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High-Performance Haskell Johan Tibell johan.tibell@gmail.com 2010-10-01 Welcome! A few things about this tutorial: Stop me and ask questionsearly and often I assume no prior Haskell exposure Sequential performance is still important


  1. High-Performance Haskell Johan Tibell johan.tibell@gmail.com 2010-10-01

  2. Welcome! A few things about this tutorial: ◮ Stop me and ask questions—early and often ◮ I assume no prior Haskell exposure

  3. Sequential performance is still important Parallelism is not a magic bullet: ◮ The speedup of a program using multiple processors is limited by the time needed for the sequential fraction of the program. (Amdahl’s law) ◮ We want to make efficient use of every core.

  4. Caveats The usual caveats about performance optimizations: ◮ Improvements to the compiler might make some optimizations redundant. Write benchmarks to detect these cases. ◮ Some optimizations are compiler (i.e. GHC) specific That being said, many of these optimizations have remained valid over a number of GHC releases.

  5. Software prerequisites The Haskell Platform: ◮ Download installer for Windows, OS X, or Linux here: ◮ http://hackage.haskell.org/platform The Criterion benchmarking library: cabal install -f-Chart criterion

  6. Outline ◮ Introduction to Haskell ◮ Lazy evaluation ◮ Reasoning about space usage ◮ Benchmarking ◮ Making sense of compiler output ◮ Profiling

  7. Haskell in 10 minutes Our first Haskell program sums a list of integers: sum : : [ Int ] − > Int sum [ ] = 0 sum ( x : xs ) = x + sum xs main : : IO () main = print ( sum [ 1 . . 1 0 0 0 0 ] )

  8. Type signatures Definition A type signature describes the type of a Haskell expression: : : [ Int ] − > Int sum ◮ Int is an integer. ◮ [a] is a list of as ◮ So [ Int ] is a list of integers ◮ − > denotes a function. ◮ So sum is a function from a list of integers to an integer.

  9. Defining a function Functions are defined as a series of equations, using pattern matching : sum [ ] = 0 sum ( x : xs ) = x + sum xs The list is defined recursively as either ◮ an empty list, written as [] , or ◮ an element x, followed by a list xs. [] is pronounced “nil” and : is pronounced “cons”.

  10. Function application Function application is indicated by juxtaposition : main = print ( sum [ 1 . . 1 0 0 0 0 ] ) ◮ [1..10000] creates a list of 10,000 integers from 1 to 10,000. ◮ We apply the sum function to the list and then apply the result to the print function. We say that we apply rather then call a function: ◮ Haskell is a lazy language ◮ The result may not be computed immediately

  11. Compiling and running our program Save the program in a file called Sum.hs and then compile it using ghc: $ ghc -O --make Sum.hs [1 of 1] Compiling Main ( Sum.hs, Sum.o ) Linking Sum ... Now lets run the program $ ./Sum 50005000

  12. Defining our own data types Data types have one or more constructors , each with zero or more arguments (or fields ). data Shape = C i r c l e Double | Rectangle Double Double And a function over our data type, again defined using pattern matching: area : : Shape − > Double area ( C i r c l e r ) = r ∗ r ∗ 3.14 area ( Rectangle w h) = w ∗ h Constructing a value uses the same syntax as pattern matching: area ( Rectangle 3.0 5.0)

  13. Back to our sum function Our sum has a problem. If we increase the size of the input main = print ( sum [ 1 . . 1 0 0 0 0 0 0 0 ] ) and run the program again $ ghc -O --make Sum.hs [1 of 1] Compiling Main ( Sum.hs, Sum.o ) Linking Sum ... $ ./Sum Stack space overflow: current size 8388608 bytes. Use ‘+RTS -Ksize -RTS’ to increase it.

  14. Tail recursion Our function creates a stack frame for each recursive call, eventually reaching the predefined stack limit. ◮ Must do so as we still need to apply + to the result of the call. Make sure that the recursive application is the last thing in the function sum : : [ Int ] − > Int sum xs = sum ’ 0 xs where sum ’ acc [ ] = acc sum ’ acc ( x : xs ) = sum ’ ( acc + x ) xs

  15. Polymorphic functions Many functions follow the same pattern. For example, : : [ Int ] − > Int product product xs = product ’ 1 xs where product ’ acc [ ] = acc product ’ acc ( x : xs ) = product ’ ( acc ∗ x ) xs is just like sum except we replace 0 with 1 and + with *. We can generalize sum and product to f o l d l : : ( a − > b − > a ) − > a − > [ b ] − > a f o l d l f z [ ] = z f z ( x : xs ) = f o l d l f ( f z x ) xs f o l d l sum = f o l d l (+) 0 product = f o l d l ( ∗ ) 1

  16. Summing some numbers... Using our new definition of sum , lets sum all number from 1 to 1000000: $ ghc -O --make Sum.hs [1 of 1] Compiling Main ( Sum.hs, Sum.o ) Linking Sum ... $ ./Sum Stack space overflow: current size 8388608 bytes. Use ‘+RTS -Ksize -RTS’ to increase it. What went wrong this time?

