From 1350e8cae485a802e23f029e6fc18b151b7344e2 Mon Sep 17 00:00:00 2001 From: Miroslav Stoyanov Date: Wed, 30 Oct 2019 15:04:25 -0400 Subject: [PATCH 1/5] added for-trilinos to the alexa overview --- .../2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex b/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex index 83680e77..902d569e 100644 --- a/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex +++ b/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex @@ -4,19 +4,24 @@ \subsubsection{\stid{3.14} ALExa} \paragraph{Overview} The ALExa project ({\sl Accelerated Libraries for Exascale}) focuses on -preparing the DTK and Tasmanian libraries for exascale platforms and +preparing the DTK, Tasmanian and ForTrilinos libraries for exascale platforms and integrating these libraries into ECP applications. These libraries deliver capabilities identified as needs of ECP applications: (1) the ability to transfer computed solutions between grids with differing layouts on parallel accelerated architectures, enabling multiphysics projects to seamlessly combine results from different computational grids to perform their required -simulations (DTK); and +simulations (DTK); % (2) the ability to construct fast and memory efficient surrogates to large scale engineering models with multiple inputs and large number of outputs, enabling uncertainty quantification (both forward and inverse) as well as optimization and efficient multi-physics simulations in projects such as -ExaStar (Tasmanian). +ExaStar (Tasmanian); and +% +(3) the ability to interface large and complex Fortran-based codes to the +growing collection of Trilinos advanced solver capabilities that can +utilize next-generation platforms, the interface is done without C/C++ +interface code. These capabilities are being developed through ongoing interactions with our ECP application project collaborators to ensure they will satisfy requirements From ac6e9791f5ea6a0bd30685523b2d9ff0666fc4ac Mon Sep 17 00:00:00 2001 From: Miroslav Stoyanov Date: Wed, 30 Oct 2019 15:28:50 -0400 Subject: [PATCH 2/5] merged fortrilinos with the rest of alexa --- .../2.3.3.14-ALExa.tex | 97 ++++++++++++++++++- 1 file changed, 94 insertions(+), 3 deletions(-) diff --git a/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex b/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex index 902d569e..a0f1ecc6 100644 --- a/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex +++ b/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex @@ -84,6 +84,34 @@ \subsubsection{\stid{3.14} ALExa} {\it URL:} http://tasmanian.ornl.gov + +{\bf ForTrilinos} (Fortran for Trilinos) + +{\it Purpose:} ForTrilinos provides a seamless pathway for large and complex +Fortran-based codes to access Trilinos without C/C++ interface code. +This access includes Fortran versions of Kokkos abstractions for code +execution and data management.. + +{\it Significance:} The Exascale Computing Project (ECP) requires the successful +transformation and porting of many Fortran application codes in preparation for +ECP platforms. A significant number of these codes rely upon the scalable +solution of linear and nonlinear equations. The Trilinos Project contains +a large and growing collection of solver capabilities that can utilize +next-generation platforms, in particular scalable multicore, manycore, +accelerator and heterogeneous systems. Trilinos is primarily written in C++, +including its user interfaces. While C++ is advantageous for gaining access to +the latest programming environments, it limits Trilinos usage via Fortran. + +{\it SWIG capabilities:} an interface generator, SWIG, which the project is +extending, to create the object-oriented Fotran wrapper code that users can +access directly. This language translation will occur in both directions; +ForTrilinos will provide an inversion of control functionality that enables +custom extensions of the Trilinos solvers that are Fortran-based. Once the +ForTrilinos project is complete, a functional, extensible suite of capabilities +to access Trilinos on next-generation computing systems will be provided. + +{\it URL:} https://github.com/trilinos/ForTrilinos + \paragraph{Key Challenges} \indent @@ -104,6 +132,17 @@ \subsubsection{\stid{3.14} ALExa} analysis (or multi-physics simulations) requires a massive number of basis evaluations and many sparse and