Scala benchmark: use fullLinkJS output

The JavaScript produced by `fullLinkJS` is about twice as fast as the code produced by `fastLinkJS`.
Scala benchmark: step rotation by multiplying
2024-08-10 21:30:36 -07:00 · 2024-08-10 19:11:55 -07:00
2 changed files with 32 additions and 22 deletions
--- a/lang-trials/scala-benchmark/index.html
+++ b/lang-trials/scala-benchmark/index.html
@ -3,7 +3,7 @@
  <head>
    <meta charset="UTF-8">
    <title>The circular law</title>
-    <script type="text/javascript" src="./target/scala-3.4.2/circular-law-fastopt/main.js"></script>
+    <script type="text/javascript" src="./target/scala-3.4.2/circular-law-opt/main.js"></script>
    <link rel="stylesheet" href="main.css"/>
  </head>
  <body></body>
--- a/lang-trials/scala-benchmark/src/main/scala/CircularLawApp.scala
+++ b/lang-trials/scala-benchmark/src/main/scala/CircularLawApp.scala
@ -2,6 +2,7 @@ import com.raquo.laminar.api.L.{*, given}
 import narr.*
 import org.scalajs.dom
 import org.scalajs.dom.document
+import scala.collection.mutable.ArrayBuffer
 import scala.math.{cos, sin}
 import slash.matrix.Matrix
 import slash.matrix.decomposition.Eigen
@ -38,36 +39,45 @@ object CircularLawApp:
      )
      ctx.fill()
  
-  def eigvalsRotated[N <: Int](A: Matrix[N, N], time: Double)(using ValueOf[N]): (NArray[Double], NArray[Double]) =
-    // create transformation
-    val maxFreq = 4
-    val T = Matrix.identity[N, N]
-    val dim: Int = valueOf[N]
-    for n <- 0 to dim by 2 do
-      val a = cos(math.Pi * time * (n % maxFreq))
-      val b = sin(math.Pi * time * (n % maxFreq))
-      T(n, n) = a
-      T(n+1, n) = b
-      T(n, n+1) = -b
-      T(n+1, n+1) = a
-    
-    // find eigenvalues
-    val eigen = Eigen(T*A)
+  def complexEigenvalues[N <: Int](mat: Matrix[N, N])(using ValueOf[N]): (NArray[Double], NArray[Double]) =
+    val eigen = Eigen(mat)
    (
      eigen.realEigenvalues.asInstanceOf[NArray[Double]],
      eigen.imaginaryEigenvalues.asInstanceOf[NArray[Double]]
    )
  
-  def randEigvalSeries[N <: Int]()(using ValueOf[N]): (List[(NArray[Double], NArray[Double])], String) =
-    val timeRes = 100
-    val dim: Int = valueOf[N]
+  def randEigvalSeries[N <: Int]()(using ValueOf[N]): (ArrayBuffer[(NArray[Double], NArray[Double])], String) =
+    // start timing
    val startTime = System.currentTimeMillis()
-    val A = new Matrix[N, N](
+    
+    // initialize the random matrix step
+    val dim: Int = valueOf[N]
+    var randMat = new Matrix[N, N](
      NArray.tabulate(dim*dim)(k => (math.E*k*k) % 2 - 1)
    ).times(math.sqrt(3d / dim))
-    val series = List.tabulate(timeRes)(t => eigvalsRotated(A, t.toDouble / timeRes))
+    
+    // initialize the rotation step
+    val timeRes = 100
+    val maxFreq = 4
+    val rotStep = Matrix.identity[N, N]
+    for n <- 0 to dim by 2 do
+      val ang = math.Pi * (n % maxFreq) / timeRes
+      val cos_ang = cos(ang)
+      val sin_ang = sin(ang)
+      rotStep(n, n) = cos_ang
+      rotStep(n+1, n) = sin_ang
+      rotStep(n, n+1) = -sin_ang
+      rotStep(n+1, n+1) = cos_ang
+    
+    // find the eigenvalues
+    val eigvalSeries = ArrayBuffer(complexEigenvalues(randMat))
+    for _ <- 1 to timeRes-1 do
+      randMat = rotStep * randMat
+      eigvalSeries += complexEigenvalues(randMat)
+    
+    // finish timing
    val runTime = System.currentTimeMillis() - startTime
-    (series, runTime.toString() + " ms")
+    (eigvalSeries, runTime.toString() + " ms")
  
  def main(args: Array[String]): Unit =
    ctx.fillStyle = "white"
Author	SHA1	Message	Date
Aaron Fenyes	144bfb8faf	Scala benchmark: use `fullLinkJS` output The JavaScript produced by `fullLinkJS` is about twice as fast as the code produced by `fastLinkJS`.	2024-08-10 21:30:36 -07:00
Aaron Fenyes	27ada6566b	Scala benchmark: step rotation by multiplying This makes the algorithm more consistent with the Rust benchmark.	2024-08-10 19:11:55 -07:00