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Accelerating linear solvers for Stokes problems with c plus plus metaprogramming

JOURNAL OF cOMPUTATIONAL ScIENcE 2021年 49卷 101285-101285页

作者： Demidov, Denis Mu, Lin Wang, Bin Russian Acad Sci Sci Res Inst Syst Anal Kazan Branch Joint Supercomp Ctr Lobachevsky St 2-31 Kazan 420111 Russia Univ Georgia Dept Math Athens GA 30605 USA Louisiana State Univ Craft & Hawkins Dept Petr Engn Baton Rouge LA 70803 USA

The efficient solution of large sparse saddle point systems is very important in computational fluid mechanics. The discontinuous Galerkin finite element methods have become increasingly popular for incompressible flow problems but their application is limited due to high computational cost. We describe c++ programming techniques that may help to accelerate linear solvers for such problems. The approach is based on the policy based design pattern and partial template specialization, and is implemented in the open source AMGcL library. The efficiency is demonstrated with the example of accelerating an iterative solver of a discontinuous Galerkin finite element method for the Stokes problem. The implementation allows selecting algorithmic components of the solver by adjusting template parameters without any changes to the codebase. It is possible to switch the system matrix to use small statically sized blocks to store the nonzero values, or use a mixed precision solution, which results in up to 4 times speedup, and reduces the memory footprint of the algorithm by about 40%. We evaluate both monolithic and composite preconditioning strategies for 3 benchmark problems. The performance of the proposed solution is compared with a multithreaded direct Pardiso solver and a parallel iterative PETSc solver.

关键词： Stokes problem c plus plus metaprogramming Algebraic multigrid Scalability

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Semantic and behavioral library transformations

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INFORMATION AND SOFTWARE TEcHNOLOGY 2002年第13期44卷 797-810页

作者： Schupp, S Gregor, D Musser, D Liu, SM Rensselaer Polytech Inst Dept Comp Sci Troy NY 12180 USA Hewlett Packard Corp Cupertino CA USA

While software methodology encourages the use of libraries and advocates architectures of layered libraries, in practice the composition of libraries is not always seamless and the combination of two well-designed libraries not necessarily well designed, since it could result in suboptimal call sequences, lost functionality, or avoidable overhead. In this paper we introduce Simplicissimus, a framework for rewrite-based source code transformations that allows for code replacement in a systematic and safe manner. We discuss the design and implementation of the framework and illustrate its functionality with applications in several areas. (c) 2002 Elsevier Science B.V. All rights reserved.

关键词： active libraries extensible compilers concept-based transformations c plus plus metaprogramming

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A MultiGPU Performance-Portable Solution for Array Programming Based on Kokkos 9

A MultiGPU Performance-Portable Solution for Array Programmi...

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9th AcM SIGPLAN International Workshop on Libraries, Languages and compilers for Array Programming (ARRAY)

作者： Valero-Lara, Pedro Vetter, Jeffrey S. Oak Ridge Natl Lab Oak Ridge TN 37830 USA

ISBN: (纸本)9798400701696

MultiGPU nodes are widely used in high-performance computing and data centers. However, current programming models do not provide transparent, and portable support for automatically targeting multiple GPUs within a node. In this paper, we describe a new application programming interface based on the Kokkos programming model to enable array computation on multiple GPUs in a transparent and portable way across both NVIDIA and AMD GPUs. We implement different variations of this technique to accommodate the exchange of stencils, and we provide autotuning to select the proper number of GPUs, depending on the computational cost of the operations to be computed on arrays. We evaluate our multiGPU extension on Summit (#5 TOP500), with six NVIDIA V100 Volta GPUs per node, and crusher that contains identical hardware/software as Frontier (#1 TOP500), with four AMD MI250X GPUs, each with 2 Graphics compute Dies (GcDs) for a total of 8 GcDs per node. We also compare the performance of this solution against the use of MPI + Kokkos. Our evaluation shows that the new Kokkos solution provides good scalability for many GPUs. than MPI + Kokkos.

关键词： Array programming c plus plus metaprogramming multiGPU performance portability productivity autotuning parallel programming model Kokkos MPI cUDA HIP

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sKokkos: Enabling Kokkos with Transparent Device Selection on Heterogeneous Systems using OpenAcc 24

sKokkos: Enabling Kokkos with Transparent Device Selection o...