dense linear operations. +{\bf ForTrilinos:} Developing the interfaces to the C++ libraries that provide +access to cutting-edge research, such as Trilinos, is of significant benefit +to Fortran community. However, such interfaces must be well documented, +sustainable and extensible, which would require significant amount of resources +and investment. This is further complicated by the requirements to support +heterogeneous platforms (e.g., GPUs) and inversion-of-control functionality. +The manual approach to such interfaces has been shown to be unsustainable as it +requires interface developers to have in-depth expertise in multiple languages +and the peculiarities in their interaction on top of the time commitment to +update the interfaces with changes in the library. + \paragraph{Solution Strategy} \nobreak @@ -124,6 +163,16 @@ \subsubsection{\stid{3.14} ALExa} SLATE/MAGMA capabilities to ensure performance portability across relevant platforms. +{\bf ForTrilinos:} Develop a Fortran module for the Simplified Wrapper +Interface Generator (SWIG) utility~\cite{beazley1996swig}. SWIG is used to parse +C++ code and generate wrapper code, and was already used for this purpose for +several dozen target languages, most notably Python. The project took the +approach of adding a Fortran 2003 wrapper generator for SWIG in order to +fulfill many of the critical feature requirements for ForTrilinos. +The developed SWIG/Fortran functionality allowed to proceed with automatic +generation of Fortran interfaces to selected Trilinos libraries. The work is +conducted in phases, with each phase increasing the number of wrapped of +Trilinos packages. %---------------------------------------- @@ -145,7 +194,7 @@ \subsubsection{\stid{3.14} ALExa} {\bf Tasmanian:} The infrastructure of Tasmanian has been upgraded to support the broader ECP focus of the work. GPU acceleration of sparse grid surrogates has been implemented. Tasmanian recently enabled the ExaStar project to -reduce the size of a large-memory table of neutrino opacities by 100X while +reduce the size of a large-memory table of neutrino opacities by 10X while still preserving accuracy. \begin{figure}[htb] @@ -154,6 +203,30 @@ \subsubsection{\stid{3.14} ALExa} \caption{\label{fig:tasmanian-gpu}Tasmanian approximation (right) of neutrino capacities (left).} \end{figure} +{\bf ForTrilinos:} +Figure~\ref{fig:fortran_ioc} illustrates a new Inversion-of-Control~(IoC) +implementation in ForTrilinos. The new approach allows Fortran users to define +an operator by using a derived type on the Fortran side, and use Trilinos +algorithms, e.g. Krylov solvers, to solve the linear system with that operator. + +\begin{figure}[htb] + \centering + \includegraphics[scale=0.8,width=6in]{projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/ForTrilinos_ioc} + \caption{\label{fig:fortran_ioc}The proposed Inversion-of-Control approach + allowing Fortran applications to define operators on Fortran side while + still using ForTrilinos types.} +\end{figure} + +This approach allows the user callback functions to interact with native Fortran +types and ForTrilinos class wrapper types. In the same vein, users would not +have to manually pass \texttt{type(C\_PTR)} instances into and out of the +callback function, as the C++ Fortran conversions can be tedious and +error-prone, which indeed is the motivation for using SWIG to generate +ForTrilinos. Another important feature is that it allows the application code +to extend Trilinos without having to generate any new interface code, either by +hand or using SWIG. In other words, the Fortran end user should not have to know +C++ or SWIG. + %---------------------------------------- \paragraph{Next Steps} @@ -164,7 +237,25 @@ \subsubsection{\stid{3.14} ALExa} lightweight library, ArborX, to provide these ECP investments to a broader user base. -{\bf Tasmanian:} Work will continue with the development of the asynchronous -construction methods that exploit the native sparse grids DAG hierarchy. +{\bf Tasmanian:} Work will continue with the development of mixed precision +algorithms for fast surrogate evaluations and integratinv the capability within +the ExaStar project. + +{\bf ForTrilinos:} the next efforts will include +\begin{enumerate} + \item \textbf{Provide wrappers for more libraries:} ForTrilinos will continue + efforts to increase