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Merge pull request #580 from peastman/docs 

Updates to documentation for 6.1
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# Makefile for Sphinx documentation
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# -*- coding: utf-8 -*-
#
# OpenMM Developer Guide documentation build configuration file, created by
# sphinx-quickstart on Fri Feb 7 12:42:06 2014.
#
# This file is execfile()d with the current directory set to its containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
import sys, os
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
sys.path.insert(0, os.path.abspath('.'))
sys.path.append(os.path.abspath('../sphinx'))
# -- General configuration -----------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
#needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be extensions
# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
extensions = ['autonumber', 'numsec']
# Add any paths that contain templates here, relative to this directory.
templates_path = ['_templates']
# The suffix of source filenames.
source_suffix = '.rst'
# The encoding of source files.
#source_encoding = 'utf-8-sig'
# The master toctree document.
master_doc = 'index'
# General information about the project.
project = u'OpenMM Developer Guide'
copyright = u'2011-2014, Stanford University'
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
version = os.getenv('OPENMM_VERSION')
# The full version, including alpha/beta/rc tags.
release = os.getenv('OPENMM_VERSION')
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#language = None
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
#today = ''
# Else, today_fmt is used as the format for a strftime call.
#today_fmt = '%B %d, %Y'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
exclude_patterns = ['_build']
# The reST default role (used for this markup: `text`) to use for all documents.
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# If true, '()' will be appended to :func: etc. cross-reference text.
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# If true, the current module name will be prepended to all description
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# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
# -- Options for HTML output ---------------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
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html_theme = 'agogo'
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
#html_theme_options = {}
# Add any paths that contain custom themes here, relative to this directory.
#html_theme_path = []
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
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#html_favicon = None
# Add any paths that contain custom static files (such as style sheets) here,
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html_static_path = ['_static']
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#html_file_suffix = None
# Output file base name for HTML help builder.
htmlhelp_basename = 'OpenMMDeveloperGuidedoc'
# -- Options for LaTeX output --------------------------------------------------
latex_elements = {
# The paper size ('letterpaper' or 'a4paper').
#'papersize': 'letterpaper',
# The font size ('10pt', '11pt' or '12pt').
#'pointsize': '10pt',
# Additional stuff for the LaTeX preamble.
'preamble': """
\\usepackage[none]{hyphenat}
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latex_documents = [
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u'Peter Eastman', 'manual'),
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# For "manual" documents, if this is true, then toplevel headings are parts,
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# If true, show page references after internal links.
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# If true, show URL addresses after external links.
#latex_show_urls = False
# Documents to append as an appendix to all manuals.
#latex_appendices = []
# If false, no module index is generated.
#latex_domain_indices = True
# -- Options for manual page output --------------------------------------------
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
('index', 'openmmdeveloperguide', u'OpenMM Developer Guide',
[u'Peter Eastman'], 1)
]
# If true, show URL addresses after external links.
#man_show_urls = False
# -- Options for Texinfo output ------------------------------------------------
# Grouping the document tree into Texinfo files. List of tuples
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
('index', 'OpenMMDeveloperGuide', u'OpenMM Developer Guide',
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'Miscellaneous'),
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# Documents to append as an appendix to all manuals.
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#texinfo_domain_indices = True
# How to display URL addresses: 'footnote', 'no', or 'inline'.
#texinfo_show_urls = 'footnote'
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.. role:: code
.. raw:: html
<style> .code {font-family:monospace;} </style>
<style> .caption {text-align:center;} </style>
.. highlight:: c++
Introduction
############
This guide describes the internal architecture of the OpenMM library. It is
targeted at developers who want to add features to OpenMM, either by modifying
the core library directly or by writing plugins. If you just want to write
applications that use OpenMM, you do not need to read this guide; the Users
Manual tells you everything you need to know. This guide is *only* for
people who want to contribute to OpenMM itself.
It is organized as follows:
* Chapter :ref:`the-core-library` describes the architecture of the core OpenMM library. It
discusses how the high level and low level APIs relate to each other, and the
flow of execution between them.
* Chapter :ref:`writing-plugins` describes in detail how to write a plugin. It focuses on the two
most common types of plugins: those which define new Forces, and those which
implement new Platforms.
* Chapter :ref:`the-reference-platform` discusses the architecture of the reference Platform, providing
information relevant to writing reference implementations of new features.
* Chapter :ref:`the-cpu-platform` discusses the architecture of the CPU Platform, providing
information relevant to writing CPU implementations of new features.
* Chapter :ref:`the-opencl-platform` discusses the architecture of the OpenCL Platform, providing
information relevant to writing OpenCL implementations of new features.
* Chapter :ref:`the-cuda-platform` discusses the architecture of the CUDA Platform, providing
information relevant to writing CUDA implementations of new features.
This guide assumes you are already familiar with the public API and how to use
OpenMM in applications. If that is not the case, you should first read the
Users Manual and work through some of the example programs. Pay especially
close attention to the “Introduction to the OpenMM Library” chapter, since it
introduces concepts that are important in understanding this guide.
.. _the-core-library:
The Core Library
################
OpenMM is based on a layered architecture, as shown in the following diagram:
.. figure:: ../images/ArchitectureLayers.jpg
:align: center
:width: 100%
:autonumber:`Figure,Architecture Layers`\ : OpenMM architecture
The public API layer consists of the classes you access when using OpenMM in an
application: System; Force and its subclasses; Integrator and its subclasses;
and Context. These classes define a public interface but do no computation.
The next layer down consists of “implementation” classes that mirror the public
API classes: ContextImpl, ForceImpl, and a subclass of ForceImpl for each
subclass of Force (HarmonicBondForceImpl, NonbondedForceImpl, etc.). These
objects are created automatically when you create a Context. They store
information related to a particular simulation, and define methods for
performing calculations.
Note that, whereas a Force is logically “part of” a System, a ForceImpl is
logically “part of” a Context. (See :numref:`Figure,API Relationships`\ .) If you create many Contexts
for simulating the same System, there is still only one System and only one copy
of each Force in it. But there will be separate ForceImpls for each Context,
and those ForceImpls store information related to their particular Contexts.
.. figure:: ../images/SystemContextRelationships.jpg
:align: center
:autonumber:`Figure,API Relationships`\ : Relationships between public API and implementation layer objects
Also note that there is no “IntegratorImpl” class, because it is not needed.
Integrator is already specific to one Context. Many Contexts can all simulate
the same System, but each of them must have its own Integrator, so information
specific to one simulation can be stored directly in the Integrator.
The next layer down is the OpenMM Low Level API (OLLA). The important classes
in this layer are: Platform; Kernel; KernelImpl and its subclasses; and
KernelFactory. A Kernel is just a reference counted pointer to a KernelImpl;
the real work is done by KernelImpl objects (or more precisely, by instances of
its subclasses). A KernelFactory creates KernelImpl objects, and a Platform
ties together a set of KernelFactories, as well as defining information that
applies generally to performing computations with that Platform.
All of these classes (except Kernel) are abstract. A particular Platform
provides concrete subclasses of all of them. For example, the reference
platform defines a Platform subclass called ReferencePlatform, a KernelFactory
subclass called ReferenceKernelFactory, and a concrete subclass of each abstract
KernelImpl type: ReferenceCalcNonbondedForceKernel extends
CalcNonbondedForceKernel (which in turn extends KernelImpl),
ReferenceIntegrateVerletStepKernel extends IntegrateVerletStepKernel, and so on.
We can understand this better by walking through the entire sequence of events
that takes place when you create a Context. As an example, suppose you create a
System; add a NonbondedForce to it; create a VerletIntegrator; and then create a
Context for them using the reference Platform. Here is what happens.
#. The Context constructor creates a ContextImpl.
