It can be used to either assess abstract algorithms, or to profile and
debug real distributed applications. SimGrid enables studies in the
-domains of (data-)Grids, Clusters, IaaS Clouds, High Performance
-Computing, Volunteer Computing and Peer-to-Peer.
+domains of (data-)Grids, IaaS Clouds, Clusters, High Performance
+Computing, Volunteer Computing and Peer-to-Peer systems.
-Technically speaking, SimGrid is a library. It is not a graphical
-interface nor a command-line simulator running user scripts. You
-interact with SimGrid by writting programs with the exposed functions
-to build your own simulator.
+Technically speaking, SimGrid is a library. It is neither a graphical
+interface nor a command-line simulator running user scripts. The
+interaction with SimGrid is done by writing programs with the exposed
+functions to build your own simulator.
-SimGrid have many features, many options and many possibilities. The
+SimGrid offers many features, many options and many possibilities. The
documentation aims at smoothing the learning curve. But nothing's
perfect, and this documentation is really no exception here. Please
-help us improving it by reporting the issues that you see and
+help us improving it by reporting any issue that you see and
proposing the content that is still missing.
-SimGrid is a Free Software distributed under the LGPL licence. It
-means that you are welcome to use it as you wish, or even to modify
-and distribute your version (as long as your version is as free as
-ours). It also means that SimGrid is developed by a vivid community of
-users and developers. We hope that you will come and join us!
+SimGrid is a Free Software distributed under the LGPL licence. You are
+thus welcome to use it as you wish, or even to modify and distribute
+your version (as long as your version is as free as ours). It also
+means that SimGrid is developed by a vivid community of users and
+developers. We hope that you will come and join us!
SimGrid is the result of over 15 years of research from several
-groups, both in France and in the USA. It benefited of many fundings
+groups, both in France and in the USA. It benefited of many funding
from various research instances, including the ANR, Inria, CNRS,
University of Lorraine, University of Hawai'i at Manoa, ENS Rennes and
-many others. Many thanks to our generous donators!
+many others. Many thanks to our generous sponsors!
@section starting_components Typical Study based on SimGrid
- The studied **Application**. This can be either a distributed
algorithm described in our simple APIs, or a full featured real
- parallel application using the MPI interface (or other).
+ parallel application using for example the MPI interface
+ @ref application "(more info)".
- The **Virtual Platform**. This is a description of a given
distributed system (machines, links, disks, clusters, etc). Most of
Platform with a Dynamic Scenario where for example the links are
slowed down (because of external usage), the machines fail. You
have even support to specify the applicative workload that you want
- to feed to your application.
+ to feed to your application @ref platform "(more info)".
- - The application's **Deployment Description**. In SimGrid terminology,
- the application is an inert set of source files and binaries. To
- make it run, you have to describe how your application should be
- deployed on the virtual platform. Specify which process is located
- on which host, along with its parameters.
+ - The application's **Deployment Description**. In SimGrid
+ terminology, the application is an inert set of source files and
+ binaries. To make it run, you have to describe how your application
+ should be deployed on the virtual platform. You need to specify
+ which process is mapped on which host, along with their parameters
+ @ref deployment "(more info)".
- The **Platform Models**. They describe how the virtual platform
reacts to the actions of the application. For example, they compute
the time taken by a given communication on the virtual platform.
These models are already included in SimGrid, and you only need to
- pick one and maybe tweak its configuration to get your results.
+ pick one and maybe tweak its configuration to get your results
+ @ref models "(more info)".
These components are put together to run a **simulation**, that is an
experiment or a probe. The result of one or many simulation provides
probe will not change the simulated state). It also makes it easy
to mock some parts of the real system that are not under study.
-@section starting_gears SimGrid Execution Gears
+Depending on the context, you may see some parts of this process as
+less important, but you should pay close attention if you want to be
+confident in the results coming out of your simulations. In
+particular, you should not trust blindly your results but always
+strive to double-check them. Likewise, you should question the realism
+of your input configuration, and we even encourage you to doubt (and
+check) the provided performance models.
-Depending on the intended study, SimGrid can be run in several gears,
-that are different execution modes.
+To ease such questionning, you really should logically separate these
+parts in your experimental setup. It is seen as a very bad practice to
+merge the application, the platform and the deployment all together.
+SimGrid is versatile and your milleage may vary, but you should start
+with your Application specified as a C++ or Java program, using one of
+the provided XML platform file, and with your deployment in a separate
+XML file.
-** **Simulation Gear**. This is the most common gear, where you want
+@section starting_gears SimGrid Execution Modes
+
+Depending on the intended study, SimGrid can be run in several execution modes.
+
+** **Simulation Mode**. This is the most common execution mode, where you want
to study how your application behaves on the virtual platform under
the experimental scenario.
-
-In this gear, SimGrid can provide information about the time taken by
+
+In this mode, SimGrid can provide information about the time taken by
your application, the amount of energy dissipated by the platform to
run your application and the detailed usage of each resource.
-
-** **Model-Checking Gear**. This can be seen as a sort of exhaustive
-testing gear, where every possible outcome of your application is
-explored. In some sense, this gear tests your application for all
+
+** **Model-Checking Mode**. This can be seen as a sort of exhaustive
+testing mode, where every possible outcome of your application is
+explored. In some sense, this mode tests your application for all
possible platforms that you could imagine (and more).
-
+
You just provide the application and its deployment (amount of
processes and parameters), and the model-checker will litterally
explore all possible outcomes by testing all possible message
-interleaving: if at some point a given process can either receive the
+interleavings: if at some point a given process can either receive the
message A first or the message B depending on the platform
characteristics, the model-checker will explore the scenario where A
arrives first, and then rewind to the same point to explore the
-scenarion where B arrives first.
