How do you write data structures that are as efficient as possible in GHC? [closed]

by

That’s a big topic! Most has been explained elsewhere, so I won’t try to write a book chapter right here. Instead:

  • Real World Haskell, ch 25, “Performance” – discusses profiling, simple specialization and unpacking, reading Core, and some optimizations.

Johan Tibell is writing a lot on this topic:

And some things from here:

  • Reading GHC Core
  • How GHC does optimization
  • Profiling for performance
  • Tweaking GC settings
  • General improvements
  • More on unpacking
  • Unboxing and strictness

And some other things:

Related Contents:

  1. lenses, fclabels, data-accessor – which library for structure access and mutation is better
  2. Haskell’s algebraic data types
  3. What is the benefit of purely functional data structure?
  4. Doubly Linked List in a Purely Functional Programming Language
  5. How does a hash table work?
  6. Difference between binary tree and binary search tree
  7. golang why don’t we have a set datastructure [closed]
  8. Are duplicate keys allowed in the definition of binary search trees?
  9. Test whether a list contains a specific value in Clojure
  10. How do I represent a hextile/hex grid in memory?
  11. When to use Preorder, Postorder, and Inorder Binary Search Tree Traversal strategies
  12. Advantages of Binary Search Trees over Hash Tables
  13. When would I want to use a heap?
  14. Data structure: insert, remove, contains, get random element, all at O(1)
  15. Practical uses of different data structures [closed]
  16. Efficient (and well explained) implementation of a Quadtree for 2D collision detection [closed]
  17. What is the difference between a KD-tree and a R-tree?
  18. When to choose RB tree, B-Tree or AVL tree?
  19. Difference between “Complete binary tree”, “strict binary tree”,”full binary Tree”?
  20. Difference between red-black trees and AVL trees
  21. Statistical performance of purely functional maps and sets
  22. Why is it better to have 100 functions operate on one data structure than 10 functions on 10 data structure
  23. Designing a web crawler
  24. What’s a RDF triple?
  25. Opposite of Bloom filter?
  26. How would you represent a Rubik’s Cube in code?
  27. What is the intuition behind the Fibonacci heap data structure?
  28. Why do we need Deque data structures in the real world? [closed]
  29. Chained Hash Tables vs. Open-Addressed Hash Tables
  30. Interview question: data structure to set all values in O(1)
  31. Why hashmap lookup is O(1) i.e. constant time?
  32. Stack and Queue, Why?
  33. Repository pattern vs. “smart” business objects [closed]
  34. What is the Zipper data structure and should I be using it?
  35. data structure used to implement UNDO and REDO option
  36. What is the distinction between sparse and dense graphs?
  37. What are “sums-and-products” data structures?
  38. Data structure for text editor
  39. What are good examples of problems that graphs can solve better than the alternative? [closed]
  40. Red Black Tree versus B Tree
  41. Representing A Tree in Clojure
  42. Why code-as-data?
  43. What is an “internal node” in a binary search tree?
  44. Advanced data structures in practice
  45. How do I express mutually recursive data structures in safe Rust?
  46. What is the difference between . (dot) and $ (dollar sign)?
  47. Why does Haskell’s “do nothing” function, id, consume tons of memory?
  48. Haskell: why the convention to name a helper function “go”?
  49. What does $ mean/do in Haskell?
  50. functions as applicative functors (Haskell / LYAH)

Leave a Comment