#. The ContextImpl calls :code:`createImpl()` on each Force in the System,
which creates an instance of the appropriate ForceImpl subclass.
#. The ContextImpl calls :code:`contextCreated()` on the Platform(), which
in turn calls :code:`setPlatformData()` on the ContextImpl. This allows
Platform-specific information to be stored in a ContextImpl. Every Platform has
its own mechanism for storing particle masses, constraint definitions, particle
positions, and so on. ContextImpl therefore allows the Platform to create an
arbitrary block of data and store it where it can be accessed by that Platform’s
kernels.
#. The ContextImpl calls :code:`createKernel()` on the Platform several
times to get instances of various kernels that it needs:
CalcKineticEnergyKernel, ApplyConstraintsKernel, etc.
#. For each kernel, the Platform looks up which KernelFactory has been
registered for that particular kernel. In this case, it will be a
ReferenceKernelFactory.
#. It calls :code:`createKernelImpl()` on the KernelFactory, which
creates and returns an instance of an appropriate KernelImpl subclass:
ReferenceCalcKineticEnergyKernel, ReferenceApplyConstraintsKernel, etc.
#. The ContextImpl loops over all of its ForceImpls and calls
:code:`initialize()` on each one.
#. Each ForceImpl asks the Platform to create whatever kernels it needs. In
this example, NonbondedForceImpl will request a CalcNonbondedForceKernel, and
get back a ReferenceCalcNonbondedForceKernel.
#. The ContextImpl calls :code:`initialize()` on the Integrator which, like
the other objects, requests kernels from the Platform. In this example,
VerletIntegrator requests an IntegrateVerletStepKernel and gets back a
ReferenceIntegrateVerletStepKernel.
At this point, the Context is fully initialized and ready for doing computation.
Reference implementations of various KernelImpls have been created, but they are
always referenced through abstract superclasses. Similarly, data structures
specific to the reference Platform have been created and stored in the
ContextImpl, but the format and content of these structures is opaque to the
ContextImpl. Whenever it needs to access them (for example, to get or set
particle positions), it does so through a kernel (UpdateStateDataKernel in this
case).
Now suppose that you call :code:`step()` on the VerletIntegrator. Here is
what happens to execute each time step.
#. The VerletIntegrator calls :code:`updateContextState()` on the
ContextImpl. This gives each Force an opportunity to modify the state of the
Context at the start of each time step.
#. The ContextImpl loops over its ForceImpls and calls
:code:`updateContextState()` on each one. In this case, our only ForceImpl is
a NonbondedForceImpl, which returns without doing anything. On the other hand,
if we had an AndersenThermostat in our System, its ForceImpl would invoke a
kernel to modify particle velocities.
#. The VerletIntegrator calls :code:`calcForcesAndEnergy()` on the
ContextImpl to request that the forces be computed.
#. The ContextImpl calls :code:`beginComputation()` on its
CalcForcesAndEnergyKernel. This initializes all the forces to zero and does any
other initialization the Platform requires before forces can be computed. For
example, some Platforms construct their nonbonded neighbor lists at this point.
#. The ContextImpl loops over its ForceImpls and calls
:code:`calcForcesAndEnergy()` on each one. In this case, we have a
NonbondedForceImpl which invokes its CalcNonbondedForceKernel to compute forces.
#. Finally, the ContextImpl calls :code:`finishComputation()` on its
CalcForcesAndEnergyKernel. This does any additional work needed to determine
the final forces, such as summing the values from intermediate buffers.
#. Finally, the VerletIntegrator invokes its IntegrateVerletStepKernel. This
takes the forces, positions, and velocities that are stored in a Platform-
specific format in the ContextImpl, uses them to compute new positions and
velocities, and stores them in the ContextImpl.
.. _writing-plugins:
Writing Plugins
###############
A plugin is a dynamic library that adds new features to OpenMM. It is typically
stored in the :code:`lib/plugins` directory inside your OpenMM installation,
and gets loaded along with all other plugins when the user calls
::
Platform::loadPluginsFromDirectory(Platform::getDefaultPluginsDirectory());
It is also possible to load plugins from a different directory, or to load them
individually by calling :code:`Platform::loadPluginLibrary()`\ .
Every plugin must implement two functions that are declared in the
PluginInitializer.h header file:
::
extern "C" void registerPlatforms();
extern "C" void registerKernelFactories();
When a plugin is loaded, these two functions are invoked to register any
Platforms and KernelFactories defined by the plugin. When many plugins are
loaded at once by calling :code:`Platform::loadPluginsFromDirectory()`\ ,
:code:`registerPlatforms()` is first called on all of them, then
:code:`registerKernelFactories()` is called on all of them. This allows one
plugin to define a Platform, and a different plugin to add KernelFactories to
it; the Platform is guaranteed to be registered by the first plugin before the
second plugin tries to add its KernelFactories, regardless of what order the
plugins happen to be loaded in.
Creating New Platforms
**********************
One common type of plugin defines a new Platform. There are three such plugins
that come with OpenMM: one for the CPU Platform, one for the CUDA Platform, and
one for the OpenCL Platform.
To define a new Platform, you must create subclasses of the various abstract
classes in the OpenMM Low Level API: a subclass of Platform, one or more
subclasses of KernelFactory, and a subclass of each KernelImpl. That is easy to
say, but a huge amount of work to actually do. There are many different
algorithms involved in computing forces, enforcing constraints, performing
integration, and so on, all of which together make up a Platform. Of course,
there is no requirement that every Platform must implement every possible
feature. If you do not provide an implementation of a particular kernel, it
simply means your Platform cannot be used for any simulation that requires that
kernel; if a user tries to do so, an exception will be thrown.
Your plugin’s :code:`registerPlatforms()` function should create an instance
of your Platform subclass, then register it by calling
:code:`Platform::registerPlatform()`\ . You also must register the
KernelFactory for each kernel your Platform supports. This can be done in the
:code:`registerKernelFactories()` function, or more simply, directly in the
Platform’s constructor. You can use as many different KernelFactories as you
want for different kernels, but usually it is simplest to use a single
KernelFactory for all of them. The support for multiple KernelFactories exists
primarily to let plugins add new features to existing Platforms, as described in
the next section.
Creating New Forces
*******************
Another common type of plugin defines new Forces and provides implementations of
them for existing Platforms. (Defining new Integrators is not specifically
discussed here, but the process is very similar.) There are two such plugins
that come with OpenMM. They implement the AMOEBA force field and Drude
oscillators, respectively.
As an example, suppose you want to create a new Force subclass called
StringForce that uses the equations of String Theory to compute the interactions
between particles. You want to provide implementations of it for all four
standard platforms: Reference, CPU, CUDA, and OpenCL.
The first thing to realize is that this *cannot* be done with only a plugin
library. Plugins are loaded dynamically at runtime, and they relate to the low
level API; but you must also provide a public API. Users of your class need to
create StringForce objects and call methods on them. That means providing a
header file with the class declaration, and a (non-plugin) library with the
class definition to link their code against. The implementations for particular
Platforms can be in plugins, but the public API class itself cannot. Or to put
it differently, the full “plugin” (from the user’s perspective) consists of
three parts: the library OpenMM loads at runtime (which is what OpenMM considers
to be the “plugin”), a second library for users to link their code against, and
a header file for them to include in their source code.
To define the API, you will need to create the following classes:
#. StringForce. This is the public API for your force, and users will directly
link against the library containing it.
#. StringForceImpl. This is the ForceImpl subclass corresponding to
StringForce. It should be defined in the same library as StringForce, and
StringForce’s :code:`createImpl()` method should create an instance of it.
#. CalcStringForceKernel. This is an abstract class that extends KernelImpl,
and defines the API by which StringForceImpl invokes its kernel. You only need
to provide a header file for it, not an implementation; those will be provided
by Platforms.
