1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
|
package scala.collection.parallel.benchmarks.parallel_array
import scala.collection.parallel.benchmarks._
import scala.collection.parallel.mutable.ParArray
object ScanMedium extends Companion {
def benchName = "scan-medium";
def apply(sz: Int, parallelism: Int, what: String) = new ScanMedium(sz, parallelism, what)
override def comparisons = List("jsr")
override def defaultSize = 5000
val op = (a: Cont, b: Cont) => {
operation(a, b)
}
def operation(a: Cont, b: Cont) = {
val m = if (a.in < 0) 1 else 0
val k = calc(a.in, b.in, m)
new Cont(a.in + b.in + k * m * (0 until 2).reduceLeft(_ + _))
}
private def calc(x: Int, y: Int, n: Int) = {
var sum = x
for (i <- 0 until 500) {
sum += y + (if (sum % 2 == 0) n * x else y)
if (sum % 5 == 0) sum -= x * y - n * (x + y)
}
sum
}
}
class ScanMedium(sz: Int, p: Int, what: String)
extends Resettable[Cont](sz, p, what, new Cont(_), new Array[Any](_), classOf[Cont]) {
def companion = ScanMedium
override def repetitionsPerRun = 50
override val runs = 12
def runpar = pa.scan(new Cont(0))(ScanMedium.op)
def runseq = sequentialScan(new Cont(0), ScanMedium.op, sz)
def runjsr = jsrarr.cumulate(new extra166y.Ops.Reducer[Cont] {
def op(a: Cont, b: Cont) = ScanMedium.operation(a, b)
}, new Cont(0))
override def comparisonMap = collection.Map("jsr" -> runjsr _)
}
|