the number of wrapped Trilinos libraries. The scheduled + release of the next phase of the project will include libraries + corresponding to nonlinear solvers, such as NOX. + \item \textbf{Integrate developed capabilities into applications:} E3SM-MMF + is an Earth system model development and simulation project. It relies on + Trilinos for its implicit capabilities. The ForTrilinos project will + integrate the developed nonlinear solver with IoC into E3SM-MMF to provide + path forward to heterogeneous stack. + \item \textbf{Provide interfaces for heterogeneous platforms:} ForTrilinos + will develop support for heterogeneous memory through providing access to + Kokkos-based interfaces in Trilinos. This will allow full exposure to + Trilinos capabilities targeting Exascale machines. +\end{enumerate} %---------------------------------------- From 4da3340f48db3cbd730f314ae2169539cdf15ae2 Mon Sep 17 00:00:00 2001 From: Miroslav Stoyanov Date: Wed, 30 Oct 2019 15:29:10 -0400 Subject: [PATCH 3/5] removed the separate fortrilinos include --- ECP-ST-CAR.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ECP-ST-CAR.tex b/ECP-ST-CAR.tex index 50cfa713..361eafe6 100644 --- a/ECP-ST-CAR.tex +++ b/ECP-ST-CAR.tex @@ -199,7 +199,7 @@ \subsection{\mathlibs} \input{projects/2.3.3-MathLibs/2.3.3.13-CLOVER/2.3.3.13-SLATE} \newpage \input{projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa} -\input{projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ForTrilinos} +% \input{projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ForTrilinos} % merged with ALExa \newpage From 363c027efb04da78d146450d940594f69b10b9f8 Mon Sep 17 00:00:00 2001 From: Stuart Slattery Date: Mon, 4 Nov 2019 11:29:25 -0500 Subject: [PATCH 4/5] updating dtk/arborx content --- .../2.3.3.14-ALExa.tex | 105 ++++++++++++------ .../arborx_summit.png | Bin 0 -> 265706 bytes .../dtk_exaam_pit.png | Bin 0 -> 74231 bytes 3 files changed, 71 insertions(+), 34 deletions(-) create mode 100644 projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/arborx_summit.png create mode 100644 projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/dtk_exaam_pit.png diff --git a/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex b/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex index 83680e77..c7989c8c 100644 --- a/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex +++ b/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex @@ -4,19 +4,19 @@ \subsubsection{\stid{3.14} ALExa} \paragraph{Overview} The ALExa project ({\sl Accelerated Libraries for Exascale}) focuses on -preparing the DTK and Tasmanian libraries for exascale platforms and +preparing the ArborX, DTK, and Tasmanian libraries for exascale platforms and integrating these libraries into ECP applications. These libraries deliver -capabilities identified as needs of ECP applications: (1) the ability to -transfer computed solutions between grids with differing layouts on parallel -accelerated architectures, enabling multiphysics projects to seamlessly -combine results from different computational grids to perform their required -simulations (DTK); and -% -(2) the ability to construct fast and memory efficient surrogates to large -scale engineering models with multiple inputs and large number of outputs, -enabling uncertainty quantification (both forward and inverse) as well as -optimization and efficient multi-physics simulations in projects such as -ExaStar (Tasmanian). +capabilities identified as needs of ECP applications: (1) the ability the +perform performance portable spatial searches between arbitrary sets of +distributed geometric objects (ArborX); (2) the ability to transfer computed +solutions between grids with differing layouts on parallel accelerated +architectures, enabling multiphysics projects to seamlessly combine results +from different computational grids to perform their required simulations +(DTK); and (3) the ability to construct fast and memory efficient surrogates +to large scale engineering models with multiple inputs and large number of +outputs, enabling uncertainty quantification (both forward and inverse) as +well as optimization and efficient multi-physics simulations in projects such +as ExaStar (Tasmanian). These capabilities are being developed through ongoing interactions with our ECP application project collaborators to ensure they will satisfy