Now suppose you are writing the OpenCL implementation of StringForce. Here are
the classes you need to write:
#. OpenCLCalcStringForceKernel. This extends CalcStringForceKernel and provides
implementations of its virtual methods. The code for this class will probably
be very complicated (and if it actually works, worth a Nobel Prize). It may
execute many different GPU kernels and create its own internal data structures.
But those details are entirely internal to your own code. As long as this class
implements the virtual methods of CalcStringForceKernel, you can do anything you
want inside it.
#. OpenCLStringForceKernelFactory. This is a KernelFactory subclass that knows
how to create instances of OpenCLCalcStringForceKernel.
Both of these classes should be packaged into a dynamic library (.so on Linux,
.dylib on Mac, .dll on Windows) that can be loaded as a plugin. This library
must also implement the two functions from PluginInitializer.h.
:code:`registerPlatforms()` will do nothing, since this plugin does not
implement any new Platforms. :code:`registerKernelFactories()` should call
\ :code:`Platform::getPlatformByName("OpenCL")` to get the OpenCL Platform,
then create a new OpenCLStringForceKernelFactory and call
:code:`registerKernelFactory()` on the Platform to register it. If the OpenCL
Platform is not available, you should catch the exception then return without
doing anything. Most likely this means there is no OpenCL runtime on the
computer your code is running on.
.. _the-reference-platform:
The Reference Platform
######################
The reference Platform is written with simplicity and clarity in mind, not
performance. (It is still not always as simple or clear as one might hope, but
that is the goal.) When implementing a new feature, it is recommended to create
the reference implementation first, then use that as a model for the versions in
other Platforms.
The reference Platform represents all floating point numbers with the type
RealOpenMM, which is defined in SimTKOpenMMRealType.h. This allows the entire
platform to be compiled in either single or double precision. By default it is
double precision, but it can be changed by modifying one flag at the top of that
file. The same file also defines lots of numerical constants and mathematical
functions, so the correct precision version will always be used. Vector
quantities (positions, velocities, etc.) are represented by RealVec objects.
This class is identical to Vec3, except that its components are of type
RealOpenMM instead of double.
When using the reference Platform, the “platform-specific data” stored in
ContextImpl is of type ReferencePlatform::PlatformData, which is declared in
ReferencePlatform.h. Several of the fields in this class are declared as void*
to avoid having to include SimTKOpenMMRealType.h in ReferencePlatform.h. If you
look in ReferenceKernels.cpp, you will find code for extracting the correct
values of these fields. For example:
::
static vector<RealVec>& extractPositions(ContextImpl& context) {
ReferencePlatform::PlatformData* data =
reinterpret_cast<ReferencePlatform::PlatformData*>(context.getPlatformData());
return *((vector<RealVec>*) data->positions);
}
The PlatformData’s vector of forces contains one element for each particle. At
the start of each force evaluation, all elements of it are set to zero. Each
Force adds its own contributions to the vector, so that at the end, it contains
the total force acting on each particle.
There are a few additional classes that contain useful static methods.
SimTKOpenMMUtilities has various utility functions, of which the most important
is a random number generator. ReferenceForce provides methods for calculating
the displacement between two positions, optionally taking periodic boundary
conditions into account.
.. _the-cpu-platform:
The CPU Plaform
###############
CpuPlatform is a subclass of ReferencePlatform. It provides optimized versions
of a small number of kernels, while using the reference implementations for all
the others. Any kernel implementation written for the reference Platform will
work equally well with the CPU platform. Of course, if that kernel happens to
be a performance bottleneck, you will probably want to write an optimized
version of it. But many kernels have negligible effect on performance, and for
these you can just use the same implementation for both platforms.
If you choose to do that, you can easily support both platforms with a single
plugin library. Just implement :code:`registerKernelFactories()` like this:
::
extern "C" void registerKernelFactories() {
for (int i = 0; i < Platform::getNumPlatforms(); i++) {
Platform& platform = Platform::getPlatform(i);
if (dynamic_cast<ReferencePlatform*>(&platform) != NULL) {
// Create and register your KernelFactory.
}
}
}
The loop identifies every ReferencePlatform, either an instance of the base
class or of a subclass, and registers a KernelFactory for every one.
.. _the-opencl-platform:
The OpenCL Platform
###################
The OpenCL Platform is much more complicated than the reference Platform. It
also provides many more tools to simplify your work, but those tools themselves
can be complicated to use correctly. This chapter will attempt to explain how
to use some of the most important ones. It will *not* teach you how to
program with OpenCL. There are many tutorials on that subject available
elsewhere, and this guide assumes you already understand it.
Overview
********
When using the OpenCL Platform, the “platform-specific data” stored in
ContextImpl is of type OpenCLPlatform::PlatformData, which is declared in
OpenCLPlatform.h. The most important field of this class is :code:`contexts`
, which is a vector of OpenCLContexts. (There is one OpenCLContext for each
device you are using. The most common case is that you are running everything
on a single device, in which case there will be only one OpenCLContext.
Parallelizing computations across multiple devices is not discussed here.) The
OpenCLContext stores most of the important information about a simulation:
positions, velocities, forces, an OpenCL CommandQueue used for executing
kernels, workspace buffers of various sorts, etc. It provides many useful
methods for compiling and executing kernels, clearing and reducing buffers, and
so on. It also provides access to three other important objects: the
OpenCLIntegrationUtilities, OpenCLNonbondedUtilities, and OpenCLBondedUtilities.
These are discussed below.
Allocation of device memory is generally done through the OpenCLArray class. It
takes care of much of the work of memory management, and provides a simple
interface for transferring data between host and device memory.
Every kernel is specific to a particular OpenCLContext, which in turn is
specific to a particular OpenMM::Context. This means that kernel source code
can be customized for a particular simulation. For example, values such as the
number of particles can be turned into compile-time constants, and specific
versions of kernels can be selected based on the device being used or on
particular aspects of the system being simulated.
:code:`OpenCLContext::createProgram()` makes it easy to specify a list of
preprocessor definitions to use when compiling a kernel.
The normal way to execute a kernel is by calling :code:`executeKernel()` on
the OpenCLContext. It allows you to specify the total number of work-items to
execute, and optionally the size of each work-group. (If you do not specify a
work-group size, it uses 64 as a default.) The number of work-groups to launch
is selected automatically based on the work-group size, the total number of
work-items, and the number of compute units in the device it will execute on.
Numerical Precision
*******************
The OpenCL platform supports three precision modes:
#. **Single**\ : All values are stored in single precision, and nearly all
calculations are done in single precision. The arrays of positions, velocities,
forces, and energies (returned by the OpenCLContext’s :code:`getPosq()`\ ,
:code:`getVelm()`\ , :code:`getForce()`\ , :code:`getForceBuffers()`\ , and
:code:`getEnergyBuffer()` methods) are all of type :code:`float4` (or
:code:`float` in the case of :code:`getEnergyBuffer()`\ ).
#. **Mixed**\ : Forces are computed and stored in single precision, but
integration is done in double precision. The velocities have type
:code:`double4`\ . The positions are still stored in single precision to avoid
adding overhead to the force calculations, but a second array of type
:code:`float4` is created to store “corrections” to the positions (returned by
the OpenCLContext’s getPosqCorrection() method). Adding the position and the
correction together gives the full double precision position.
#. **Double**\ : Positions, velocities, forces, and energies are all stored in
double precision, and nearly all calculations are done in double precision.
You can call :code:`getUseMixedPrecision()` and
:code:`getUseDoublePrecision()` on the OpenCLContext to determine which mode
is being used. In addition, when you compile a kernel by calling
:code:`createKernel()`\ , it automatically defines two types for you to make it
easier to write kernels that work in any mode:
#. :code:`real` is defined as :code:`float` in single or mixed precision
mode, :code:`double` in double precision mode.
