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README.md
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README.md
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# qmckl
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# Quantum Monte Carlo Kernel Library.
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Quantum Monte Carlo Kernel Library.
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The domain of quantum chemistry needs a library in which the main
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kernels of Quantum Monte Carlo (QMC) methods are implemented. In the
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library proposed in this project, we expose the main algorithms in a
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language and provide a standard API and tests to enable the
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development of high-performance QMCkl implementations taking
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advantage of modern hardware.
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See the [Wiki](https://github.com/TREX-CoE/qmckl/wiki) for more information.
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See the [source code](https://github.com/TREX-CoE/qmckl/src/README.org)
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to read the documentation.
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------------------------------
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[[https://trex-coe.eu/sites/default/files/inline-images/euflag.jpg]]
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[TREX: Targeting Real Chemical Accuracy at the Exascale](https://trex-coe.eu) project has received funding from the European Union’s Horizon 2020 - Research and Innovation program - under grant agreement no. 952165. The content of this document does not represent the opinion of the European Union, and the European Union is not responsible for any use that might be made of such content.
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145
src/README.org
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src/README.org
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** Introduction
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The main objective of present library is documentation. Therefore,
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literate programming is particularly adapted in this context.
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Source files are written in org-mode format, to provide useful
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The ultimate goal of QMCkl is to provide a high-performance
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implementation of the main kernels of QMC. In this particular
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repository, we focus on the definition of the API and the tests,
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and on a /pedagogical/ presentation of the algorithms. We expect the
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HPC experts to use this repository as a reference for re-writing
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optimized libraries.
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Literate programming is particularly adapted in this context.
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Source files are written in [[ottps://karl-voit.at/2017/09/23/orgmode-as-markup-only/][org-mode]] format, to provide useful
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comments and LaTex formulas close to the code. There exists multiple
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possibilities to convert org-mode files into different formats such as
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HTML or pdf.
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The code is extracted from the org files using Emacs as a command-line
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tool in the =Makefile=, and then the produced files are compiled.
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If the name of the file is =xxx.org=, the name of the produced C
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files should be =xxx.c= and =xxx.h= and the name of the produced
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Fortran files should be =xxx.f90=
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*** Language used
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Fortran is one of the most common languages used by the community,
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and is simple enough to make the algorithms readable. Hence we
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propose in this pedagogical implementation of QMCkl to use Fortran
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to express the algorithms. For specific internal functions where
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the C language is more natural, C is used.
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As Fortran modules generate compiler-dependent files, the use of
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modules is restricted to the internal use of the library, otherwise
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the compliance with C is violated.
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The external dependencies should be kept as small as possible, so
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external libraries should be used /only/ if their used is strongly
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justified.
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*** Source code editing
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@ -50,8 +68,123 @@ rm ${nb}.md
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iso-c-binding. The name of the Fortran source files should end
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with =_f.f90= to be properly handled by the Makefile.
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*** Coding style
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# TODO: decide on a coding style
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To improve readability, we maintain a consistent coding style in the library.
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- For C source files, we will use __(decide on a coding style)__
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- For Fortran source files, we will use __(decide on a coding style)__
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Coding style can be automatically checked with [[https://clang.llvm.org/docs/ClangFormat.html][clang-format]].
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** Design of the library
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The proposed API should allow the library to:
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- deal with memory transfers between CPU and accelerators
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- use different levels of floating-point precision
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We chose a multi-layered design with low-level and high-level
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functions (see below).
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*** Naming conventions
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Use =qmckl_= as a prefix for all exported functions and variables.
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All exported header files should have a filename with the prefix
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=qmckl_=.
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If the name of the org-mode file is =xxx.org=, the name of the
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produced C files should be =xxx.c= and =xxx.h= and the name of the
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produced Fortran files should be =xxx.f90=
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*** Application programming interface
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The application programming interface (API) is designed to be
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compatible with the C programming language (not C++), to ensure
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that the library will be easily usable in any language.
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This implies that only the following data types are allowed in the API:
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- 32-bit and 64-bit floats and arrays
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- 32-bit and 64-bit integers and arrays
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- Pointers should be represented as 64-bit integers (even on
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32-bit architectures)
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- ASCII strings are represented as a pointers to a character arrays
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and terminated by a zero character (C convention).
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To facilitate the use in other languages than C, we provide some
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bindings in other languages in other repositories.
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# TODO : Link to repositories for bindings
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*** Global state
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Global variables should be avoided in the library, because it is
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possible that one single program needs to use multiple instances of
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the library. To solve this problem we propose to use a pointer to a
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=context= variable, built by the library with the
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=qmckl_context_create= function. The =context= contains the global
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state of the library, and is used as the first argument of many
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QMCkl functions.
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Modifying the state is done by setters and getters, prefixed
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by =qmckl_context_set_= an =qmckl_context_get_=.
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When a context variable is modified by a setter, a copy of the old
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data structure is made and updated, and the pointer to the new data
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structure is returned, such that the old contexts can still be
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accessed.
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It is also possible to modify the state in an impure fashion, using
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the =qmckl_context_update_= functions.
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The context and its old versions can be destroyed with
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=qmckl_context_destroy=.
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*** Low-level functions
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Low-level functions are very simple functions which are leaves of the
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function call tree (they don't call any other QMCkl function).
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This functions are /pure/, and unaware of the QMCkl =context=. They are
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not allowed to allocate/deallocate memory, and if they need
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temporary memory it should be provided in input.
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*** High-level functions
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High-level functions are at the top of the function call tree.
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They are able to choose which lower-level function to call
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depending on the required precision, and do the corresponding type
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conversions.
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These functions are also responsible for allocating temporary
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storage, to simplify the use of accelerators.
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The high-level functions should be pure, unless the introduction of
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non-purity is justified. All the side effects should be made in the
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=context= variable.
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# TODO : We need an identifier for impure functions
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*** Numerical precision
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The number of bits of precision required for a function should be
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given as an input of low-level computational functions. This input will
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be used to define the values of the different thresholds that might
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be used to avoid computing unnecessary noise.
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High-level functions will use the precision specified in the
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=context= variable.
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** Algorithms
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Reducing the scaling of an algorithm usually implies also reducing
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its arithmetic complexity (number of flops per byte). Therefore,
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for small sizes \(\mathcal{O}(N^3)\) and \(\mathcal{O}(N^2)\) algorithms
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are better adapted than linear scaling algorithms.
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As QMCkl is a general purpose library, multiple algorithms should
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be implemented adapted to different problem sizes.
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** Documentation
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- [[qmckl.org][Main QMCkl header file]]
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- [[qmckl_context.org][Context]]
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** Acknowledgments
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[[https://trex-coe.eu/sites/default/files/inline-images/euflag.jpg]]
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[[https://trex-coe.eu][TREX: Targeting Real Chemical Accuracy at the Exascale]] project has received funding from the European Union’s Horizon 2020 - Research and Innovation program - under grant agreement no. 952165. The content of this document does not represent the opinion of the European Union, and the European Union is not responsible for any use that might be made of such content.
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