# numerics

Published articles for numerics.

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.

## 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?