#. :code:`mixed` is defined as :code:`float` in single precision mode,
:code:`double` in mixed or double precision mode.
It also defines vector versions of these types (\ :code:`real2`\ ,
:code:`real4`\ , etc.).
.. _computing-forces:
Computing Forces
****************
When forces are computed, they are stored in multiple buffers. This is done to
enable multiple work-items or work-groups to compute forces on the same particle
at the same time; as long as each one writes to a different buffer, there is no
danger of race conditions. At the start of a force calculation, all forces in
all buffers are set to zero. Each Force is then free to add its contributions
to any or all of the buffers. Finally, the buffers are summed to produce the
total force on each particle.
The size of each buffer is equal to the number of particles, rounded up to the
next multiple of 32. Call :code:`getPaddedNumAtoms()` on the OpenCLContext
to get that number. The actual force buffers are obtained by calling
:code:`getForceBuffers()`\ . The first *n* entries (where *n* is the
padded number of atoms) represent the first force buffer, the next *n*
represent the second force buffer, and so on. More generally, the *i*\ ’th
force buffer’s contribution to the force on particle *j* is stored in
element :code:`i*context.getPaddedNumAtoms()+j`\ .
Depending on the device, a buffer may also be created that stores contributions
to the forces in 64 bit fixed point format. On devices that support atomic
operations on 64 bit integers in global memory, this can be a more efficient way
of accumulating forces than using a large number of force buffers. To convert a
value from floating point to fixed point, multiply it by 0x100000000 (2\ :sup:`32`\ ),
then cast it to a :code:`long`\ . The fixed point buffer is
ordered differently from the others. For atom *i*\ , the x component of its
force is stored in element :code:`i`\ , the y component in element
:code:`i+context.getPaddedNumAtoms()`\ , and the z component in element
:code:`i+2*context.getPaddedNumAtoms()`\ .
The potential energy is also accumulated in a set of buffers, but this one is
simply a list of floating point values. All of them are set to zero at the
start of a computation, and they are summed at the end of the computation to
yield the total energy.
The OpenCL implementation of each Force object should define a subclass of
OpenCLForce, and register an instance of it by calling :code:`addForce()` on
the OpenCLContext. This serves two purposes:
#. It reports how many force buffers are required when calculating this
particular Force. The OpenCLContext sets the size of its force buffer array
based on the largest number of buffers required by any Force.
#. It implements methods for determining whether particular particles or groups
of particles are identical. This is important when reordering particles, and is
discussed below.
Nonbonded Forces
****************
Computing nonbonded interactions efficiently is a complicated business in the
best of cases. It is even more complicated on a GPU. Furthermore, the
algorithms must vary based on the type of processor being used, whether there is
a distance cutoff, and whether periodic boundary conditions are being applied.
The OpenCLNonbondedUtilities class tries to simplify all of this. To use it you
need provide only a piece of code to compute the interaction between two
particles. It then takes responsibility for generating a neighbor list, looping
over interacting particles, loading particle parameters from global memory, and
writing the forces and energies to the appropriate buffers. All of these things
are done using an algorithm appropriate to the processor you are running on and
high level aspects of the interaction, such as whether it uses a cutoff and
whether particular particle pairs need to be excluded.
Of course, this system relies on certain assumptions, the most important of
which is that the Force can be represented as a sum of independent pairwise
interactions. If that is not the case, things become much more complicated.
You may still be able to use features of OpenCLNonbondedUtilities, but you
cannot use the simple mechanism outlined above. That is beyond the scope of
this guide.
To define a nonbonded interaction, call :code:`addInteraction()` on the
OpenCLNonbondedUtilities, providing a block of OpenCL source code for computing
the interaction. This block of source code will be inserted into the middle of
an appropriate kernel. At the point where it is inserted, various variables
will have been defined describing the interaction to compute:
#. :code:`atom1` and :code:`atom2` are the indices of the two
interacting particles.
#. :code:`r`\ , :code:`r2`\ , and :code:`invR` are the distance *r*
between the two particles, *r*\ :sup:`2`\ , and 1/\ *r* respectively.
#. :code:`isExcluded` is a :code:`bool` specifying whether this pair of
particles is marked as an excluded interaction. (Excluded pairs are not skipped
automatically, because in some cases they still need to be processed, just
differently from other pairs.)
#. :code:`posq1` and :code:`posq2` are :code:`real4`\ s containing the
positions (in the xyz fields) and charges (in the w fields) of the two
particles.
#. Other per-particle parameters may be specified, as described below.
The following preprocessor macros will also have been defined:
#. :code:`NUM_ATOMS` is the total number of particles in the system.
#. :code:`PADDED_NUM_ATOMS` is the padded number of particles in the system.
#. :code:`USE_CUTOFF` is defined if and only if a cutoff is being used
#. :code:`USE_PERIODIC` is defined if and only if periodic boundary
conditions are being used.
#. :code:`CUTOFF` and :code:`CUTOFF_SQUARED` are the cutoff distance and
its square respectively (but only defined if a cutoff is being used).
Finally, two output variables will have been defined:
#. You should add the energy of the interaction to :code:`tempEnergy`\ .
#. You should add the derivative of the energy with respect to the inter-
particle distance to :code:`dEdR`\ .
You can also define arbitrary per-particle parameters by calling
:code:`addParameter()` on the OpenCLNonbondedUtilities. You provide an array
in device memory containing the set of values, and the values for the two
interacting particles will be loaded and stored into variables called
:code:`<name>1` and :code:`<name>2`\ , where <name> is the name you specify
for the parameter. Note that nonbonded interactions are not computed until
after :code:`calcForcesAndEnergy()` has been called on every ForceImpl, so
it is possible to make the parameter values change with time by modifying them
inside :code:`calcForcesAndEnergy()`\ . Also note that the length of the
array containing the parameter values must equal the *padded* number of
particles in the system.
Finally, you can specify arbitrary other memory objects that should be passed as
arguments to the interaction kernel by calling :code:`addArgument()`\ . The
rest of the kernel ignores these arguments, but you can make use of them in your
interaction code.
Consider a simple example. Suppose we want to implement a nonbonded interaction
of the form *E*\ =\ *k*\ :sub:`1`\ *k*\ :sub:`2`\ *r*\ :sup:`2`\ ,
where *k* is a per-particle parameter. First we create a parameter as
follows
::
nb.addParameter(OpenCLNonbondedUtilities::ParameterInfo("kparam", "float", 1,
sizeof(cl_float), kparam->getDeviceBuffer()));
where :code:`nb` is the OpenCLNonbondedUtilities for the context. Now we
call :code:`addInteraction()` to define an interaction with the following
source code:
::
#ifdef USE_CUTOFF
if (!isExcluded && r2 < CUTOFF_SQUARED) {
#else
if (!isExcluded) {
#endif
tempEnergy += kparam1*kparam2*r2;
dEdR += 2*kparam1*kparam2*r;
}
An important point is that this code is executed for every pair of particles in
the *padded* list of atoms. This means that some interactions involve
padding atoms, and should not actually be included. You might think, then, that
the above code is incorrect and we need another check to filter out the extra
interactions:
::
if (atom1 < NUM_ATOMS && atom2 < NUM_ATOMS)
This is not necessary in our case, because the :code:`isExcluded` flag is
always set for interactions that involve a padding atom. If our force did not
use excluded interactions (and so did not check :code:`isExcluded`\ ), then we
would need to add this extra check. Self interactions are a similar case: we do
not check for :code:`(atom1 == atom2)` because the exclusion flag prevents
them from being processed, but for some forces that check is necessary.
