dvcompute_branch

Crates.iodvcompute_branch
lib.rsdvcompute_branch
version2.0.0
sourcesrc
created_at2022-01-05 11:12:45.799002
updated_at2024-06-29 10:44:20.265545
descriptionDiscrete event simulation library (nested simulation)
homepagehttps://gitflic.ru/project/dsorokin/dvcompute
repositoryhttps://gitflic.ru/project/dsorokin/dvcompute
max_upload_size
id508321
size598,565
dsorokin (dsorokin)

documentation

README

dvcompute_branch

This crate is a part of discrete event simulation framework DVCompute Simulator (registration number 2021660590 of Rospatent). The dvcompute_branch crate is destined for nested simulation, but the same code base is shared by the dvcompute_dist crate destined for optimistic distributed simulation.

There are the following main crates: dvcompute (sequential simulation), dvcompute_dist (optimistic distributed simulation), dvcompute_cons (conservative distributed simulation) and dvcompute_branch (nested simulation). All four crates are very close. They are based on the same method.

Simulation Method

The main idea is to use continuations for modeling discontinuous processes. Such continuations are themselves wrapped in the monad, for which there are easy-to-use combinators. This idea is inspired by two sources: (1) combinators for futures that were in Rust before introducing the async/await syntax and (2) the Aivika simulation library that I developed in Haskell before.

Here is an example that defines a model of the machine that breaks down and then it is repaired:

const UP_TIME_MEAN: f64 = 1.0;
const REPAIR_TIME_MEAN: f64 = 0.5;

fn machine_process(total_up_time: Grc<RefComp<f64>>) -> ProcessBox<()> {
    let total_up_time2 = total_up_time.clone();
    random_exponential_process(UP_TIME_MEAN)
        .and_then(move |up_time| {
            RefComp::modify(total_up_time, move |total_up_time| {
                total_up_time + up_time
            })
            .into_process()
            .and_then(move |()| {
                random_exponential_process_(REPAIR_TIME_MEAN)
            })
            .and_then(move |()| {
                machine_process(total_up_time2)
            })
        })
        .into_boxed()
}

These computations are combined with help of the monadic bind. Such computations should be run later to take effect.

Examples

You can find examples in the author's repository.

Documentation

Tutorial

Also you can read the PDF document DVCompute Simulator Tutorial.

Bibliography

  • Sorokin David. DVCompute Simulator for discrete event simulation. Prikladnaya informatika=Journal of Applied Informatics, 2021, vol.16, no.3, pp.93-108 (in Russian). DOI: 10.37791/2687-0649-2021-16-3-93-108

Licence

Copyright 2020-2024 David Sorokin davsor@mail.ru, based in Yoshkar-Ola, Russia

This software is subject to the terms of the Mozilla Public License, v. 2.0. If a copy of the MPL was not distributed with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

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