# Numerical Methods

Published articles for Numerical Methods.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Stochastic Systems, Fokker-Planck and the Heat Equation via Haskell

DevFeed: [Stochastic Systems, Fokker-Planck and the Heat Equation via Haskell](<https://devfeed.tech/articles/stochastic-systems-fokker-planck-and-the-heat-equation-via-haskell-36145.md>)

Original publisher: [Read original article](<https://idontgetoutmuch.wordpress.com/2020/04/26/stochastic-systems-fokker-planck-and-the-heat-equation-via-haskell/>)

Author: Dominic Steinitz

Published: 2020-04-26T14:20:10Z

Content type: tutorial

Language: en

Sources: [Maths, Stats & Functional Programming](<https://devfeed.tech/sources/maths-stats-functional-programming.md>)

Topics: [systems](<https://devfeed.tech/topics/systems.md>), [Haskell](<https://devfeed.tech/topics/haskell.md>), [Library](<https://devfeed.tech/topics/library.md>), [C](<https://devfeed.tech/topics/c.md>)

Tags: [c](<https://devfeed.tech/tags/c.md>), [example](<https://devfeed.tech/tags/example.md>), [examples](<https://devfeed.tech/tags/examples.md>), [haskell](<https://devfeed.tech/tags/haskell.md>), [library](<https://devfeed.tech/tags/library.md>), [numerical-methods](<https://devfeed.tech/tags/numerical-methods.md>), [numerics](<https://devfeed.tech/tags/numerics.md>), [partial-differential-equations](<https://devfeed.tech/tags/partial-differential-equations.md>), [source](<https://devfeed.tech/tags/source.md>), [system](<https://devfeed.tech/tags/system.md>), [systems](<https://devfeed.tech/tags/systems.md>), [using](<https://devfeed.tech/tags/using.md>), [with](<https://devfeed.tech/tags/with.md>)

### AI overview

A short Haskell example models a stochastic system with the Fokker-Planck method, converts it to a partial differential equation, and solves a two-dimensional equation using SUNDIALS through the hmatrix-sundials library. The example is based on C examples included with the SUNDIALS source.

### Source excerpt

This is a short example of taking a stochastic system, using Fokker-Planck to convert it to a PDES and using SUNDIALS to solve a 2D partial differential equation in Haskell via the hmatrix-sundials library. The example is taken from the C examples that come with the SUNDIALS source. Here's the full blog.

## Workshop on Numerical Programming in Functional Languages (NPFL)

DevFeed: [Workshop on Numerical Programming in Functional Languages (NPFL)](<https://devfeed.tech/articles/workshop-on-numerical-programming-in-functional-languages-npfl-36139.md>)

Original publisher: [Read original article](<https://idontgetoutmuch.wordpress.com/2018/04/23/1108/>)

Author: Dominic Steinitz

Published: 2018-04-23T15:54:27Z

Content type: news

Language: en

Sources: [Maths, Stats & Functional Programming](<https://devfeed.tech/sources/maths-stats-functional-programming.md>)

Topics: [Programming](<https://devfeed.tech/topics/programming.md>), [Code](<https://devfeed.tech/topics/code.md>)

Tags: [demo](<https://devfeed.tech/tags/demo.md>), [functional](<https://devfeed.tech/tags/functional.md>), [international](<https://devfeed.tech/tags/international.md>), [keynote](<https://devfeed.tech/tags/keynote.md>), [languages](<https://devfeed.tech/tags/languages.md>), [numerical-methods](<https://devfeed.tech/tags/numerical-methods.md>), [programming](<https://devfeed.tech/tags/programming.md>), [submission](<https://devfeed.tech/tags/submission.md>), [talk](<https://devfeed.tech/tags/talk.md>), [video](<https://devfeed.tech/tags/video.md>), [workshop](<https://devfeed.tech/tags/workshop.md>)

### AI overview

An announcement invites submissions for the first ACM SIGPLAN International Workshop on Numerical Programming in Functional Languages, co-located with ICFP in September in St. Louis. Submissions should describe a talk and may be accompanied by slides or a demo; talks are planned to be recorded.

