda-forge sortedcontainers matplotlib pathos deap tqdm

   conda install -c anaconda jinja2 pygraphviz networkx pygraphviz numpy

Install

4. Go to the CPP folder and run the compile script with python include directoy path. For example:

   ./compile ~/anaconda2/include/python2.7/

5. Add APSim to your PYTHONPATH

   export PYTHONPATH=$PYTHONPATH:/home/foo/APSim

6. Clone a fresh copy of ANMLZoo

   git clone https://github.com/gr-rahimi/ANMLZoo.git

7. Update the variable ANMLZoo's address path in APSim's module automata/AnmalZoo/anml_zoo.py variable _base_address

Usage

There are some scripts available in the "Example" folder replicating main experiments in the paper. Run each of them using the following command python <script name>

Reference