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7th International conference on High Performance computing in Asia-Pacific Region (HPc Asia)

作者： Valero-Lara, Pedro Lee, Seyong Denny, Joel Teranishi, Keita Vetter, Jeffrey S. Gonzalez-Tallada, Marc Oak Ridge Natl Lab Oak Ridge TN 37830 USA Univ Politecn Cataluna Barcelona Spain

ISBN: (纸本)9798400708893

This paper presents a new feature to enable Kokkos with transparent device selection. For application developers, it is not easy to identify which device is the most appropriate to use in a heterogeneous system, since this depends on the characteristics of both the application and the hardware. In Kokkos, a backend is associated with one specific programming model/hardware. Programmers decide which backend to use at compilation time. This new feature implemented on the OpenAcc backend eliminates the burden of deciding which device to use, providing a highly productive programming solution for Kokkos applications. This work includes implementation details and a performance study conducted with a set of mini-benchmarks (i.e., AXPY and dot product), kernels (Lattice-Bolzmann method), and two mini-apps (LULESH and miniFE) on two heterogeneous systems with different hardware capabilities. This new Kokkos feature provides high accelerations of up to 35x thanks to automatic and transparent device selection.

关键词： Kokkos OpenAcc c plus plus metaprogramming Heterogeneous Systems cPU GPU Parallel Programming Models Auto-tuning

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KokkAcc: Enhancing Kokkos with OpenAcc 9

KokkACC: Enhancing Kokkos with OpenACC

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9th Workshop on Accelerator Programming Using Directives (WAccPD)

作者： Valero-Lara, Pedro Lee, Seyong Gonzalez-Tallada, Marc Denny, Joel Vetter, Jeffrey S. Oak Ridge Natl Lab ORNL Oak Ridge TN 37830 USA

ISBN: (纸本)9781665490191

Template metaprogramming is gaining popularity as a high-level solution for achieving performance portability on heterogeneous computing resources. Kokkos is a representative approach that offers programmers high-level abstractions for generic programming while most of the device-specific code generation and optimizations are delegated to the compiler through template specializations. For this, Kokkos provides a set of device-specific code specializations in multiple back ends, such as cUDA and HIP. Unlike cUDA or HIP, OpenAcc is a high-level and directive-based programming model. This descriptive model allows developers to insert hints (pragmas) into their code that help the compiler to parallelize the code. The compiler is responsible for the transformation of the code, which is completely transparent to the programmer. This paper presents an OpenAcc back end for Kokkos: KokkAcc. As an alternative to Kokkos's existing device-specific back ends, KokkAcc is a multi-architecture back end providing a high-productivity programming environment enabled by OpenAcc's high-level and descriptive programming model. Moreover, we have observed competitive performance;in some cases, KokkAcc is faster (up to 9x) than NVIDIA's cUDA back end and much faster than OpenMP's GPU offloading back end. This work also includes implementation details and a detailed performance study conducted with a set of mini-benchmarks (AXPY and DOT product) and three mini-apps (LULESH, miniFE and SNAP, a LAMMPS proxy mini-app).

关键词： OpenAcc c plus plus metaprogramming Kokkos cUDA OpenMP Target Parallel Programming Models

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Enhancing Kokkos with OpenAcc

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INTERNATIONAL JOURNAL OF HIGH PERFORMANcE cOMPUTING APPLIcATIONS 2024年第5期38卷 409-426页

作者： Valero-Lara, Pedro Lee, Seyong Gonzalez-Tallada, Marc Denny, Joel Teranishi, Keita Vetter, Jeffrey S. Oak Ridge Natl Lab 1 Bethel Valley Rd Oak Ridge TN 37830 USA Univ Politecn Cataluna Barcelona Spain

c++ template metaprogramming has emerged as a prominent approach for achieving performance portability in heterogeneous computing. Kokkos represents a notable paradigm in this domain, offering programmers a suite of high-level abstractions for generic programming while deferring much of the device-specific code generation and optimization to the compiler through template specializations. Kokkos furnishes a range of device-specific code specializations across multiple back ends, including cUDA and HIP. Diverging from conventional back ends, the OpenAcc implementation presents a high-level, multicompiler, multidevice, and directive-based programming model. This paper presents recent advancements in the OpenAcc back end for Kokkos (i.e., KokkAcc) and focuses on its integration into the Kokkos ecosystem, exploration of automatic device selection capabilities to enhance productivity, and performance evaluation on modern hardware such as NVIDIA H100 GPUs. The study includes implementation details and a thorough performance assessment across various computational benchmarks, including minibenchmarks (AXPY and DOT product), miniapps (LULESH, MiniFE, and SNAP-LAMMPS), and a scientific kernel based on the lattice Boltzmann method.

关键词： OpenAcc c plus plus metaprogramming Kokkos cUDA OpenMP target parallel programming models

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