name: aivika-distributed
version: 1.1.2
synopsis: Parallel distributed discrete event simulation module for the Aivika library
description:
This package extends the aivika-transformers [1] package and allows running parallel distributed simulations.
It uses an optimistic strategy known as the Time Warp method. To synchronize the global virtual time,
it uses Samadi's algorithm.
.
Moreover, this package uses the author's modification that allows recovering the distributed
simulation after temporary connection errors whenever possible. For that, you have to enable explicitly
the recovering mode and enable the monitoring of all logical processes including the specialized Time Server process
as it is shown in one of the test examples included in the distribution.
.
With the recovering mode enabled, you can try to build a distributed simulation using ordinary computers connected
via the ordinary net. For example, such a distributed model could even consist of computers located in different
continents of the Earth, where the computers could be connected through the Internet. Here the most exciting thing
is that this is the optimistic distributed simulation with possible rollbacks. It is assumed that optimistic methods
tend to better support the parallelism inherited in the models.
.
You can test the distributed simulation using your own laptop, although the package is still destined to be
used with a multi-core computer, or computers connected in the distributed cluster.
.
There are additional packages that allow you to run the distributed simulation experiments by using
the Monte-Carlo method. They allow you to save the simulation results in SQL databases and then generate a report
or a set of reports consisting of HTML pages with charts, histograms, links to CSV tables, summary statistics etc.
Please consult the AivikaSoft [3] website for more details.
.
Regarding the speed of simulation, the recent rough estimation is as follows. This estimation may change from
version to version. For example, in version 1.0 the rollback log was rewritten, which had a significant effect.
.
The distributed simulation module is slower up to 8-15 times in comparison with the sequential aivika [2] simulation
library using the equivalent sequential models. The lower estimation in 8 times is likely to correspond to complex
models. The upper estimation in 15 times will probably correspond to quite simple event-oriented and process-oriented
models, where the sequential module can be exceptionally fast. At the same time, the message passing between
the logical processes can dramatically decrease the speed of distributed simulation, especially if they cause rollbacks.
Thus, much depends on the distributed model itself.
.
When residing the logical processes in a computer with multi-core processor, you should follow the next recommendations.
You should reserve at least 1 core for each logical process, or even reserve 2 cores if the logical process extensively
sends and receives messages. Also you should additionally reserve at least 1 or 2 cores for each computational node.
These additional processor cores will be used by the GHC run-time system that includes the garbage collector as well.
The Aivika distributed module creates a huge amount of short-living small objects. Therefore, the garbage collector
needs at least one core to utilize efficiently these objects.
.
You should compile your code with options -O2 and -threaded, but then launch it with run-time options +RTS -N.
.
\[1] <http://hackage.haskell.org/package/aivika-transformers>
.
\[2] <http://hackage.haskell.org/package/aivika>
.
\[3] <http://www.aivikasoft.com>
.
category: Simulation
license: BSD3
license-file: LICENSE
copyright: (c) 2015-2017. David Sorokin <david.sorokin@gmail.com>
author: David Sorokin
maintainer: David Sorokin <david.sorokin@gmail.com>
homepage: http://www.aivikasoft.com
cabal-version: >= 1.6
build-type: Simple
tested-with: GHC == 7.10.1
extra-source-files: tests/Guard1.hs
tests/MachRep1.hs
tests/MachRep1Simple.hs
tests/MachRep1SimpleWithMonitoring.hs
tests/MachRep2.hs
tests/MachRep2Distributed.hs
tests/MachRep2DistributedReproducible.hs
tests/MachRep2DistributedReproducibleFaultTolerant.hs
tests/MachRep2DistributedWithMonitoring.hs
tests/MachRep2Reproducible.hs
tests/MachRep2Sync.hs
tests/MachRep2SyncIO.hs
tests/MachRep2WithMonitoring.hs
tests/SimpleLocalnetHelper.hs
tests/cluster.conf
CHANGELOG.md
library
exposed-modules: Simulation.Aivika.Distributed
Simulation.Aivika.Distributed.Optimistic
Simulation.Aivika.Distributed.Optimistic.DIO
Simulation.Aivika.Distributed.Optimistic.Guard
Simulation.Aivika.Distributed.Optimistic.Generator
Simulation.Aivika.Distributed.Optimistic.QueueStrategy
Simulation.Aivika.Distributed.Optimistic.Message
Simulation.Aivika.Distributed.Optimistic.Priority
Simulation.Aivika.Distributed.Optimistic.Ref.Base
Simulation.Aivika.Distributed.Optimistic.Ref.Base.Lazy
Simulation.Aivika.Distributed.Optimistic.Ref.Base.Strict
Simulation.Aivika.Distributed.Optimistic.State
Simulation.Aivika.Distributed.Optimistic.TimeServer
other-modules: Simulation.Aivika.Distributed.Optimistic.Internal.Channel
Simulation.Aivika.Distributed.Optimistic.Internal.DIO
Simulation.Aivika.Distributed.Optimistic.Internal.Event
Simulation.Aivika.Distributed.Optimistic.Internal.Expect
Simulation.Aivika.Distributed.Optimistic.Internal.InputMessageQueue
Simulation.Aivika.Distributed.Optimistic.Internal.IO
Simulation.Aivika.Distributed.Optimistic.Internal.KeepAliveManager
Simulation.Aivika.Distributed.Optimistic.Internal.Message
Simulation.Aivika.Distributed.Optimistic.Internal.OutputMessageQueue
Simulation.Aivika.Distributed.Optimistic.Internal.Priority
Simulation.Aivika.Distributed.Optimistic.Internal.Ref
Simulation.Aivika.Distributed.Optimistic.Internal.Ref.Lazy
Simulation.Aivika.Distributed.Optimistic.Internal.Ref.Strict
Simulation.Aivika.Distributed.Optimistic.Internal.SignalHelper
Simulation.Aivika.Distributed.Optimistic.Internal.TimeServer
Simulation.Aivika.Distributed.Optimistic.Internal.TimeWarp
Simulation.Aivika.Distributed.Optimistic.Internal.TransientMessageQueue
Simulation.Aivika.Distributed.Optimistic.Internal.UndoableLog
build-depends: base >= 4.6.0.0 && < 6,
mtl >= 2.1.1,
array >= 0.3.0.0,
stm >= 2.4.2,
random >= 1.0.0.3,
mwc-random >= 0.13.0.0,
binary >= 0.6.4.0,
time >= 1.5.0.1,
containers >= 0.4.0.0,
exceptions >= 0.8.0.2,
distributed-process >= 0.6.1,
aivika >= 5.3.1,
aivika-transformers >= 5.3.1
extensions: MultiParamTypeClasses,
FlexibleInstances,
FlexibleContexts,
TypeFamilies,
RankNTypes,
DeriveGeneric,
DeriveDataTypeable,
OverlappingInstances,
MonoLocalBinds
ghc-options: -O2
source-repository head
type: git
location: https://github.com/dsorokin/aivika-distributed