requirements @@ -27,6 +27,26 @@ \subsubsection{\stid{3.14} ALExa} the xSDK4ECP project. +{\bf ArborX} + +{\it Purpose:} ArborX is an open-source library designed to provide +performance portable algorithms for geometric search. + +{\it Significance:} General geometric search capabilities are needed in a wide +variety of applications including the generation of neighbor lists in +particle-based applications (e.g. molecular dynamics or general N-body +dynamics simulations) and mesh-mesh interactions including contact in +computational mechanics and solution transfer in multiphysics simulations. + +{\it Performance portable search capabilities:} Shared memory and GPU +implementations of spatial tree construction; shared memory and GPU +implementations of various spatial tree queries; MPI front-end for +coordinating distributed spatial searches between sets of geometric objects +with different decompositions; communication plan generation based on spatial +search results. + +{\it URL:} https://github.com/arborx/ArborX + {\bf DTK} (Data Transfer Kit) {\it Purpose:} Transfers computed solutions between grids with differing @@ -43,13 +63,6 @@ \subsubsection{\stid{3.14} ALExa} common applications include conjugate heat transfer, fluid structure interaction, and mesh deformation. -{\it Performance portable search capabilities:} shared memory and GPU -implementations of spatial tree construction; shared memory and GPU -implementations of various spatial tree queries; MPI front-end for -coordinating distributed spatial searches between sets of geometric objects -with different decompositions; communication plan generation based on spatial -search results. - {\it URL:} https://github.com/ORNL-CEES/DataTransferKit @@ -83,14 +96,16 @@ \subsubsection{\stid{3.14} ALExa} \indent +{\bf ArborX:} Search procedures to locate neighboring points, mesh cells, or +other geometric objects require tree search methods difficult to optimize on +modern accelerated architectures due to vector lane or thread divergence. + {\bf DTK:} General data transfer between grids of unrelated applications requires many-to-many communication which is increasingly challenging as communication to computation ratios are decreasing on successive HPC systems. -Search procedures to locate neighboring points and mesh cells require tree -search methods difficult to optimize on modern accelerated architectures due -to vector lane or thread divergence. Maintaining high accuracy for the -transfer requires careful attention to the mathematical properties of the -interpolation methods and is highly application-specific. +Maintaining high accuracy for the transfer requires careful attention to the +mathematical properties of the interpolation methods and is highly +application-specific. {\bf Tasmanian:} Complex models usually have significant variability in execution time for different model inputs, which leads to massive down-time @@ -106,6 +121,13 @@ \subsubsection{\stid{3.14} ALExa} \indent +{\bf ArborX:} ArborX builds on a Kokkos+MPI programming model to deploy to all +DOE HPC architectures. Extensive performance engineering has yielded +implementations that are both as performant in serial as state-of-the-art +libraries while also expanding on the capability provided by other libraries +by demonstrating thread scalability on both GPU and multi-core CPU +architectures.. + {\bf DTK:} State-of-the-art, mathematically rigorous methods are used in DTK to preserve accuracy of interpolated solutions. Algorithms are implemented in a C++ code base with extensive unit testing on multiple platforms. Trilinos @@ -126,15 +148,27 @@ \subsubsection{\stid{3.14} ALExa} \indent -{\bf DTK:} Extensive optimization work has yielded significant performance -improvements on accelerated and heterogeneous architectures. Work with partner -application ExaAM (WBS 2.2.1.05) created a preliminary multiphysics driver -capability for additive manufacturing simulations. +{\bf ArborX:} Extensive optimization work has yielded significant performance +improvements on accelerated and heterogeneous architectures. Recent results on +Summit show effective use of the Power9 hyperthreading capability as well as +excellent performance on the V100 GPU. \begin{figure}[htb] - \centering - \includegraphics[width=3.0in]{projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/dtk-gpu} - \caption{\label{fig:dtk-gpu}DTK search performance relative to Boost with Intel Xeon E5-2698 and Nvidia P100. 