Code repository for master thesis about example-driven DSML design http://msdl.cs.mcgill.ca/people/lucas

Yentl Van Tendeloo 793d027c74 Updated results to be in milliseconds 7 年 前
bootstrap 6ced80d6da Switch to fast-jit for everything, and take into account purging (GC) in DEVS model 7 年 前
calibration 793d027c74 Updated results to be in milliseconds 7 年 前
doc 39d817bbc9 Add generation scripts for the pdf of the dot files 7 年 前
hybrid_server 56a15b627f Semi-working automatically generated Modelverse Kernel 7 年 前
integration 6ced80d6da Switch to fast-jit for everything, and take into account purging (GC) in DEVS model 7 年 前
interface fa447d7311 Patched exporting to Graphviz 7 年 前
kernel 90aed1ad57 Use minimal PDEVS simulation kernel for decent performance 7 年 前
model 793d027c74 Updated results to be in milliseconds 7 年 前
models 42fb0e82cd Updated model_overwrite: only the megamodelling version remains, and explicitly takes the required metamodel 7 年 前
scripts 953439a5e2 Minor tweaks to add all performance benchmarks in 7 年 前
services 96fff1b2a5 Initial RRD support for rule generation 7 年 前
state 990561a052 Added a rudimentary form of None... 7 年 前
unit d47504ce7f Preliminary working version of parallel process enactment 7 年 前
wrappers fca8141de0 Updated with realistic results from server 7 年 前
.gitattributes b3d374390d Make .gz files merge properly 8 年 前
.gitignore a804676c3b Merge branch 'testing' into MvK_rules 7 年 前
README.md 592282cbcf Massive cleanup 8 年 前
sum_times.py bfcb1fb5d4 More general code to sum times 8 年 前

README.md

Installation

Installing the Modelverse is unnecessary, as it is mere Python code and doesn't use installation scripts. All scripts which are generally useful are found in the 'scripts' directory, and are written in OS-independent Python code.

You will, however, need to install a dependency: the SCCD compiler and runtime.

Starting up the Modelverse

Starting up the Modelverse is easy: simply execute the scripts/run_local_modelverse.py script, with as parameter the port you want to use. By default, port 8001 is used.

Communicating with the Modelverse

Now that the Modelverse is running, you will want to communicate with it! To do this, you can use whatever tool you want, as long as it can send and receive XML/HTTPRequests. For example, a mere internet browser can already communicate with the Modelverse, though not in the most user-friendly way.

A nicer way is through the Python prompt script scripts/prompt.py. After that, it will print out all the output of the Modelverse, and send in all your queries directly to the Modelverse.

Python wrapper

To automatically communicate with the Modelverse in a programmatic way, a Python wrapper is provided. This wrapper is found in wrappers/modelverse.py, and provides Python functions that make the necessary Modelverse requests. At the moment, not all functions are implemented in the wrapper yet.

Performance

Performance of the Modelverse is currently rather low. This is primarily caused by the reliance on the action language, which is an explicitly modelled (and interpreted) language. Additionally, the Modelverse runs remotely, meaning that all requests have to pass over the network. Even when this is executed on the same machine, this causes quite some overhead.

Additional documentation

Some additional documentation can be found online in the Modelverse techreport, describing the internal workings of the Modelverse, as well as a brief introduction on how to use it. There is also in-depth documentation describing how to use the Modelverse and its various languages.

Tests

Running the tests is easy: simply execute scripts/run_tests.py in the main modelverse folder. This will invoke the necessary build commands (to create bootstrapping code etc.) and call the tests for each individual aspect of the Modelverse. Note that testing is done using py.test, which is the only dependency of the Modelverse (and only for tests, of course).

Using PyPy

Since all scripts chain the invocation with the same interpreter as originally invoking the script, you will need to install py.test for PyPy. Assuming that you already have PyPy installed, you can simply install py.test using these commands:

wget https://msdl.uantwerpen.be/files/get-pip.py
pypy get-pip.py --user
pypy -m pip install pytest --user

From then on, you can simply invoke all tests in PyPy using:

pypy scripts/run_tests.py