Bonded Forces
*************
Just as OpenCLNonbondedUtilities simplifies the task of creating nonbonded
interactions, OpenCLBondedUtilities simplifies the process for many types of
bonded interactions. A “bonded interaction” means one that is applied to small,
fixed groups of particles. This includes bonds, angles, torsions, etc. The
important point is that the list of particles forming a “bond” is known in
advance and does not change with time.
Using OpenCLBondedUtilities is very similar to the process described above. You
provide a block of OpenCL code for evaluating a single interaction. This block
of code will be inserted into the middle of a kernel that loops over all
interactions and evaluates each one. At the point where it is inserted, the
following variables will have been defined describing the interaction to
compute:
#. :code:`index` is the index of the interaction being evaluated.
#. :code:`atom1`\ , :code:`atom2`\ , ... are the indices of the interacting
particles.
#. :code:`pos1`\ , :code:`pos2`\ , ... are :code:`real4`\ s containing the
positions (in the xyz fields) of the interacting particles.
A variable called :code:`energy` will have been defined for accumulating the
total energy of all interactions. Your code should add the energy of the
interaction to it. You also should define :code:`real4` variables called
:code:`force1`\ , :code:`force2`\ , ... and store the force on each atom into
them.
As a simple example, the following source code implements a pairwise interaction
of the form *E*\ =\ *r*\ :sup:`2`\ :
::
real4 delta = pos2-pos1;
energy += delta.x*delta.x + delta.y*delta.y + delta.z*delta.z;
real4 force1 = 2.0f*delta;
real4 force2 = -2.0f*delta;
To use it, call :code:`addInteraction()` on the Context’s
OpenCLBondedUtilities object. You also provide a list of the particles involved
in every bonded interaction.
Exactly as with nonbonded interactions, you can call :code:`addArgument()`
to specify arbitrary memory objects that should be passed as arguments to the
interaction kernel. These might contain per-bond parameters (use
:code:`index` to look up the appropriate element) or any other information you
want.
Reordering of Particles
***********************
Nonbonded calculations are done a bit differently in the OpenCL Platform than in
most CPU based codes. In particular, interactions are computed on blocks of 32
particles at a time (which is why the number of particles needs to be padded to
bring it up to a multiple of 32), and the neighbor list actually lists pairs of
\ *blocks*\ , not pairs of individual particles, that are close enough to
interact with each other.
This only works well if sequential particles tend to be close together so that
blocks are spatially compact. This is generally true of particles in a
macromolecule, but it is not true for solvent molecules. Each water molecule,
for example, can move independently of other water molecules, so particles that
happen to be sequential in whatever order the molecules were defined in need not
be spatially close together.
The OpenCL Platform addresses this by periodically reordering particles so that
sequential particles are close together. This means that what the OpenCL
Platform calls particle *i* need not be the same as what the System calls
particle *i*\ .
This reordering is done frequently, so it must be very fast. If all the data
structures describing the structure of the System and the Forces acting on it
needed to be updated, that would make it prohibitively slow. The OpenCL
Platform therefore only reorders particles in ways that do not alter any part of
the System definition. In practice, this means exchanging entire molecules; as
long as two molecules are truly identical, their positions and velocities can be
exchanged without affecting the System in any way.
Every Force can contribute to defining the boundaries of molecules, and to
determining whether two molecules are identical. This is done through the
OpenCLForceInfo it adds to the OpenCLContext. It can specify two types of
information:
#. Given a pair of particles, it can say whether those two particles are
identical (as far as that Force is concerned). For example, a Force object
implementing a Coulomb force would check whether the two particles had equal
charges.
#. It can define *particle groups*\ . The OpenCL Platform will ensure that
all the particles in a group are part of the same molecule. It also can specify
whether two groups are identical to each other. For example, in a Force
implementing harmonic bonds, each group would consist of the two particles
connected by a bond, and two groups would be identical if they had the same
spring constants and equilibrium lengths.
Integration Utilities
*********************
The OpenCLContext’s OpenCLIntegrationUtilities provides features that are used
by many integrators. The two most important are random number generation and
constraint enforcement.
If you plan to use random numbers, you should call
:code:`initRandomNumberGenerator()` during initialization, specifying the
random number seed to use. Be aware that there is only one random number
generator, even if multiple classes make use of it. If two classes each call
:code:`initRandomNumberGenerator()` and request different seeds, an exception
will be thrown. If they each request the same seed, the second call will simply
be ignored.
For efficiency, random numbers are generated in bulk and stored in an array in
device memory, which you can access by calling :code:`getRandom()`\ . Each
time you need to use a block of random numbers, call
:code:`prepareRandomNumbers()`\ , specifying how many values you need. It will
register that many values as having been used, and return the index in the array
at which you should start reading values. If not enough unused values remain in
the array, it will generate a new batch of random values before returning.
To apply constraints, simply call :code:`applyConstraints()`\ . For numerical
accuracy, the constraint algorithms do not work on particle positions directly,
but rather on the *displacements* taken by the most recent integration step.
These displacements must be stored in an array which you can get by calling
:code:`getPosDelta()`\ . That is, the constraint algorithms assume the actual
(unconstrained) position of each particle equals the position stored in the
OpenCLContext plus the delta stored in the OpenCLIntegrationUtilities. It then
modifies the deltas so that all distance constraints are satisfied. The
integrator must then finish the time step by adding the deltas to the positions
and storing them into the main position array.
.. _the-cuda-platform:
The CUDA Platform
#################
The CUDA platform is very similar to the OpenCL platform, and most of the
previous chapter applies equally well to it, just changing “OpenCL” to “Cuda” in
class names. There are a few differences worth noting.
Compiling Kernels
*****************
Like the OpenCL platform, the CUDA platform compiles all its kernels at runtime.
Unlike OpenCL, CUDA does not have built in support for runtime compilation.
OpenMM therefore needs to implement this itself by writing the source code out
to disk, invoking the nvcc compiler as a separate process, and then loading the
compiled kernel in from disk.
For the most part, you can ignore all of this. Just call
:code:`createModule()` on the CudaContext, passing it the CUDA source code.
It takes care of the details of compilation and loading, returning a CUmodule
object when it is done. You can then call :code:`getKernel()` to look up
individual kernels in the module (represented as CUfunction objects) and
:code:`executeKernel()` to execute them.
The CUDA platform does need two things to make this work: a directory on disk
where it can write out temporary files, and the path to the nvcc compiler.
These are specified by the “CudaTempDirectory” and “CudaCompiler” properties
when you create a new Context. It often can figure out suitable values for them
on its own, but sometimes it needs help. See the “Platform-Specific Properties”
chapter of the Users Manual for details.
Accumulating Forces
*******************
The OpenCL platform, as described in Section :ref:`computing-forces`\ , uses two types of buffers for
accumulating forces: a set of floating point buffers, and a single fixed point
buffer. In contrast, the CUDA platform uses *only* the fixed point buffer
(represented by the CUDA type :code:`long` :code:`long`\ ). This means
the CUDA platform only works on devices that support 64 bit atomic operations
(compute capability 1.2 or higher).
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######################
OpenMM Developer Guide
######################
Portions copyright (c) 2011-2014 Stanford University and the Authors
Contributors: Peter Eastman
Permission is hereby granted, free of charge, to any person obtaining a copy of
this document (the "Document"), to deal in the Document without restriction,
including without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Document, and to permit
persons to whom the Document is furnished to do so, subject to the following
conditions:
This copyright and permission notice shall be included in all copies or
substantial portions of the Document.
THE DOCUMENT IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS,
CONTRIBUTORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE DOCUMENT OR THE USE OR OTHER DEALINGS IN THE
DOCUMENT.
Acknowledgments
OpenMM software and all related activities, such as this manual, are funded by
the Simbios National Center for Biomedical Computing through the National
Institutes of Health Roadmap for Medical Research, Grant U54 GM072970.
