HPTCDL2015 - Second Workshop for High Performance Technical Computing in Dynamic Languages
Workshop date: Sunday, November 15, 2015
Austin Convention Center, Austin, Texas, USA
Held in conjunction with SC15: The International Conference on High Performance Computing, Networking, Storage and Analysis.
Call for participation
Dynamic high-level languages such as Julia, Maple®, Mathematica®, MATLAB®, Octave, Python/NumPy/SciPy, R, and Scilab are rapidly gaining popularity with computational scientists and engineers. High-level languages offer the advantage of writing legible and expressive code, which facilitate the rapid prototyping of programs for technical computing. However, high-level languages have a reputation for being subperformant and being difficult to deploy scalably on massively parallel architectures such as clusters, cloud servers, and supercomputers. Thus, some scientific developers resort to prototyping in one language and deploying at scale in another, thus incurring the costs associated with reimplementing a scientific code at least twice. This two-language problem is but one example of the technical challenges associated with the use of dynamic languages on massively parallel platforms.
This workshop aims to bring together users, developers, and practitioners of dynamic technical computing languages, regardless of language, affiliation or discipline, to discuss topics of common interest. Disciplines affiliated the broad umbrella of computational science and engineering, such as physical sciences, biological sciences, social sciences, digital humanities, mathematics, statistics, computer science, all share common challenges associated with the implementation of computational models in extant programming languages. Examples of such topics include code performance, the use of abstractions for composability and reusability, the two-language problem, best practices for software development and engineering, and the implications of such code design decisions for applications in visualization, information retrieval and big data analytics. We expect that these challenges are common to researchers and programmers in academia, national laboratories and industry.
Key dates
Paper submissions due: Monday, August 31
Notification to authors of acceptance: Monday, September 21
E-copyright forms and camera-ready papers due: Thursday, October 8
Submission information
Please submit a PDF version of your article to our EasyChair website. We strongly recommend using the ACM SIGHPC Tighter Alternate style template for submissions. There is no official page limit but we encourage all submissions to be as concise as possible.
Organizers
- Jiahao Chen, MIT
- Alan Edelman, MIT
- Wade Shen, MIT Lincoln Labs
- Andy Terrel, Fashion Metric, Inc. and The NumFOCUS Foundation
Program committee
- Douglas Bates, Wisconsin-Madison
- Stephen Boyd, Stanford
- Claude Gomez, Scilab Enterprises
- Ryan Hafen, PNNL
- Tim Holy, WUSTL
- Steven Johnson, MIT
- Michael Kane, Yale
- Dahua Lin, TTIC
- Travis Oliphant, Continuum Analytics
- Duncan Temple Lang, UC Davis
- Juan Pablo Vielma, MIT
- John Myles White, Facebook