Scala code slows down as array size increases - scala

Question

I have written a Scala Spark application that is implementation of iterative algorithm. Element wise operation have to be performed in each iteration on arrays. Initially size of all collection was 1000. For 1000 size arrays, code works fine and faster. Now size of arrays is 1 million and this code (part of application) is taking too long time, slowing down whole application. This code is used inside mapPartitionWithIndex of Spark RDD. Here is code.
def ESt(arr: Array[Double], arr1: Array[Double], frq: Double): Array[Double] = {
val newArr = new Array[Double](arr.length)
var i = 0
while (i < arr.length) {
newArr(i) = (arr(i) - arr1(i)) * frq
i += 1
}
newArr
}
def ES(arr: Array[Double], arr1: Array[Double], arr2: Array[Double]): Array[Double] = {
val newArr =new Array[Double](arr.length)
var i = 0
while (i < arr.length) {
newArr(i) = arr(i) + arr1(i) + arr2(i)
i += 1
}
newArr
}
Here is usage of above two functions to create an Array.
val dim = 1000000 // one million
val number : Double = math.random
val xr1 : Array[Double] = Array of size dim
val xr2 : Array[Double] = Array of size dim
val xbest : Array[Double] = Array of size dim
val randomArray : Array[Double] = Array.fill(dim)(math.random)
var result : Array[Double] = ES(randomArray, ESt(xbest, randomArray, number), ESt(xr1, xr2, number))
I have lot of cores in cluster where I executes this code. How can I speed-up this computation using Scala functional or parallel programming power or using any other technique?