Tag Archives: Simulation

Global Systems Science meets Programming Languages and Systems

Martin Elsman from HIPERFIT (@DIKU.dk) will present GSS meets Programming Languages and Systems in the workshop on GSS Languages, 2013-06-11.
Abstract In this talk, we demonstrate how functional programming and domain specific languages, in particular, can be useful for effectively deriving performance efficient programs and systems. As an example, we outline a system for specifying financial contracts (used in practice by the financial industry) and demonstrate the effect of applying programming language technology to derive tools for pricing contracts efficiently on modern parallel hardware. We argue that research in managing and querying big data and efficiently performing big computations (simulations), as for instance carried out by the HIPERFIT research center, is a central ingredient of the development of a Global Systems Science.

Welcome,
Patrik Jansson

CFP: Functional High-Performance Computing (FHPC 2013)

I just want to “advertise” the Functional High-Performance Computing workshop which this year has “Large-Scale Simulation” as their theme which I think fits very well with GSS. Half of the organizers (Fritz Henglein and Jost Berthold) are at the HIPERFIT research center in Denmark (HIPERFIT: research in tailor-made expressive programming languages, frameworks, tools and technologies for financial modeling, and effective use of modern parallel hardware without compromising correctness, transparency or portability.)

http://hiperfit.dk/fhpc13.html

Kind regards,

Patrik Jansson

 

 

The FHPC workshop aims at bringing together researchers exploring uses
of functional (or more generally, declarative or high-level) programming
technology in application domains where large-scale computations arise
naturally and high performance is essential. Such computations would
typically — but not necessarily — involve execution on highly parallel
systems ranging from multi-core multi-processor systems to graphics
accelerators (GPGPUs), reconfigurable hardware (FPGAs), large-scale
compute clusters or any combination thereof. It is becoming apparent
that radically new and well founded methodologies for programming such
systems are required to address their inherent complexity and to
reconcile execution performance with programming productivity.

 

ICT challenges for GSS, part 3

Notes from The Saturday ICT workshop (by Patrik Jansson, 2012-11-22)

(Ilan Chabay started out with a summary of the Thursday and Friday Narratives workshops – that part is reported elsewhere.)

Second topic was introduced by Jeremy Gibbons. We need robust modelling – we cannot assume a single shared context. Even for a long-lived single-person project, but more urgently for larger collaborations. We need assumptions to be explicit, documented, transparent, checkable. Challenge 1: make computational science results transparent and repeatable. Challenge 2: provide languages which let you write a high-level model of your program and let the computer generate the low-level code.

Third Michael Resch talked about “Verification and Validation of Simulation Models”. There is a chain (or tower) of models from theory, through modelling, numeric modelling (like discretization), programming, running and interpreting the results. To be sure about the validity of the results we need Challenge 3: validation and verification at each step (each level). This is a major challenge with many sub-parts. If we carefully explain all the potential “bugs” which could in principle invalidate our results we could easily project the image that “they have no credibility”. Thus there is the pedagogical Challenge 4: how to present results with uncertainties? There is also a historical dimension as science moves forward and consensus changes (due to improvements of theory, models and data). Journalists dig up old results (which we now know are incorrect) and make headlines based on the “contradictions” found.

Last discussion topic was introduced by David De Roure: “Knowledge Infrastructure for Global Systems Science”. This comes back to the transparency and repeatability (and multiple meanings of that) mentioned by Jeremy. The main message was that methods are as important as the data. Bundles of workflows, documents and data make up “computational research objects”. An important Challenge 5 here is how to represent these research objects so that they can be mixed and matched freely. Some support for automatic curation and repair would also be needed.

Saturday ICT chairs + presenters

  • Patrik Jansson – Chalmers Univ. of Techn., patrikj@chalmers.se
    • Co-chair of “Models and Narratives in GSS”
  • Ilan Chabay
    • Co-chair and talk: “Models and Narratives in Global Systems Science”
  • Jeremy Gibbons
    • Talk: Dependable Modelling
  • Michael Resch
    • Talk: Verification and Validation of Simulation Models
  • David De Roure;
    • Talk: “Knowledge Infrastructure for Global Systems Science”

Other participants:

  • Ulf Dahlsten (first hour)
  • Ralph Dum
  • David Tabara
  • several others (unfortunately I did not make a list)