  17. Laziness ◮ Haskell is a lazy language ◮ Functions and data constructors don’t evaluate their arguments until they need them cond : : Bool − > a − > a − > a cond True t e = t cond False t e = e ◮ Same with local definitions abs : : Int − > Int abs x | x > 0 = x | otherwise = neg x where neg x = negate x

  18. Why laziness is important ◮ Laziness supports modular programming ◮ Programmer-written functions instead of built-in language constructs ( | | ) : : Bool − > Bool − > Bool True | | = True False | | x = x

  19. Laziness and modularity Laziness lets us separate producers and consumers and still get efficient execution: ◮ Generate all solutions (a huge tree structure) ◮ Find the solution(s) you want nextMove : : Board − > Move nextMove b = selectMove allMoves where allMoves = allMovesFrom b The solutions are generated as they are consumed.

  20. Back to our misbehaving function How does evaluation of this expression proceed? sum [ 1 , 2 , 3 ] Like this: sum [1,2,3] ==> foldl (+) 0 [1,2,3] ==> foldl (+) (0+1) [2,3] ==> foldl (+) ((0+1)+2) [3] ==> foldl (+) (((0+1)+2)+3) [] ==> ((0+1)+2)+3 ==> (1+2)+3 ==> 3+3 ==> 6

  21. Thunks A thunk represents an unevaluated expression. ◮ GHC needs to store all the unevaluated + expressions on the heap, until their value is needed. ◮ Storing and evaluating thunks is costly, and unnecessary if the expression was going to be evaluated anyway. ◮ foldl allocates n thunks, one for each addition, causing a stack overflow when GHC tries to evaluate the chain of thunks.

  22. Controlling evaluation order The seq function allows to control evaluation order. seq : : a − > b − > b Informally, when evaluated, the expression seq a b evaluates a and then returns b.

  23. Weak head normal form Evaluation stops as soon as a data constructor (or lambda) is reached: ghci> seq (1 ‘div‘ 0) 2 *** Exception: divide by zero ghci> seq ((1 ‘div‘ 0), 3) 2 2 We say that seq evaluates to weak head normal form (WHNF).

  24. Weak head normal form Forcing the evaluation of an expression using seq only makes sense if the result of that expression is used later: x = 1 + 2 in seq x ( f x ) l e t The expression ( seq (1 + 2) 3) print doesn’t make sense as the result of 1+2 is never used.

  25. Exercise Rewrite the expression (1 + 2 , ’a ’ ) so that the component of the pair is evaluated before the pair is created.

  26. Solution Rewrite the expression as l e t x = 1 + 2 in seq x ( x , ’a ’ )

  27. A strict left fold We want to evaluate the expression f z x before evaluating the recursive call: foldl ’ : : ( a − > b − > a ) − > a − > [ b ] − > a foldl ’ f z [ ] = z foldl ’ f z ( x : xs ) = l e t z ’ = f z x in seq z ’ ( foldl ’ f z ’ xs )

  28. Summing numbers, attempt 2 How does evaluation of this expression proceed? foldl’ (+) 0 [1,2,3] Like this: foldl’ (+) 0 [1,2,3] ==> foldl’ (+) 1 [2,3] ==> foldl’ (+) 3 [3] ==> foldl’ (+) 6 [] ==> 6 Sanity check: ghci> print (foldl’ (+) 0 [1..1000000]) 500000500000

  29. Computing the mean A function that computes the mean of a list of numbers: mean : : [ Double ] − > Double mean xs = s / fromIntegral l where ( s , l ) = foldl ’ step (0 , 0) xs step ( s , l ) a = ( s+a , l +1) We compute the length of the list and the sum of the numbers in one pass. $ ./Mean Stack space overflow: current size 8388608 bytes. Use ‘+RTS -Ksize -RTS’ to increase it. Didn’t we just fix that problem?!?

  30. seq and data constructors Remember: ◮ Data constructors don’t evaluate their arguments when created ◮ seq only evaluates to the outmost data constructor, but doesn’t evaluate its arguments Problem: foldl ’ forces the evaluation of the pair constructor, but not its arguments, causing unevaluated thunks build up inside the pair: (0.0 + 1.0 + 2.0 + 3.0, 0 + 1 + 1 + 1)

  31. Forcing evaluation of constructor arguments We can force GHC to evaluate the constructor arguments before the constructor is created: mean : : [ Double ] − > Double mean xs = s / fromIntegral l where ( s , l ) = foldl ’ step (0 , 0) xs step ( s , l ) a = l e t s ’ = s + a l ’ = l + 1 in seq s ’ ( seq l ’ ( s ’ , l ’ ) )

  32. Bang patterns A bang patterns is a concise way to express that an argument should be evaluated. {− # LANGUAGE BangPatterns # −} mean : : [ Double ] − > Double mean xs = s / fromIntegral l where ( s , l ) = foldl ’ step (0 , 0) xs step ( ! s , ! l ) a = ( s + a , l + 1) s and l are evaluated before the right-hand side of step is evaluated.

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