--- /dev/null
+.. _intro_concepts:
+
+Main Concepts
+=============
+
+Typical Study based on SimGrid
+------------------------------
+
+.. raw:: html
+
+ <object data="graphical-toc.svg" width="100%" type="image/svg+xml"></object>
+
+
+Any SimGrid study entails the following components:
+
+ - The studied **Application**. This can be either a distributed
+ algorithm described in our simple APIs, or a full featured real
+ parallel application using for example the MPI interface
+ :ref:`(more info) <application>`.
+
+ - The **Simulated Platform**. This is a description of a given
+ distributed system (machines, links, disks, clusters, etc). Most of
+ the platform files are written in XML althrough a Lua interface is
+ under development. SimGrid makes it easy to augment the Simulated
+ Platform with a Dynamic Scenario where for example the links are
+ slowed down (because of external usage) or the machines fail. You
+ have even support to specify the applicative workload that you want
+ to feed to your application
+ :ref:`(more info) <platform>`.
+
+ - 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 simulated platform. You need to specify
+ which process is mapped on which machine, along with their parameters
+ :ref:`(more info) <scenario>`.
+
+ - The **Platform Models**. They describe how the simulated platform
+ reacts to the actions of the application. For example, they compute
+ the time taken by a given communication on the simulated platform.
+ These models are already included in SimGrid, and you only need to
+ pick one and maybe tweak its configuration to get your results
+ :ref:`(more info) <models>`.
+
+These components are put together to run a **simulation**, that is an
+experiment or a probe. The result of one or many simulation provides
+an **outcome** (logs, visualization, or statistical analysis) that help
+answering the **question** targeted by this study.
+
+Here are some questions on which SimGrid is particularly relevant:
+
+ - **Compare an Application to another**. This is the classical use
+ case for scientists, who use SimGrid to test how the solution that
+ they contribute to compares to the existing solutions from the
+ literature.
+
+ - **Design the best [Simulated] Platform for a given Application.**
+ Tweaking the platform file is much easier than building a new real
+ platform for testing purpose. SimGrid also allows for the co-design
+ of the platform and the application by modifying both of them.
+
+ - **Debug Real Applications**. With real systems, is sometimes
+ difficult to reproduce the exact run leading to the bug that you
+ are tracking. With SimGrid, you are *clairvoyant* about your
+ *reproducible experiments*: you can explore every part of the
+ system, and your 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.
+
+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 blindly trust 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.
+
+To ease such questioning, 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 mileage 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.
+
+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 simulated platform under
+the experimental scenario.
+
+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 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 literally
+explore all possible outcomes by testing all possible message
+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
+scenario where B arrives first.
+
+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
+occurs, then another given event will occur in a finite amount of
+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 extent).
+
+The main limit of Model Checking lays in the huge amount of scenarios
+to explore. SimGrid tries to explore only non-redundant scenarios
+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 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 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 how much time it took or the amount of watts that were dissipated.
+
+Finally, the model checker only explores the interleavings of
+computations and communications. Other factors such as thread
+execution interleaving are not considered by the SimGrid model
+checker.
+
+The model checker may well miss existing issues, as it computes the
+possible outcomes *from a given initial situation*. There is no way to
+prove the correction of your application in all generality with this
+tool.
+
+**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
+what you are interested in. You are probably looking for a way to run
+each computation kernel only once, save on disk the time it takes and
+some other metadata. This code block can then be skipped in simulation
+and replaced by a synthetic block using the cached information. The
+simulated platform will take this block into account without requesting
+the real hosting machine to benchmark it.
+
+SimGrid Limits
+--------------
+
+This framework is by no means the perfect holly grail able to solve
+every problem on earth.
+
+**SimGrid scope is limited to distributed systems.** Real-time
+multi-threaded systems are out of scope. You could probably tweak
+SimGrid for such studies (or the framework could possibly be extended
+in this direction), but another framework specifically targeting such a
+use case would probably be more suited.
+
+**There is currently no support for wireless networks**.
+The framework could certainly be improved in this direction, but this
+still has to be done.
+
+**There is no perfect model, only models adapted to your study.**
+The SimGrid models target fast and large studies yet requesting
+realistic results. In particular, our models abstract away parameters
+and phenomena that are often irrelevant to the realism in our
+context.
+
+SimGrid is simply not intended to any study that would mandate the
+abstracted phenomenon. Here are some **studies that you should not do
+with SimGrid**:
+
+ - Studying the effect of L3 vs. L2 cache effects on your application
+ - Comparing kernel schedulers and policies
+ - Comparing variants of TCP
+ - Exploring pathological cases where TCP breaks down, resulting in
+ abnormal executions.
+ - Studying security aspects of your application, in presence of
+ malicious agents.
+
+SimGrid Success Stories
+-----------------------
+
+SimGrid was cited in over 1,500 scientific papers (according to Google
+Scholar). Among them
+`over 200 publications <https://simgrid.org/Usages.html>`_
+(written by about 300 individuals) use SimGrid as a scientific
+instrument to conduct their experimental evaluation. These
+numbers do not include the articles contributing to SimGrid.
+This instrument was used in many research communities, such as
+`High-Performance Computing <https://hal.inria.fr/inria-00580599/>`_,
+`Cloud Computing <http://dx.doi.org/10.1109/CLOUD.2015.125>`_,
+`Workflow Scheduling <http://dl.acm.org/citation.cfm?id=2310096.2310195>`_,
+`Big Data <https://hal.inria.fr/hal-01199200/>`_ and
+`MapReduce <http://dx.doi.org/10.1109/WSCAD-SSC.2012.18>`_,
+`Data Grid <http://ieeexplore.ieee.org/document/7515695/>`_,
+`Volunteer Computing <http://www.sciencedirect.com/science/article/pii/S1569190X17301028>`_,
+`Peer-to-Peer Computing <https://hal.archives-ouvertes.fr/hal-01152469/>`_,
+`Network Architecture <http://dx.doi.org/10.1109/TPDS.2016.2613043>`_,
+`Fog Computing <http://ieeexplore.ieee.org/document/7946412/>`_, or
+`Batch Scheduling <https://hal.archives-ouvertes.fr/hal-01333471>`_
+`(more info) <https://simgrid.org/Usages.html>`_.
+
+If your platform description is accurate enough (see
+`here <http://hal.inria.fr/hal-00907887>`_ or
+`there <https://hal.inria.fr/hal-01523608>`_),
+SimGrid can provide high-quality performance predictions. For example,
+we determined the speedup achieved by the Tibidabo ARM-based
+cluster before its construction
+(`paper <http://hal.inria.fr/hal-00919507>`_). In this case,
+some differences between the prediction and the real timings were due to
+misconfiguration or other problems with the real platform. 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.
+`BigDFT <http://bigdft.org>`_ (a massively parallel code
+computing the electronic structure of chemical elements developped by
+the CEA), `StarPU <http://starpu.gforge.inria.fr/>`_ (a
+Unified Runtime System for Heterogeneous Multicore Architectures
+developped by Inria Bordeaux) and
+`TomP2P <https://tomp2p.net/dev/simgrid/>`_ (a high performance
+key-value pair storage library developed at University of Zurich).
+Some of these applications enjoy large user communities themselves.
+
+.. LocalWords: SimGrid
+