Information on the National Centers can be found at
http://nihroadmap.nih.gov/bioinformatics.
.. toctree::
:maxdepth: 3
:numbered:
developer
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1. Source Code.
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The Corresponding Source for a work in source code form is that
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All rights granted under this License are granted for the term of
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You may convey verbatim copies of the Program's source code as you
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You may convey a covered work in object code form under the terms
of sections 4 and 5, provided that you also convey the
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(including a physical distribution medium), accompanied by the
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customarily used for software interchange.
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(including a physical distribution medium), accompanied by a
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long as you offer spare parts or customer support for that product
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copy of the Corresponding Source for all the software in the
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conveying of source, or (2) access to copy the
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c) Convey individual copies of the object code with a copy of the
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with subsection 6b.
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that supports equivalent copying facilities, provided you maintain
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If you convey an object code work under this section in, or with, or
specifically for use in, a User Product, and the conveying occurs as
part of a transaction in which the right of possession and use of the
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if neither you nor any third party retains the ability to install
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in accord with this section must be in a format that is publicly
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unpacking, reading or copying.
7. Additional Terms.
"Additional permissions" are terms that supplement the terms of this
License by making exceptions from one or more of its conditions.
Additional permissions that are applicable to the entire Program shall
be treated as though they were included in this License, to the extent
that they are valid under applicable law. If additional permissions
apply only to part of the Program, that part may be used separately
under those permissions, but the entire Program remains governed by
this License without regard to the additional permissions.
When you convey a copy of a covered work, you may at your option
remove any additional permissions from that copy, or from any part of
it. (Additional permissions may be written to require their own
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Notwithstanding any other provision of this License, for material you
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that material) supplement the terms of this License with terms:
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terms of sections 15 and 16 of this License; or
b) Requiring preservation of specified reasonable legal notices or
author attributions in that material or in the Appropriate Legal
Notices displayed by works containing it; or
c) Prohibiting misrepresentation of the origin of that material, or
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All other non-permissive additional terms are considered "further
restrictions" within the meaning of section 10. If the Program as you
received it, or any part of it, contains a notice stating that it is
governed by this License along with a term that is a further
restriction, you may remove that term. If a license document contains
a further restriction but permits relicensing or conveying under this
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of that license document, provided that the further restriction does
not survive such relicensing or conveying.
If you add terms to a covered work in accord with this section, you
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where to find the applicable terms.
Additional terms, permissive or non-permissive, may be stated in the
form of a separately written license, or stated as exceptions;
the above requirements apply either way.
8. Termination.
You may not propagate or modify a covered work except as expressly
provided under this License. Any attempt otherwise to propagate or
modify it is void, and will automatically terminate your rights under
this License (including any patent licenses granted under the third
paragraph of section 11).
However, if you cease all violation of this License, then your
license from a particular copyright holder is reinstated (a)
provisionally, unless and until the copyright holder explicitly and
finally terminates your license, and (b) permanently, if the copyright
holder fails to notify you of the violation by some reasonable means
prior to 60 days after the cessation.
Moreover, your license from a particular copyright holder is
reinstated permanently if the copyright holder notifies you of the
violation by some reasonable means, this is the first time you have
received notice of violation of this License (for any work) from that
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your receipt of the notice.
Termination of your rights under this section does not terminate the
licenses of parties who have received copies or rights from you under
this License. If your rights have been terminated and not permanently
reinstated, you do not qualify to receive new licenses for the same
material under section 10.
9. Acceptance Not Required for Having Copies.
You are not required to accept this License in order to receive or
run a copy of the Program. Ancillary propagation of a covered work
occurring solely as a consequence of using peer-to-peer transmission
to receive a copy likewise does not require acceptance. However,
nothing other than this License grants you permission to propagate or
modify any covered work. These actions infringe copyright if you do
not accept this License. Therefore, by modifying or propagating a
covered work, you indicate your acceptance of this License to do so.
10. Automatic Licensing of Downstream Recipients.
Each time you convey a covered work, the recipient automatically
receives a license from the original licensors, to run, modify and
propagate that work, subject to this License. You are not responsible
for enforcing compliance by third parties with this License.
An "entity transaction" is a transaction transferring control of an
organization, or substantially all assets of one, or subdividing an
organization, or merging organizations. If propagation of a covered
work results from an entity transaction, each party to that
transaction who receives a copy of the work also receives whatever
licenses to the work the party's predecessor in interest had or could
give under the previous paragraph, plus a right to possession of the
Corresponding Source of the work from the predecessor in interest, if
the predecessor has it or can get it with reasonable efforts.
You may not impose any further restrictions on the exercise of the
rights granted or affirmed under this License. For example, you may
not impose a license fee, royalty, or other charge for exercise of
rights granted under this License, and you may not initiate litigation
(including a cross-claim or counterclaim in a lawsuit) alleging that
any patent claim is infringed by making, using, selling, offering for
sale, or importing the Program or any portion of it.
11. Patents.
A "contributor" is a copyright holder who authorizes use under this
License of the Program or a work on which the Program is based. The
work thus licensed is called the contributor's "contributor version".
A contributor's "essential patent claims" are all patent claims
owned or controlled by the contributor, whether already acquired or
hereafter acquired, that would be infringed by some manner, permitted
by this License, of making, using, or selling its contributor version,
but do not include claims that would be infringed only as a
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patent sublicenses in a manner consistent with the requirements of
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Each contributor grants you a non-exclusive, worldwide, royalty-free
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In the following three paragraphs, a "patent license" is any express
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(such as an express permission to practice a patent or covenant not to
sue for patent infringement). To "grant" such a patent license to a
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If you convey a covered work, knowingly relying on a patent license,
and the Corresponding Source of the work is not available for anyone
to copy, free of charge and under the terms of this License, through a
publicly available network server or other readily accessible means,
then you must either (1) cause the Corresponding Source to be so
available, or (2) arrange to deprive yourself of the benefit of the
patent license for this particular work, or (3) arrange, in a manner
consistent with the requirements of this License, to extend the patent
license to downstream recipients. "Knowingly relying" means you have
actual knowledge that, but for the patent license, your conveying the
covered work in a country, or your recipient's use of the covered work
in a country, would infringe one or more identifiable patents in that
country that you have reason to believe are valid.
If, pursuant to or in connection with a single transaction or
arrangement, you convey, or propagate by procuring conveyance of, a
covered work, and grant a patent license to some of the parties
receiving the covered work authorizing them to use, propagate, modify
or convey a specific copy of the covered work, then the patent license
you grant is automatically extended to all recipients of the covered
work and works based on it.
A patent license is "discriminatory" if it does not include within
the scope of its coverage, prohibits the exercise of, or is
conditioned on the non-exercise of one or more of the rights that are
specifically granted under this License. You may not convey a covered
work if you are a party to an arrangement with a third party that is
in the business of distributing software, under which you make payment
to the third party based on the extent of your activity of conveying
the work, and under which the third party grants, to any of the
parties who would receive the covered work from you, a discriminatory
patent license (a) in connection with copies of the covered work
conveyed by you (or copies made from those copies), or (b) primarily
for and in connection with specific products or compilations that
contain the covered work, unless you entered into that arrangement,
or that patent license was granted, prior to 28 March 2007.
Nothing in this License shall be construed as excluding or limiting
any implied license or other defenses to infringement that may
otherwise be available to you under applicable patent law.
12. No Surrender of Others' Freedom.
If conditions are imposed on you (whether by court order, agreement or
otherwise) that contradict the conditions of this License, they do not
excuse you from the conditions of this License. If you cannot convey a
covered work so as to satisfy simultaneously your obligations under this
License and any other pertinent obligations, then as a consequence you may
not convey it at all. For example, if you agree to terms that obligate you
to collect a royalty for further conveying from those to whom you convey
the Program, the only way you could satisfy both those terms and this
License would be to refrain entirely from conveying the Program.
