Liszt

DeVito, Zachary; Joubert, N.; Palacios, Francisco; Oakley, S. P.; Medina, Montserrat; Barrientos, Mike; Elsen, Erich; Ham, Frank; Aiken, Alex; Duraisamy, Karthik; Darve, Eric; Alonso, Juan J.; Hanrahan, Pat

doi:10.1145/2063384.2063396

Cited by 133 publications

(15 citation statements)

References 28 publications

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“…Most scientific DSLs are embedded in a general-purpose programming language. A few almost arbitrarily selected examples are Liszt, a DSL for mesh definitions in finite-element computation, embedded in Scala (DeVito et al, 2011), Kendrick, a DSL for ODE-based models in epidemiology, embedded in Smalltalk (Bui et al, 2016), and an unnamed DSL for micromagnetics, embedded in Python (Beg, Pepper & Fangohr, 2017). The choice for an embedded DSL is typically motivated by simpler implementation and integration into an existing ecosystem of development tools and libraries.…”

Section: Digital Scientific Notationsmentioning

confidence: 99%

Verifiability in computer-aided research: the role of digital scientific notations at the human-computer interface

Hinsen

2018

PeerJ Computer Science

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Most of today's scientific research relies on computers and software for processing scientific information. Examples of such computer-aided research are the analysis of experimental data or the simulation of phenomena based on theoretical models. With the rapid increase of computational power, scientific software has integrated more and more complex scientific knowledge in a black-box fashion. As a consequence, its users do not know, and do not even have a chance of finding out, which assumptions and approximations their computations are based on. This black-box nature of scientific software has made the verification of much computer-aided research close to impossible. The present work starts with an analysis of this situation from the point of view of human-computer interaction in scientific research. It identifies the key role of digital scientific notations at the human-computer interface, reviews the most popular ones in use today, and describes a proof-of-concept implementation of Leibniz, a language designed as a verifiable digital scientific notation for models formulated as mathematical equations.

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Section: Digital Scientific Notationsmentioning

confidence: 99%

Verifiability in computer-aided research: the role of digital scientific notations at the human-computer interface

Hinsen

2018

PeerJ Computer Science

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“…Wellknown frameworks and applications include Nek5000 [Fischer et al 2008], the FEniCS project [Logg et al 2012], Fluidity [AMCG 2010], and of course Firedrake. Numerical integration based on quadrature, as in Firedrake, is usually employed to implement the local assembly phase.…”

Section: Related Workmentioning

confidence: 99%

Cross-Loop Optimization of Arithmetic Intensity for Finite Element Local Assembly

Luporini

Vărbănescu

Rathgeber

et al. 2015

ACM Trans. Archit. Code Optim.

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We study and systematically evaluate a class of composable code transformations that improve arithmetic intensity in local assembly operations, which represent a significant fraction of the execution time in finite element methods. Their performance optimization is indeed a challenging issue. Even though affine loop nests are generally present, the short trip counts and the complexity of mathematical expressions, which vary among different problems, make it hard to determine an optimal sequence of successful transformations. Our investigation has resulted in the implementation of a compiler (called COFFEE) for local assembly kernels, fully integrated with a framework for developing finite element methods. The compiler manipulates abstract syntax trees generated from a domain-specific language by introducing domain-aware optimizations for instruction-level parallelism and register locality. Eventually, it produces C code including vector SIMD intrinsics. Experiments using a range of real-world finite element problems of increasing complexity show that significant performance improvement is achieved. The generality of the approach and the applicability of the proposed code transformations to other domains is also discussed.

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“…Examples in the area of CFD are SBLOCK [27] for structured grids, OP2 [28,29] and Liszt [30] for general unstructured grid computations, and FEniCS for finite-element computations [31]. SBLOCK uses an algorithm specification expressed in Python to generate the required code for different platforms.…”

Section: Software Researchmentioning

confidence: 99%

Trends in high-performance computing for engineering calculations

Giles

Reguly

2014

Phil. Trans. R. Soc. A.

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High-performance computing has evolved remarkably over the past 20 years, and that progress is likely to continue. However, in recent years, this progress has been achieved through greatly increased hardware complexity with the rise of multicore and manycore processors, and this is affecting the ability of application developers to achieve the full potential of these systems. This article outlines the key developments on the hardware side, both in the recent past and in the near future, with a focus on two key issues: energy efficiency and the cost of moving data. It then discusses the much slower evolution of system software, and the implications of all of this for application developers.

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Liszt

Cited by 133 publications

References 28 publications

Verifiability in computer-aided research: the role of digital scientific notations at the human-computer interface

Verifiability in computer-aided research: the role of digital scientific notations at the human-computer interface

Cross-Loop Optimization of Arithmetic Intensity for Finite Element Local Assembly

Trends in high-performance computing for engineering calculations

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