+scenario where B arrives first.
-This is a very powerful gear, where you can evaluate the correction of
-your application. It can verify either *safety properties* (asserts)
-or *liveless properties* stating for example that if a given event
+This is a very powerful mode, where you can evaluate the correction of
+your application. It can verify either **safety properties** (asserts)
+or **liveless properties** stating for example that if a given event
occures, then another given event will occur in a finite amount of
-steps. This gear is not only usable with the abstract algorithms
+steps. This mode is not only usable with the abstract algorithms
developed on top of the SimGrid APIs, but also with real MPI
applications (to some extend).
The main limit of Model Checking lays in the huge amount of scenarios
to explore. SimGrid tries to explore only non-redundent scenarios
-thanks to classical reduction techniques (such as DPOR and statefull
+thanks to classical reduction techniques (such as DPOR and stateful
exploration) but the exploration may well never finish if you don't
-carefully adapt your application to this gear.
+carefully adapt your application to this mode.
+
+A classical trap is that the Model Checker can only verify whether
+your application fits the provided properties, which is useless if you
+have a bug in your property. Remember also that one way for your
+application to never violate a given assert is to not start at all
+because of a stupid bug.
-Another limit of this gear is that it does not use the performance
-models of the simulation gear. Time becomes discrete: You can say for
+Another limit of this mode is that it does not use the performance
+models of the simulation mode. Time becomes discrete: You can say for
example that the application took 42 steps to run, but there is no way
to know the amount of seconds that it took or the amount of watts that
it dissipated.
prove the correction of your application in all generality with this
tool.
-** **Benchmark Recording Gear**. During debug sessions, continuous
+** **Benchmark Recording Mode**. During debug sessions, continuous
integration testing and other similar use cases, you are often only
interested in the control flow. If your application apply filters to
huge images split in small blocks, the filtered image is probably not
virtual platform will take this block into account without requesting
the real hosting machine to benchmark it.
-@section starting_successes SimGrid Success Stories
-
-TBD
-
-- Many publications
-- Accurate speedup prediction for the Mont-Blanc cluster
-- It already happened that a divergence between the simulated outcome
- and the reality resulted from a testbed misconfiguration. In some
- sense, we fixed the reality because it was not getting the result
- that SimGrid correctly computed :)
-- Star-PU, BigDFT, TomP2P use SimGrid to chase their bugs and improve
- their efficiency.
-
@section starting_limits SimGrid Limits
This framework is by no means the perfect holly grail able to solve
- Studying security aspects of your application, in presence of
malicious agents.
+@section starting_successes SimGrid Success Stories
+
+SimGrid was cited in over 1,500 scientific papers (according to Google
+Scholar). Among them
+<a href="http://simgrid.gforge.inria.fr/Usages.php">over 200
+publications</a> (written by about 300 individuals) use SimGrid as a
+scientific instrument to conduct their experimental evaluation. These
+numbers do not count the articles contributing to SimGrid.
+This instrument was used in many research communities, such as
+<a href="https://hal.inria.fr/inria-00580599/">High-Performance Computing</a>,
+<a href="http://dx.doi.org/10.1109/CLOUD.2015.125">Cloud Computing</a>,
+<a href="http://dl.acm.org/citation.cfm?id=2310096.2310195">Workflow Scheduling</a>,
+<a href="https://hal.inria.fr/hal-01199200/">Big Data</a> and
+<a href="http://dx.doi.org/10.1109/WSCAD-SSC.2012.18">MapReduce</a>,
+<a href="http://ieeexplore.ieee.org/document/7515695/">Data Grid</a>,
+<a href="http://www.sciencedirect.com/science/article/pii/S1569190X17301028">Volunteer Computing</a>,
+<a href="https://hal.archives-ouvertes.fr/hal-01152469/">Peer-to-Peer Computing</a>,
+<a href="http://dx.doi.org/10.1109/TPDS.2016.2613043">Network Architecture</a>,
+<a href="http://ieeexplore.ieee.org/document/7946412/">Fog Computing</a>, or
+<a href="https://hal.archives-ouvertes.fr/hal-01333471">Batch Scheduling</a>
+<a href="http://simgrid.gforge.inria.fr/Usages.php"><b>(more info)</b></a>.
+
+If your platform description is accurate enough (see
+<a href="http://hal.inria.fr/hal-00907887">here</a> or
+<a href="https://hal.inria.fr/hal-01523608">there</a>),
+SimGrid can provide high-quality performance predictions. For example,
+we determined the speedup achieved by the Tibidabo Arm-based
+cluster before its construction
+(<a href="http://hal.inria.fr/hal-00919507">paper</a>). In this case,
+some differences between the prediction and the real timings were due to
+misconfiguration or other problems with the real platforms. To some extent,
+SimGrid could even be used to debug the real platform :)
+
+SimGrid is also used to debug, improve and tune several large
+applications.
+<a href="http://bigdft.org">BigDFT</a> (a massively parallel code
+computing the electronic structure of chemical elements developped by
+the CEA), <a href="http://starpu.gforge.inria.fr/">StarPU</a> (a
+Unified Runtime System for Heterogeneous Multicore Architectures
+developped by Inria Bordeaux) and
+<a href="https://tomp2p.net/dev/simgrid/">TomP2P</a> (a high performance
+key-value pair storage library developped at University of Zurich).
+Some of these applications enjoy large user communities themselves.
+
@section starting_next Where to proceed next?
Now that you know about the basic concepts of SimGrid, you can give it
