A Glimpse of the Future of Scientific Programming

Hinsen, Konrad

doi:10.1109/mcse.2013.1

Cited by 7 publications

(6 citation statements)

References 4 publications

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“…However, due to lack of instrumentation and on-the-fly class modification APIs, the effort relied on static modifications of single class at a time without considering profiler feedback. Now-adays, JIT parallelization is being revisited, thanks to the proliferation of multicore/manycore systems and advancements in virtualization technologies [25][26][27][28]30]. …”

Section: Related Workmentioning

confidence: 99%

Just-in-Time Compilation-Inspired Methodology for Parallelization of Compute Intensive Java Code

Mustafa

Mahmood

Ghani

2017

Mehran Univ. res. j. eng. technol.

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Section: Related Workmentioning

confidence: 99%

Just-in-Time Compilation-Inspired Methodology for Parallelization of Compute Intensive Java Code

Mustafa

Mahmood

Ghani

2017

Mehran Univ. res. j. eng. technol.

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“…In this case, visual programming (VP) and domain-specific languages (DSLs) can be alternatives to low-level programming (Jones and Scaffidi 2011). Simpler and less error-prone than low-level languages (Hinsen 2013), DSLs are available as closed-source or open-source solutions (Papadimitriou et al 2009). VP, on the other hand, allows scientists to construct scientific models and equations by dragging and connecting components as in a CAD/CAM environment resembling data flow diagrams (Keller and Rimmon 1992;Rijnders, Spoelder and Groen 1993).…”

Section: How Is Scientific Software Developed and Used?mentioning

confidence: 99%

The Lens of the Lab: Design Challenges in Scientific Software

Queiroz¹,

Spitz²

2016

The International Journal of Design Management and Professional

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Playful and gameful design could improve the quality of scientific software. However, literature about gamification methods for that particular type of software is presently scarce. As an effort to fill that gap, this paper introduces a set of design challenges and opportunities that should be informative to professionals approaching the area. This research is based on literature review on scientific software development, also contemplating material on the gamification of science, software, and work. From the gathered information, we identify, map, and discuss key aspects of development and use of professional scientific software. Those findings are, then, formatted as a Design Lens-a set of questions designers should ask themselves to gain insight, from a particular perspective, on their work. We prop ose the Lens of the Lab as a design lens to support designers working in collaboration with scientists and software engineers in professional scientific software initiatives.

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“…Embedded DSLs have already been identified by others as a promising technique to facilitate scientific programming (e.g., [Hinsen 2013]), and are emerging for various domains, such as systems biology modeling (e.g., PySB [Lopez et al 2013], embedded in Python), machine learning (e.g., OptiML [Sujeeth et al 2011], embedded in Scala), and numerical analysis (e.g., Liszt [DeVito et al 2011], embedded in Scala). Other DSLs embedded in Scala deal, for example, with database access [Garcia et al 2010] or term rewriting [Sloane 2008].…”

Section: Related Workmentioning

confidence: 99%

Sessl

Ewald

Uhrmacher

2014

ACM Trans. Model. Comput. Simul.

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This article introduces SESSL (Simulation Experiment Specification via a Scala Layer), an embedded domain-specific language for simulation experiments. It serves as an additional software layer between users and simulation systems and is implemented in Scala. SESSL supports multiple simulation systems and offers various features (e.g., for experiment design, performance analysis, result reporting, and simulation-based optimization). It supports "cutting-edge" experiments by allowing to add custom code, enables a reuse of functionality across simulation systems, and improves the reproducibility of simulation experiments. ACM Reference Format:Roland Ewald and Adelinde M. Uhrmacher. 2014. SESSL: A domain-specific language for simulation experiments. ACM Trans. Model.

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A Glimpse of the Future of Scientific Programming

Cited by 7 publications

References 4 publications

Just-in-Time Compilation-Inspired Methodology for Parallelization of Compute Intensive Java Code

Just-in-Time Compilation-Inspired Methodology for Parallelization of Compute Intensive Java Code

The Lens of the Lab: Design Challenges in Scientific Software

Sessl

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