13. Use with the GNU Affero General Public License.
Notwithstanding any other provision of this License, you have
permission to link or combine any covered work with a work licensed
under version 3 of the GNU Affero General Public License into a single
combined work, and to convey the resulting work. The terms of this
License will continue to apply to the part which is the covered work,
but the special requirements of the GNU Affero General Public License,
section 13, concerning interaction through a network will apply to the
combination as such.
14. Revised Versions of this License.
The Free Software Foundation may publish revised and/or new versions of
the GNU General Public License from time to time. Such new versions will
be similar in spirit to the present version, but may differ in detail to
address new problems or concerns.
Each version is given a distinguishing version number. If the
Program specifies that a certain numbered version of the GNU General
Public License "or any later version" applies to it, you have the
option of following the terms and conditions either of that numbered
version or of any later version published by the Free Software
Foundation. If the Program does not specify a version number of the
GNU General Public License, you may choose any version ever published
by the Free Software Foundation.
If the Program specifies that a proxy can decide which future
versions of the GNU General Public License can be used, that proxy's
public statement of acceptance of a version permanently authorizes you
to choose that version for the Program.
Later license versions may give you additional or different
permissions. However, no additional obligations are imposed on any
author or copyright holder as a result of your choosing to follow a
later version.
15. Disclaimer of Warranty.
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
16. Limitation of Liability.
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
SUCH DAMAGES.
17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided
above cannot be given local legal effect according to their terms,
reviewing courts shall apply local law that most closely approximates
an absolute waiver of all civil liability in connection with the
Program, unless a warranty or assumption of liability accompanies a
copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
state the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail.
If the program does terminal interaction, make it output a short
notice like this when it starts in an interactive mode:
<program> Copyright (C) <year> <name of author>
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, your program's commands
might be different; for a GUI interface, you would use an "about box".
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU GPL, see
<http://www.gnu.org/licenses/>.
The GNU General Public License does not permit incorporating your program
into proprietary programs. If your program is a subroutine library, you
may consider it more useful to permit linking proprietary applications with
the library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License. But first, please read
<http://www.gnu.org/philosophy/why-not-lgpl.html>.
docs/licenses/LGPL.txt deleted 100644 → 0
View file @ 89b4a7e4
GNU LESSER GENERAL PUBLIC LICENSE
Version 3, 29 June 2007
Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
This version of the GNU Lesser General Public License incorporates
the terms and conditions of version 3 of the GNU General Public
License, supplemented by the additional permissions listed below.
0. Additional Definitions.
As used herein, "this License" refers to version 3 of the GNU Lesser
General Public License, and the "GNU GPL" refers to version 3 of the GNU
General Public License.
"The Library" refers to a covered work governed by this License,
other than an Application or a Combined Work as defined below.
An "Application" is any work that makes use of an interface provided
by the Library, but which is not otherwise based on the Library.
Defining a subclass of a class defined by the Library is deemed a mode
of using an interface provided by the Library.
A "Combined Work" is a work produced by combining or linking an
Application with the Library. The particular version of the Library
with which the Combined Work was made is also called the "Linked
Version".
The "Minimal Corresponding Source" for a Combined Work means the
Corresponding Source for the Combined Work, excluding any source code
for portions of the Combined Work that, considered in isolation, are
based on the Application, and not on the Linked Version.
The "Corresponding Application Code" for a Combined Work means the
object code and/or source code for the Application, including any data
and utility programs needed for reproducing the Combined Work from the
Application, but excluding the System Libraries of the Combined Work.
1. Exception to Section 3 of the GNU GPL.
You may convey a covered work under sections 3 and 4 of this License
without being bound by section 3 of the GNU GPL.
2. Conveying Modified Versions.
If you modify a copy of the Library, and, in your modifications, a
facility refers to a function or data to be supplied by an Application
that uses the facility (other than as an argument passed when the
facility is invoked), then you may convey a copy of the modified
version:
a) under this License, provided that you make a good faith effort to
ensure that, in the event an Application does not supply the
function or data, the facility still operates, and performs
whatever part of its purpose remains meaningful, or
b) under the GNU GPL, with none of the additional permissions of
this License applicable to that copy.
3. Object Code Incorporating Material from Library Header Files.
The object code form of an Application may incorporate material from
a header file that is part of the Library. You may convey such object
code under terms of your choice, provided that, if the incorporated
material is not limited to numerical parameters, data structure
layouts and accessors, or small macros, inline functions and templates
(ten or fewer lines in length), you do both of the following:
a) Give prominent notice with each copy of the object code that the
Library is used in it and that the Library and its use are
covered by this License.
b) Accompany the object code with a copy of the GNU GPL and this license
document.
4. Combined Works.
You may convey a Combined Work under terms of your choice that,
taken together, effectively do not restrict modification of the
portions of the Library contained in the Combined Work and reverse
engineering for debugging such modifications, if you also do each of
the following:
a) Give prominent notice with each copy of the Combined Work that
the Library is used in it and that the Library and its use are
covered by this License.
b) Accompany the Combined Work with a copy of the GNU GPL and this license
document.
c) For a Combined Work that displays copyright notices during
execution, include the copyright notice for the Library among
these notices, as well as a reference directing the user to the
copies of the GNU GPL and this license document.
d) Do one of the following:
0) Convey the Minimal Corresponding Source under the terms of this
License, and the Corresponding Application Code in a form
suitable for, and under terms that permit, the user to
recombine or relink the Application with a modified version of
the Linked Version to produce a modified Combined Work, in the
manner specified by section 6 of the GNU GPL for conveying
Corresponding Source.
1) Use a suitable shared library mechanism for linking with the
Library. A suitable mechanism is one that (a) uses at run time
a copy of the Library already present on the user's computer
system, and (b) will operate properly with a modified version
of the Library that is interface-compatible with the Linked
Version.
e) Provide Installation Information, but only if you would otherwise
be required to provide such information under section 6 of the
GNU GPL, and only to the extent that such information is
necessary to install and execute a modified version of the
Combined Work produced by recombining or relinking the
Application with a modified version of the Linked Version. (If
you use option 4d0, the Installation Information must accompany
the Minimal Corresponding Source and Corresponding Application
Code. If you use option 4d1, you must provide the Installation
Information in the manner specified by section 6 of the GNU GPL
for conveying Corresponding Source.)
5. Combined Libraries.
You may place library facilities that are a work based on the
Library side by side in a single library together with other library
facilities that are not Applications and are not covered by this
License, and convey such a combined library under terms of your
choice, if you do both of the following:
a) Accompany the combined library with a copy of the same work based
on the Library, uncombined with any other library facilities,
conveyed under the terms of this License.
b) Give prominent notice with the combined library that part of it
is a work based on the Library, and explaining where to find the
accompanying uncombined form of the same work.
6. Revised Versions of the GNU Lesser General Public License.
The Free Software Foundation may publish revised and/or new versions
of the GNU Lesser General Public License from time to time. Such new
versions will be similar in spirit to the present version, but may
differ in detail to address new problems or concerns.
Each version is given a distinguishing version number. If the
Library as you received it specifies that a certain numbered version
of the GNU Lesser General Public License "or any later version"
applies to it, you have the option of following the terms and
conditions either of that published version or of any later version
published by the Free Software Foundation. If the Library as you
received it does not specify a version number of the GNU Lesser
General Public License, you may choose any version of the GNU Lesser
General Public License ever published by the Free Software Foundation.
