Those benchmarks are flawed and you're not testing what you think you are. The first benchmark is the slowest of all because it's: - realizing the nums lazy sequence - realizing the vpairs lazy sequence - destructuring a vector - creating and realizing a lazy sequene of record types - only then benchmarking the reduce operation.
In the second benchmark you're still benchmarking the destructuring of vector pairs and the creation and realization of a lazy sequence of types The third benchmark is like the second in that you're creating and realizing a lazy sequence but it's slightly faster than the second one because you're not including destructuring in the mix The last benchmark is the fastest of all because you're just iterating over an already realized sequence. In no benchmark you're actually using any primitive types, you're always using boxed Doubles > On 12 May 2016, at 20:58, JvJ <kfjwhee...@gmail.com> wrote: > > I've been doing some performance tests on various floating point operations. > In particular, I wanted to check what would be the fastest way to implement a > 2-d floating point vector in clojure. > > Here's my tests: > > ;;; V+ Tests > ;;; Implementing floating-point vectors as: > ;;; structs, deftype, vector > (defrecord v2r > [^Double x ^Double y]) > > (defn rv+ > [^v2r v1 ^v2r v2] > (v2r. (+ (.x v1) (.x v2)) > (+ (.y v1) (.y v2)))) > > (deftype v2t > [^Double x ^Double y]) > > (defn tv+ > [^v2t v1 ^v2t v2] > (v2t. (+ (.x v1) (.x v2)) > (+ (.y v1) (.y v2)))) > > (defn vv+ > [v1 v2] > (mapv + v1 v2)) > > > (defn testvecs > "Tests the vector add operations by reducing a > random list by each of the v+ operations on > identical sets of random vectors" > [n] > (let [nums (repeatedly (* 2 n) rand) > vpairs (partition 2 nums) > v2r-list (apply list (map (fn [[x y]] (v2r. x y)) vpairs)) > v2t-list (apply list (map (fn [[x y]] (v2t. x y)) vpairs)) > v2v-list (apply list (map vec vpairs))] > (println "V2 Record:") > (bench (reduce rv+ v2r-list)) > (println "V2 Type:") > (bench (reduce tv+ v2t-list)) > (println "V2 Vector:") > (bench (reduce vv+ v2v-list)) > (println "Just Doubles:") > (bench (reduce + nums)))) > > > Here's my output: > > V2 Record: > Evaluation count : 420 in 60 samples of 7 calls. > Execution time mean : 164.379725 ms > Execution time std-deviation : 4.478128 ms > Execution time lower quantile : 149.546749 ms ( 2.5%) > Execution time upper quantile : 172.317132 ms (97.5%) > Overhead used : 1.873322 ns > > Found 8 outliers in 60 samples (13.3333 %) > low-severe 4 (6.6667 %) > low-mild 3 (5.0000 %) > high-mild 1 (1.6667 %) > Variance from outliers : 14.2105 % Variance is moderately inflated by > outliers > V2 Type: > Evaluation count : 1860 in 60 samples of 31 calls. > Execution time mean : 32.238857 ms > Execution time std-deviation : 2.331682 ms > Execution time lower quantile : 26.769206 ms ( 2.5%) > Execution time upper quantile : 35.318368 ms (97.5%) > Overhead used : 1.873322 ns > > Found 8 outliers in 60 samples (13.3333 %) > low-severe 5 (8.3333 %) > low-mild 3 (5.0000 %) > Variance from outliers : 53.4940 % Variance is severely inflated by outliers > V2 Vector: > Evaluation count : 2040 in 60 samples of 34 calls. > Execution time mean : 30.175015 ms > Execution time std-deviation : 3.870306 ms > Execution time lower quantile : 21.877116 ms ( 2.5%) > Execution time upper quantile : 37.668717 ms (97.5%) > Overhead used : 1.873322 ns > > Found 10 outliers in 60 samples (16.6667 %) > low-severe 5 (8.3333 %) > low-mild 2 (3.3333 %) > high-mild 3 (5.0000 %) > Variance from outliers : 78.9869 % Variance is severely inflated by outliers > Just Doubles: > Evaluation count : 20640 in 60 samples of 344 calls. > Execution time mean : 4.309871 ms > Execution time std-deviation : 537.444033 µs > Execution time lower quantile : 2.389294 ms ( 2.5%) > Execution time upper quantile : 4.716009 ms (97.5%) > Overhead used : 1.873322 ns > > Found 8 outliers in 60 samples (13.3333 %) > low-severe 5 (8.3333 %) > low-mild 2 (3.3333 %) > high-mild 1 (1.6667 %) > Variance from outliers : 78.9282 % Variance is severely inflated by outliers > > > The performance is amazingly better when using primitive doubles, even though > all operations are doing effectively the same thing: 20000 floating point add > operations. I assume that the overhead of allocating a new vector2 object is > responsible for the decline in performance. > > Did I use type hints correctly? Is there a way to keep the "x and y" vector > abstraction and still get something approaching primitive performance? > > -- > You received this message because you are subscribed to the Google > Groups "Clojure" group. > To post to this group, send email to clojure@googlegroups.com > Note that posts from new members are moderated - please be patient with your > first post. > To unsubscribe from this group, send email to > clojure+unsubscr...@googlegroups.com > For more options, visit this group at > http://groups.google.com/group/clojure?hl=en > --- > You received this message because you are subscribed to the Google Groups > "Clojure" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to clojure+unsubscr...@googlegroups.com. > For more options, visit https://groups.google.com/d/optout. -- You received this message because you are subscribed to the Google Groups "Clojure" group. To post to this group, send email to clojure@googlegroups.com Note that posts from new members are moderated - please be patient with your first post. To unsubscribe from this group, send email to clojure+unsubscr...@googlegroups.com For more options, visit this group at http://groups.google.com/group/clojure?hl=en --- You received this message because you are subscribed to the Google Groups "Clojure" group. To unsubscribe from this group and stop receiving emails from it, send an email to clojure+unsubscr...@googlegroups.com. For more options, visit https://groups.google.com/d/optout.
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