10M points randomly distributed in a unit cube, 1M queries. The time is in seconds. Speedup in bold.} + \centering \includegraphics[width=3.0in]{projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/arborx_summit.png} \caption{\label{fig:arborx-gpu} + ArborX search performance on a single Summit node. One V100 GPU gives + similar performance as the entire Power9 CPU performance on a node.} +\end{figure} + +{\bf DTK:} Work with partner application ExaAM (WBS 2.2.1.05) created a +preliminary multiphysics driver capability for additive manufacturing +simulations using a parallel-in-time coupling strategy. + +\begin{figure}[htb] + \centering \includegraphics[width=3.0in]{projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/dtk_exaam_pit.png} \caption{\label{fig:dtk-exaam-pit} + New ExaAM parallel-in-time coupling. Each arrow represents a DTK + transfer between different grids at different time points. Thousands + of DTK maps will be used to interpolate and communicate information + between steps. Image courtesy of Matt Bement (ExaAM Team) } \end{figure} {\bf Tasmanian:} The infrastructure of Tasmanian has been upgraded to support @@ -155,9 +189,12 @@ \subsubsection{\stid{3.14} ALExa} \indent -{\bf DTK:} DTK search and communication capabilities will deployed in a new, -lightweight library, ArborX, to provide these ECP investments to a broader -user base. +{\bf ArborX:} Continue performance engineering campaign and extend to +distributed search capabilities and communication and deploy in a variety of +applications. + +{\bf DTK:} Support parallel-in-time coupling in the ExaAM project for +simulations of metal powder bed additive manufacturing. {\bf Tasmanian:} Work will continue with the development of the asynchronous construction methods that exploit the native sparse grids DAG hierarchy. diff --git a/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/arborx_summit.png b/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/arborx_summit.png new file mode 100644 index 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z->eP$GES)(c@z$v+DZ@G_{8=MZ@^wU>UVkqRqv;Lj!evF<{Q~wiU)7Bz8>Rse5-B< z2AwvRv_FJ}Zbf?UZh6>L2fvMF{m;Dqe@ejqf80}w0JqEoSM=7PwWoME*z1K7RIyUt HGVH$qEfkS& literal 0 HcmV?d00001 From 3008282e9f2bf92189434c7b964d1f3cf95a6548 Mon Sep 17 00:00:00 2001 From: Andrey Prokopenko Date: Mon, 4 Nov 2019 15:29:44 -0500 Subject: [PATCH 5/5] Update ForTrilinos sections --- .../2.3.3.14-ALExa.tex | 66 ++++++------------- 1 file changed, 21 insertions(+), 45 deletions(-) diff --git a/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex b/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex index 40d25b90..054f60bd 100644 --- a/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex +++ b/projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/2.3.3.14-ALExa.tex @@ -23,10 +23,9 @@ \subsubsection{\stid{3.14} ALExa} optimization and efficient multi-physics simulations in projects such as ExaStar (Tasmanian); and % -(4) the ability to interface large and complex Fortran-based codes to the -growing collection of Trilinos advanced solver capabilities that can -utilize next-generation platforms, the interface is done without C/C++ -interface code (ForTrilinos). +(4) the ability to automatically interface Fortran-based codes to existing +large and complex C/C++ solftware libraries, such as Trilinos advanced solvers +that can utilize next-generation platforms. These capabilities are being developed through ongoing interactions with our @@ -107,9 +106,9 @@ \subsubsection{\stid{3.14} ALExa} {\bf ForTrilinos} (Fortran for Trilinos) {\it Purpose:} ForTrilinos provides a seamless pathway for large and complex -Fortran-based codes to access Trilinos without C/C++ interface code. -This access includes Fortran versions of Kokkos abstractions for code -execution and data management.. +Fortran-based codes to access Trilinos. In addition, the developed SWIG/Fortran +allows automatic generation of the interfaces to any C/C++ library for seamless +interaction with Fortran application. {\it Significance:} The Exascale Computing Project (ECP) requires the successful transformation and porting of many Fortran application codes in preparation for @@ -121,13 +120,14 @@ \subsubsection{\stid{3.14} ALExa} including its user