.. _intro_concepts:
-Main Concepts
-=============
-
+Introduction
+============
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-Introduction
-============
+Main Concepts
+-------------
Typical Study based on SimGrid
-------------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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
+ - 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
+ - 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
+ the platform files are written in XML but a new C++ programmatic
+ interface has recently been introduced. 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 even have 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
+ - 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
+ which process is mapped onto which machine, along with their parameters
:ref:`(more info) <scenario>`.
- - The **Platform Models**. They describe how the simulated platform
+ - 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
: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.
+experiment or a probe. Simulations produce **outcomes** (logs,
+visualization, or statistical analysis) that help to answer the
+**question** targeted by this study.
Here are some questions on which SimGrid is particularly relevant:
- **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
+ platform for testing purposes. 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
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.
+strive to double-check them. Likewise, :ref:`you should question the
+realism of your input configuration <howto_calibration>`, and we even
+encourage you to :ref:`doubt (and check) the provided performance models
+<howto_science>`.
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.
+merge the application, the platform, and the deployment altogether.
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
+the provided XML platform files, 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.
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
+You just provide the application and its deployment (number of
+processes and parameters), and the model checker will
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
+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
+This is a very powerful mode, where you can evaluate the correctness of
+your application. It can verify either **safety properties** (assertions)
+or **liveness 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
+The main limit of Model Checking lies 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
+your application fits the properties provided, 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
+application to never violate a given assertion 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.
+to know how much time it took or the number of watts that were dissipated.
Finally, the model checker only explores the interleavings of
computations and communications. Other factors such as thread
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
+prove the correctness of your application in full 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
+interested in the control flow. If your application applies filters to
+huge images split into 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
+each computational kernel only once, and record the time it takes to cache it.
+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.
+the actual hosting machine to benchmark it.
SimGrid Limits
---------------
+^^^^^^^^^^^^^^
-This framework is by no means the perfect holly grail able to solve
-every problem on earth.
+This framework is by no means the holy 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
+multi-threaded systems are out of this scope. You could probably tweak
+SimGrid for such studies (or the framework could 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**.
+**There is currently no support for 5G or LoRa 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.
+**There is no perfect model, only models adapted to your study.** The SimGrid
+models target fast and large studies, and yet they target realistic results. In
+particular, our models abstract away parameters and phenomena that are often
+irrelevant to reality 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**:
+SimGrid is obviously not intended for a study of any phenomenon that our
+abstraction removes. 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
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
+SimGrid was cited in over 3,000 scientific papers (according to Google
+Scholar). Among them,
+`over 500 publications <https://simgrid.org/usages.html>`_
+(written by hundreds of 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
`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>`_.
+`(more info) <https://simgrid.org/usages.html>`_.
If your platform description is accurate enough (see
`here <http://hal.inria.fr/hal-00907887>`_ or
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,
+misconfigurations 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
+computing the electronic structure of chemical elements developed 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).
+developed by Inria Bordeaux), and
+`TomP2P <https://tomp2p.net/dev/simgrid/>`_ (a high-performance
+key-value pair storage library developed at the University of Zurich).
Some of these applications enjoy large user communities themselves.
.. LocalWords: SimGrid
-
