Tree.hs {-Implementation of BST (binary search tree) Script is absolutly free/libre, but with no guarantee. Count the number of leaves in the tree: foldTree (\_ xs -> if null xs then 1 else sum xs) (Node 1 [Node 2 [], Node 3 []]) == 2. Author: Ondrej Profant -} import qualified Data.List {-DEF data structure -} data (Ord a, Eq a) => Tree a = Nil | Node (Tree a) a (Tree a) dramatically reducing running times. {-# OPTIONS -fbang-patterns -funbox-strict-fields #-}, -- allocate, walk, and deallocate many bottom-up binary trees, -- confirm the the long-lived binary tree still exists, -- traverse the tree, counting up the nodes, -- Modified by Stephen Blackheath to parallelize (a very tiny tweak), -- normally you would ensure the branches are lazy, but this benchmark, {-# OPTIONS_GHC -fglasgow-exts -O2 -optc-O3 -funbox-strict-fields #-}, https://wiki.haskell.org/index.php?title=Shootout/Binary_trees&oldid=38856. When compiled with the -threaded flag, and run with +RTS -N5 -RTS, it will exploit all cores on the quad-core machine, -- more times the maximum residency)", as per GHC User's Guide: -- , -- -H "provides a “suggested heap size” for the garbage collector. To find the depth of the binary tree we will recursively calculate the depth of the left and right child of a node. t = t sumT i d t = sumT (i-1) d (t + a + b) where a = check (make i d) b = check (make (-i) d) make:: Int-> Int-> Tree make! head let maxN = max (minN + 2) n stretchN = maxN + 1-- stretch memory tree let c = check (make 0 stretchN) io "stretch tree" stretchN c-- allocate a long lived tree let! traverseDF :: Tree a -> [a] This is a version of the Haskell GHC binary-trees benchmark, annotated for parallelism, using parallel strategy combinators. This page was last modified on 18 April 2020, at 23:27. For instance: Lets build a binary tree in Haskell. Shortest entry in any language, and almost twice as fast as old entry on my box. The depth of binary tree is the depth of the deepest node (leaf node). The Depth First traversal in Haskell is very easy. and "set your -H value high (3 or. public class TreeNode { int val; TreeNode left; TreeNode right; } The maximum depth of a tree is the number of nodes is longest path from the root node down to the leaf node. -- This implementation uses a parallel strategy to exploit the quad core machine. i! Int depth:: Int-> Int-> [P] depth! This page was last modified on 22 February 2011, at 22:33. 0 = Node i Nil Nil make i d = Node i (make (i2-1) d2) (make i2 d2) where i2 = 2 * i d2 = d-1 check:: Tree-> Int check Nil … Implementation of binary search tree in Haskell Raw. Binary trees have internal structure; for any given node, all elements to theleft are less than the current value, and all elements to the right are greaterthan the current value. d! -- For more information about Haskell parallel strategies, see, -- http://www.macs.hw.ac.uk/~dsg/gph/papers/html/Strategies/strategies.html, https://benchmarksgame-team.pages.debian.net/benchmarksgame/description/binarytrees.html#binarytrees, https://benchmarksgame-team.pages.debian.net/benchmarksgame/measurements/ghc.html, http://alioth.debian.org/tracker/index.php?func=detail&aid=311523&group_id=30402&atid=411646, http://hackage.haskell.org/trac/ghc/ticket/3061, https://wiki.haskell.org/index.php?title=Benchmarks_Game/Parallel/BinaryTrees&oldid=63285. If you look at the pseudo code, we can almost directly translate that to Haskell. the number of branches from the … Find depth of the tree; i.e. The tree is represented by multiple TreeNodes connected to each other. Description of the benchmark: https://benchmarksgame-team.pages.debian.net/benchmarksgame/description/binarytrees.html#binarytrees, Haskell entries: https://benchmarksgame-team.pages.debian.net/benchmarksgame/measurements/ghc.html, Submitted: http://alioth.debian.org/tracker/index.php?func=detail&aid=311523&group_id=30402&atid=411646, Also filed a bug ticket with GHC to find out if the GC growth strategy can be improved (so that -H240M isn't required): http://hackage.haskell.org/trac/ghc/ticket/3061. The -N5 flag asks the Haskell runtime to use 5 capabilites, which map onto the underlying cores. This is a trivial modification of Don Stewart's to add parallelism. Which is a satisfying result, as the parallelisation strategy is super simple. -- Modified by Stephen Blackheath to parallelize (a very tiny tweak), -- Where '4' is the number of cores. 0! m | d > m = [] | otherwise = P (2 * n) d (sumT n d 0): depth (d + 2) m where n = 1 ` shiftL ` (m-d + minDepth) sumT:: Int-> Int-> Int-> Int sumT! The, -- garbage collector will use about this much memory until the program, -- residency grows and the heap size needs to be expanded to retain, -- normally you would ensure the branches are lazy, but this benchmark, -- allocate, walk, and deallocate many bottom-up binary trees, -- confirm the the long-lived binary tree still exists, -- traverse the tree, counting up the nodes, {-# OPTIONS -fbang-patterns -funbox-strict-fields #-}, -- Contributed by Don Stewart and Thomas Davie. Find the maximum value in the tree: foldTree (\x xs -> maximum (x:xs)) (Node 1 [Node 2 [], Node 3 []]) == 3. After finding the depth of both left and right child we will store the depth of the child which has maximum value and add 1 to it to include the current level of tree. Tree minN = 4 io s n t = printf "%s of depth %d \t check: %d \n " s n t main = do n <-getArgs >>= readIO. d! In the problem, we are given a binary tree and we want to to find its maximum depth.

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