interfaces. While C++ is advantageous for gaining access to the latest programming environments, it limits Trilinos usage via Fortran. -{\it SWIG capabilities:} an interface generator, SWIG, which the project is -extending, to create the object-oriented Fotran wrapper code that users can -access directly. This language translation will occur in both directions; -ForTrilinos will provide an inversion of control functionality that enables -custom extensions of the Trilinos solvers that are Fortran-based. Once the -ForTrilinos project is complete, a functional, extensible suite of capabilities -to access Trilinos on next-generation computing systems will be provided. +{\it SWIG capabilities:} The SWIG/Fortran interface generator, based on the +original SWIG, creates the object-oriented Fotran wrapper code that users can +access directly. This language translation will occur in both directions, +allowing, for example, an inversion of control functionality in ForTrilinos +that enables custom extensions of the Trilinos solvers that are Fortran-based. +Once the ForTrilinos project is complete, a functional, extensible suite of +capabilities to access Trilinos on next-generation computing systems will be +provided. {\it URL:} https://github.com/trilinos/ForTrilinos @@ -243,29 +243,9 @@ \subsubsection{\stid{3.14} ALExa} \caption{\label{fig:tasmanian-gpu}Tasmanian approximation (right) of neutrino capacities (left).} \end{figure} -{\bf ForTrilinos:} -Figure~\ref{fig:fortran_ioc} illustrates a new Inversion-of-Control~(IoC) -implementation in ForTrilinos. The new approach allows Fortran users to define -an operator by using a derived type on the Fortran side, and use Trilinos -algorithms, e.g. Krylov solvers, to solve the linear system with that operator. - -\begin{figure}[htb] - \centering - \includegraphics[scale=0.8,width=6in]{projects/2.3.3-MathLibs/2.3.3.14-ALExa-ForTrilinos/ForTrilinos_ioc} - \caption{\label{fig:fortran_ioc}The proposed Inversion-of-Control approach - allowing Fortran applications to define operators on Fortran side while - still using ForTrilinos types.} -\end{figure} - -This approach allows the user callback functions to interact with native Fortran -types and ForTrilinos class wrapper types. In the same vein, users would not -have to manually pass \texttt{type(C\_PTR)} instances into and out of the -callback function, as the C++ Fortran conversions can be tedious and -error-prone, which indeed is the motivation for using SWIG to generate -ForTrilinos. Another important feature is that it allows the application code -to extend Trilinos without having to generate any new interface code, either by -hand or using SWIG. In other words, the Fortran end user should not have to know -C++ or SWIG. +{\bf ForTrilinos:} ForTrilinos was updated to support nonlinear solvers. The +list of backends supported by ForTrilinos was expanded to include serial, +OpenMP and CUDA. A thorough unit testing suite was added. %---------------------------------------- @@ -286,19 +266,15 @@ \subsubsection{\stid{3.14} ALExa} {\bf ForTrilinos:} the next efforts will include \begin{enumerate} - \item \textbf{Provide wrappers for more libraries:} ForTrilinos will continue - efforts to increase the number of wrapped Trilinos libraries. The scheduled - release of the next phase of the project will include libraries - corresponding to nonlinear solvers, such as NOX. \item \textbf{Integrate developed capabilities into applications:} E3SM-MMF is an Earth system model development and simulation project. It relies on Trilinos for its implicit capabilities. The ForTrilinos project will integrate the developed nonlinear solver with IoC into E3SM-MMF to provide path forward to heterogeneous stack. - \item \textbf{Provide interfaces for heterogeneous platforms:} ForTrilinos - will develop support for heterogeneous memory through providing access to - Kokkos-based interfaces in Trilinos. This will allow full exposure to - Trilinos capabilities targeting Exascale machines. + \item \textbf{Integrate ForTrilinos with upstream Trilinos project:} + ForTrilinos will develop a support model to interact with upstream Trilinos + developers. This will allow a faster integration of new capabilities, and + more robust testing infrastructure. \end{enumerate} %----------------------------------------

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