Automated Code Generation for Discontinuous Galerkin Methods

Ølgaard, Kristian Breum; Logg, Anders; Wells, Garth N.

doi:10.1137/070710032

Cited by 46 publications

(39 citation statements)

References 15 publications

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“…A number of research projects have implemented similar or related programming frameworks. Liszt [20] and FEniCS [30] specifically target mesh based computations.…”

Section: Related Workmentioning

confidence: 99%

OP2: An active library framework for solving unstructured mesh-based applications on multi-core and many-core architectures

Mudalige

Giles

Reguly

et al. 2012

2012 Innovative Parallel Computing (InPar)

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OP2 is an "active" library framework for the solution of unstructured mesh-based applications. It utilizes sourceto-source translation and compilation so that a single application code written using the OP2 API can be transformed into different parallel implementations for execution on different back-end hardware platforms. In this paper we present the design of the current OP2 library, and investigate its capabilities in achieving performance portability, near-optimal performance, and scaling on modern multi-core and many-core processor based systems. A key feature of this work is OP2's recent extension facilitating the development and execution of applications on a distributed memory cluster of GPUs.We discuss the main design issues in parallelizing unstructured mesh based applications on heterogeneous platforms. These include handling data dependencies in accessing indirectly referenced data, the impact of unstructured mesh data layouts (array of structs vs. struct of arrays) and design considerations in generating code for execution on a cluster of GPUs. A representative CFD application written using the OP2 framework is utilized to provide a contrasting benchmarking and performance analysis study on a range of multicore/many-core systems. These include multi-core CPUs from Intel (Westmere and Sandy Bridge) and AMD (MagnyCours), GPUs from NVIDIA (GTX560Ti, Tesla C2070), a distributed memory CPU cluster (Cray XE6) and a distributed memory GPU cluster (Tesla C2050 GPUs with InfiniBand). OP2's design choices are explored with quantitative insights into their contributions to performance. We demonstrate that an application written once at a high-level using the OP2 API can be easily portable across a wide range of contrasting platforms and is capable of achieving near-optimal performance without the intervention of the domain application programmer.

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“…A number of research projects have implemented similar or related programming frameworks. Liszt [20] and FEniCS [30] specifically target mesh based computations.…”

Section: Related Workmentioning

confidence: 99%

OP2: An active library framework for solving unstructured mesh-based applications on multi-core and many-core architectures

Mudalige

Giles

Reguly

et al. 2012

2012 Innovative Parallel Computing (InPar)

View full text Add to dashboard Cite

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“…These include Firedrake [1], FENiCS [25] and Liszt [14], OP2 [6] for unstructured mesh applications and Paraiso [24], Ypnos [26], Pochoir [30] and SBLOCK [12] for explicit stencil based applications (structured mesh applications).…”

Section: Related Workmentioning

confidence: 99%

“…The FEniCS [25] project defines a high-level language, UFL, for the specification of finite element algorithms. The FEniCS abstraction allows the user to express the problem in terms of differential equations, leaving the details of the implementation to a lower level library.…”

Section: Related Workmentioning

confidence: 99%

Performance Analysis of a High-Level Abstractions-Based Hydrocode on Future Computing Systems

Mudalige

Reguly

Giles

et al. 2015

Lecture Notes in Computer Science

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Abstract. In this paper we present research on applying a domain specific high-level abstractions (HLA) development strategy with the aim to "future-proof" a key class of high performance computing (HPC) applications that simulate hydrodynamics computations at AWE plc. We build on an existing high-level abstraction framework, OPS, that is being developed for the solution of multi-block structured mesh-based applications at the University of Oxford. OPS uses an "active library" approach where a single application code written using the OPS API can be transformed into different highly optimized parallel implementations which can then be linked against the appropriate parallel library enabling execution on different back-end hardware platforms. The target application in this work is the CloverLeaf mini-app from Sandia National Laboratory's Mantevo suite of codes that consists of algorithms of interest from hydrodynamics workloads. Specifically, we present (1) the lessons learnt in re-engineering an industrial representative hydro-dynamics application to utilize the OPS high-level framework and subsequent code generation to obtain a range of parallel implementations, and (2) the performance of the auto-generated OPS versions of CloverLeaf compared to that of the performance of the hand-coded original CloverLeaf implementations on a range of platforms. Benchmarked systems include Intel multi-core CPUs and NVIDIA GPUs, the Archer (Cray XC30) CPU cluster and the Titan (Cray XK7) GPU cluster with different parallelizations (OpenMP, OpenACC, CUDA, OpenCL and MPI). Our results show that the development of parallel HPC applications using a high-level framework such as OPS is no more time consuming nor difficult than writing a one-off parallel program targeting only a single parallel implementation. However the OPS strategy pays off with a highly maintainable single application source, through which multiple parallelizations can be realized, without compromising performance portability on a range of parallel systems.

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“…Weak no-normal-flux boundary conditions are applied to the advection operator. The viscous term is treated using an interior penalty method [52,53] with a penalty parameter value of η = 10. Weak Dirichlet boundary conditions, corresponding to (16), are applied to the viscous term.…”

Section: Incompressible Navier-stokesmentioning

confidence: 99%

Rapid development and adjoining of transient finite element models

Maddison

Farrell

2014

Computer Methods in Applied Mechanics and Engineering

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Recent advances in high level finite element systems have allowed for the symbolic representation of discretisations and their efficient automated implementation as model source code. This allows for the extremely compact implementation of complex non-linear models in a handful of lines of high level code. In this work we extend the high level finite element FEniCS system to introduce an abstract representation of the temporal discretisation: this enables the similarly rapid development of transient finite element models. Efficiency is achieved via aggressive optimisations that exploit the temporal structure, such as automated pre-assembly and caching of forms, and the robust re-use of matrix factorisations and preconditioner data. The resulting models are as fast or faster than hand-optimised finite element codes. The high level representation of the system remains extremely compact and easily manipulated. This structure is exploited to derive the associated discrete adjoint model automatically, with the adjoint model inheriting the performance advantages of the forward model. Combined, this provides a system for the rapid development of efficient transient models, together with their discrete adjoints.

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Automated Code Generation for Discontinuous Galerkin Methods

Cited by 46 publications

References 15 publications

OP2: An active library framework for solving unstructured mesh-based applications on multi-core and many-core architectures

OP2: An active library framework for solving unstructured mesh-based applications on multi-core and many-core architectures

Performance Analysis of a High-Level Abstractions-Based Hydrocode on Future Computing Systems

Rapid development and adjoining of transient finite element models

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