### Source excerpt

I'm the chair this year for the first(!) ACM SIGPLAN International Workshop on Numerical Programming in Functional Languages (NPFL), which will be co-located with ICFP this September in St. Louis, Missouri, USA. Please consider submitting something! All you have to do is submit between half a page and a page describing your talk. There will ... Continue reading Workshop on Numerical Programming in Functional Languages (NPFL)

## Implicit Runge Kutta and GNU Scientific Library

DevFeed: [Implicit Runge Kutta and GNU Scientific Library](<https://devfeed.tech/articles/implicit-runge-kutta-and-gnu-scientific-library-36138.md>)

Original publisher: [Read original article](<https://idontgetoutmuch.wordpress.com/2018/03/04/implicit-runge-kutta-and-gnu-scientific-library/>)

Author: Dominic Steinitz

Published: 2018-03-04T13:59:17Z

Content type: tutorial

Language: en

Sources: [Maths, Stats & Functional Programming](<https://devfeed.tech/sources/maths-stats-functional-programming.md>)

Topics: [Algorithm](<https://devfeed.tech/topics/algorithm.md>), [Haskell](<https://devfeed.tech/topics/haskell.md>), [Code](<https://devfeed.tech/topics/code.md>), [Library](<https://devfeed.tech/topics/library.md>)

Tags: [algorithm](<https://devfeed.tech/tags/algorithm.md>), [c](<https://devfeed.tech/tags/c.md>), [code](<https://devfeed.tech/tags/code.md>), [haskell](<https://devfeed.tech/tags/haskell.md>), [implementation](<https://devfeed.tech/tags/implementation.md>), [nix](<https://devfeed.tech/tags/nix.md>), [numerical-methods](<https://devfeed.tech/tags/numerical-methods.md>)

### AI overview

Technical notes on implicit Runge-Kutta methods, including IRK2 and IRK4, their Butcher tableaux, and an implementation using the GNU Scientific Library and Haskell.

### Source excerpt

Introduction These are some very hasty notes on Runge-Kutta methods and IRK2 in particular. I make no apologies for missing lots of details. I may try and put these in a more digestible form but not today. Some Uncomprehensive Theory In general, an implicit Runge-Kutta method is given by where and Traditionally this is written ... Continue reading Implicit Runge Kutta and GNU Scientific Library

## Comparing Haskell and Julia for High-Performance Numerical Code

DevFeed: [Comparing Haskell and Julia for High-Performance Numerical Code](<https://devfeed.tech/articles/haskell-for-numerics-36136.md>)

Original publisher: [Read original article](<https://idontgetoutmuch.wordpress.com/2017/06/02/1090/>)

Author: Dominic Steinitz

Published: 2017-06-02T15:47:12Z

Content type: opinion

Language: en

Sources: [Maths, Stats & Functional Programming](<https://devfeed.tech/sources/maths-stats-functional-programming.md>)

Topics: [Haskell](<https://devfeed.tech/topics/haskell.md>), [The Julia Language](<https://devfeed.tech/topics/julia.md>), [Programming](<https://devfeed.tech/topics/programming.md>), [floating-point](<https://devfeed.tech/topics/floating-point.md>)

Tags: [analysis](<https://devfeed.tech/tags/analysis.md>), [code](<https://devfeed.tech/tags/code.md>), [haskell](<https://devfeed.tech/tags/haskell.md>), [llvm](<https://devfeed.tech/tags/llvm.md>), [numerical-methods](<https://devfeed.tech/tags/numerical-methods.md>), [numerics](<https://devfeed.tech/tags/numerics.md>), [programming](<https://devfeed.tech/tags/programming.md>)

### AI overview

The article compares Julia with a Haskell approach using the Accelerate domain-specific embedded language for numerical computing. It discusses the goal of combining type safety with high performance and the motivation of supporting statistical inference methods.

### Source excerpt

Introduction Summary Back in January, a colleague pointed out to me that GHC did not produce very efficient code for performing floating point abs. I have yet to produce a write-up of my notes about hacking on GHC: in summary it wasn't as difficult as I had feared and the #ghc folks were extremely helpful. ... Continue reading Haskell for Numerics?