If the Library as you received it specifies that a proxy can decide
whether future versions of the GNU Lesser General Public License shall
apply, that proxy's public statement of acceptance of any version is
permanent authorization for you to choose that version for the
Library.
docs/licenses/Licenses.txt deleted 100644 → 0
View file @ 89b4a7e4
OpenMM was developed by Simbios, the NIH National Center for Physics-Based
Simulation of Biological Structures at Stanford, funded under the NIH Roadmap
for Medical Research, grant U54 GM072970. See https://simtk.org.
Portions copyright © 2008-2009 Stanford University and the Authors.
There are several licenses which cover different parts of OpenMM as described
below.
1. API and Reference Platform
The OpenMM API and the Reference Platform may be used under the terms of the
MIT License:
Permission is hereby granted, free of charge, to any person obtaining
a copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject
to the following conditions:
The above copyright notice and this permission notice shall be included
in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS, CONTRIBUTORS OR COPYRIGHT HOLDERS BE
LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
2. CUDA and OpenCL Platforms
The CUDA Platform and OpenCL Platform may be used under the terms of the GNU
Lesser General Public License. A copy of this license may be found in the
accompanying file "LGPL.txt". It in turn incorporates the terms of the GNU
General Public License, which may be found in the accompanying file "GPL.txt".
3. SIMD-oriented Fast Mersenne Twister (SFMT)
OpenMM uses the SFMT library which is copyright 2006-2007 Mutsuo Saito, Makoto
Matsumoto and Hiroshima University. It may be used under the following terms:
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are
met:
* Redistributions of source code must retain the above copyright
notice, this list of conditions and the following disclaimer.
* Redistributions in binary form must reproduce the above
copyright notice, this list of conditions and the following
disclaimer in the documentation and/or other materials provided
with the distribution.
* Neither the name of the Hiroshima University nor the names of
its contributors may be used to endorse or promote products
derived from this software without specific prior written
permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
4. Hilbert Curve
OpenMM uses an implementation of Hilbert curves which is copyright 1998-2000
Rice University. It may be used under the following terms:
This software is copyrighted by Rice University. It may be freely copied,
modified, and redistributed, provided that the copyright notice is
preserved on all copies.
There is no warranty or other guarantee of fitness for this software,
it is provided solely "as is". Bug reports or fixes may be sent
to the author, who may or may not act on them as he desires.
You may include this software in a program or other software product,
but must display the notice:
Hilbert Curve implementation copyright 1998, Rice University
in any place where the end-user would see your own copyright.
If you modify this software, you should include a notice giving the
name of the person performing the modification, the date of modification,
and the reason for such modification.
5. GPU-BBSort
The CUDA platform uses the GPU-BBSort library written by Chen Shifu. It
includes the following license statement:
The code is distributed under BSD license, you are allowed to use, modify
or sell this code, but a statement is required if you used this code any where.
\ No newline at end of file
docs/sphinx/autonumber.py deleted 100644 → 0
View file @ 89b4a7e4
from docutils.parsers.rst import roles
from docutils.nodes import Text, reference, section
from sphinx.roles import XRefRole
class autonumber(Text):
pass
class autonumber_ref(reference):
pass
def autonumber_role(name, rawtext, text, lineno, inliner, options={}, content=[]):
return ([autonumber(text)], [])
def doctree_resolved(app, doctree, docname):
index = {};
refTable = {}
if app.config.autonumber_by_chapter:
# Record the number of each chapter
env = app.builder.env
sectionNumbers = {}
for doc in env.toc_secnumbers:
sections = env.toc_secnumbers[doc]
for sectionId in sections:
sectionNumbers[sectionId[1:]] = sections[sectionId]
lastChapter = -1
# Assign numbers to all the autonumbered objects.
for node in doctree.traverse(autonumber):
category = node.astext().split(',')[0]
if category in index:
nextNumber = index[category]+1
else:
nextNumber = 1
if app.config.autonumber_by_chapter:
parent = node.parent
chapter = None
while chapter is None:
if isinstance(parent, section):
chapter = parent
parent = parent.parent
chapter = sectionNumbers[chapter.attributes['ids'][0]][0]
if chapter != lastChapter:
index = {}
newNode = Text('%s %d-%d' % (category, chapter, nextNumber))
lastChapter = chapter
else:
newNode = Text('%s %d' % (category, nextNumber))
index[category] = nextNumber
refTable[node.astext()] = newNode
node.parent.replace(node, newNode)
# Replace references with the name of the referenced object
for ref_info in doctree.traverse(autonumber_ref):
target = ref_info['reftarget']
if target not in refTable:
raise ValueError('Unknown target for autonumber reference: '+target)
ref_info.replace_self(Text(refTable[target].astext()))
def setup(app):
app.add_config_value('autonumber_by_chapter', True, False)
roles.register_local_role('autonumber', autonumber_role)
app.add_node(autonumber)
app.add_node(autonumber_ref)
app.add_role('numref', XRefRole(nodeclass=autonumber_ref))
app.connect('doctree-resolved', doctree_resolved)
docs/sphinx/caption.py deleted 100644 → 0
View file @ 89b4a7e4
from docutils.parsers.rst import Directive
from docutils.nodes import compound, raw
class CaptionDirective(Directive):
has_content = True
def run(self):
latexPrefix = raw('', '{\\centering', format='latex')
latexSuffix = raw('', '\\par}\\bigskip', format='latex')
text = '\n'.join(self.content)
content_node = compound(rawsource=text)
self.state.nested_parse(self.content, self.content_offset, content_node)
content_node.attributes['classes'].append('caption')
return [latexPrefix, content_node, latexSuffix]
def setup(app):
app.add_directive('caption', CaptionDirective)
docs/sphinx/numsec.py deleted 100644 → 0
View file @ 89b4a7e4
"""
Changes section references to be the section number
instead of the title of the section.
"""
from docutils import nodes
import sphinx.domains.std
class CustomStandardDomain(sphinx.domains.std.StandardDomain):
def __init__(self, env):
env.settings['footnote_references'] = 'superscript'
sphinx.domains.std.StandardDomain.__init__(self, env)
def resolve_xref(self, env, fromdocname, builder,
typ, target, node, contnode):
res = super(CustomStandardDomain, self).resolve_xref(env, fromdocname, builder,
typ, target, node, contnode)
if res is None:
return res
if typ == 'ref' and not node['refexplicit']:
docname, labelid, sectname = self.data['labels'].get(target, ('','',''))
res['refdocname'] = docname
return res
def doctree_resolved(app, doctree, docname):
secnums = app.builder.env.toc_secnumbers
for node in doctree.traverse(nodes.reference):
if 'refdocname' in node:
refdocname = node['refdocname']
if refdocname in secnums:
secnum = secnums[refdocname]
emphnode = node.children[0]
textnode = emphnode.children[0]
toclist = app.builder.env.tocs[refdocname]
anchorname = None
for refnode in toclist.traverse(nodes.reference):
if refnode.astext() == textnode.astext():
anchorname = refnode['anchorname']
if anchorname is None:
continue
linktext = '.'.join(map(str, secnum[anchorname]))
node.replace(emphnode, nodes.Text(linktext))
def setup(app):
app.override_domain(CustomStandardDomain)
app.connect('doctree-resolved', doctree_resolved)
docs/sphinx/samepage.py deleted 100644 → 0
View file @ 89b4a7e4
from docutils.parsers.rst import Directive
from docutils.nodes import compound, raw
class SamepageDirective(Directive):
has_content = True
def run(self):
prefix = raw('', '\\par\\begin{samepage}', format='latex')
suffix = raw('', '\\end{samepage}\\par', format='latex')
text = '\n'.join(self.content)
content_node = compound(rawsource=text)
self.state.nested_parse(self.content, self.content_offset, content_node)
return [prefix, content_node, suffix]
def setup(app):
app.add_directive('samepage', SamepageDirective)
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