Use common ForkJoinPool for light calculations

src/main/kotlin/ru/dbotthepony/kstarbound/Main.kt

@@ -75,7 +75,7 @@ fun main() {
 		for (chunkX in 0 .. 100) {
 		//for (chunkX in 0 .. 17) {
 		//	for (chunkY in 21 .. 21) {
-			for (chunkY in 0 .. 24) {
+			for (chunkY in 18 .. 24) {
 				val data = db.read(byteArrayOf(1, 0, chunkX.toByte(), 0, chunkY.toByte()))
 				val data2 = db.read(byteArrayOf(2, 0, chunkX.toByte(), 0, chunkY.toByte()))
 

src/main/kotlin/ru/dbotthepony/kstarbound/client/StarboundClient.kt

@@ -88,7 +88,7 @@ class StarboundClient : Closeable {
 	val thread: Thread = Thread.currentThread()
 	// client specific executor which will accept tasks which involve probable
 	// callback to foreground executor to initialize thread-unsafe data
-	// In above case multiple threads will introduce big congestion for resources
+	// In above case too many threads will introduce big congestion for resources, stalling entire workload; wasting cpu resources
 	val backgroundExecutor = ForkJoinPool(Runtime.getRuntime().availableProcessors().coerceAtMost(4))
 	val foregroundExecutor = ManualExecutorService(thread)
 	val capabilities: GLCapabilities

src/main/kotlin/ru/dbotthepony/kstarbound/world/LightCalculator.kt

@@ -8,8 +8,13 @@ import ru.dbotthepony.kvector.arrays.Object2DArray
 import ru.dbotthepony.kvector.util.linearInterpolation
 import ru.dbotthepony.kvector.vector.RGBAColor
 import java.nio.ByteBuffer
+import java.util.concurrent.Callable
+import java.util.concurrent.CompletableFuture
 import java.util.concurrent.ConcurrentLinkedQueue
+import java.util.concurrent.ForkJoinPool
+import java.util.concurrent.Future
 import java.util.concurrent.locks.LockSupport
+import java.util.function.Supplier
 import kotlin.math.roundToInt
 import kotlin.random.Random
 
@@ -380,10 +385,9 @@ class LightCalculator(val parent: ICellAccess, val width: Int, val height: Int)
 		// perform multithreaded calculation only when it makes sense
 		if (multithreaded && pointLights.size > 1) {
 			val thread = Thread.currentThread()
-
 			// calculate k-means clusters of point lights
 			// to effectively utilize CPU cores
-			val clusterCount = threads.size.coerceAtMost(pointLights.size)
+			val clusterCount = ForkJoinPool.commonPool().parallelism.coerceAtMost(pointLights.size)
 			val clusters = ArrayList<TaskCluster>(clusterCount)
 			val startingPoints = IntArraySet()
 			// val rand = Random(System.nanoTime())
@@ -394,7 +398,7 @@ class LightCalculator(val parent: ICellAccess, val width: Int, val height: Int)
 			}
 
 			for (index in startingPoints.intIterator()) {
-				clusters.add(TaskCluster(pointLights[index].x.toDouble(), pointLights[index].y.toDouble(), this, thread))
+				clusters.add(TaskCluster(pointLights[index].x.toDouble(), pointLights[index].y.toDouble(), this))
 			}
 
 			var converged = false
@@ -459,25 +463,14 @@ class LightCalculator(val parent: ICellAccess, val width: Int, val height: Int)
 				}
 			}
 
-			/*for ((i, cluster) in clusters.withIndex()) {
+			val tasks = ArrayList<Future<Grid>>()
-				val (r, g, b) = clusterColors[i]
+			clusters.forEach { tasks.add(CompletableFuture.supplyAsync(it, ForkJoinPool.commonPool()).also { it.thenApply { LockSupport.unpark(thread); it } }) }
 
-				for (light in cluster.lights) {
+			while (tasks.isNotEmpty()) {
-					light.red = r
+				tasks.removeIf {
-					light.green = g
+					if (it.isDone) {
-					light.blue = b
+						val grid = it.get()
-				}
-			}*/
 
-			tasks.addAll(clusters)
-			wakeup()
-
-			while (clusters.isNotEmpty()) {
-				clusters.removeIf {
-					val grid = it.grid
-
-					// wait until thread local caches are refreshed
-					if (grid != null) {
 						if (targetMem != null) {
 							for (x in grid.minX - 1 .. grid.maxX) {
 								for (y in grid.minY - 1 .. grid.maxY) {
@@ -522,10 +515,10 @@ class LightCalculator(val parent: ICellAccess, val width: Int, val height: Int)
 						}
 					}
 
-					grid != null
+					it.isDone
 				}
 
-				LockSupport.parkNanos(500_000)
+				LockSupport.parkNanos(500_000L)
 			}
 		} else {
 			val grid = Grid()
@@ -589,8 +582,7 @@ class LightCalculator(val parent: ICellAccess, val width: Int, val height: Int)
 		var x: Double,
 		var y: Double,
 		val parent: LightCalculator,
-		val parentThread: Thread
+	) : Supplier<Grid> {
-	) {
 		val lights = ArrayList<PointLight>()
 
 		fun updateCenter() {
@@ -608,13 +600,7 @@ class LightCalculator(val parent: ICellAccess, val width: Int, val height: Int)
 			y /= lights.size
 		}
 
-		@Volatile
+		override fun get(): Grid {
-		var grid: Grid? = null
-			private set
-
-		fun execute() {
-			if (grid != null) return
-
 			val grid = parent.Grid()
 
 			for (light in lights) {
@@ -635,46 +621,7 @@ class LightCalculator(val parent: ICellAccess, val width: Int, val height: Int)
 			}
 
 			grid.calculateSpread()
-			this.grid = grid
+			return grid
-			LockSupport.unpark(parentThread)
-		}
-	}
-
-	companion object {
-		private val tasks = ConcurrentLinkedQueue<TaskCluster>()
-		private val threads = ArrayList<Thread>()
-
-		private val clusterColors = ArrayList<RGBAColor>()
-
-		private fun wakeup() {
-			for (thread in threads) {
-				LockSupport.unpark(thread)
-			}
-		}
-
-		private fun thread() {
-			while (true) {
-				val next = tasks.poll()
-
-				if (next == null) {
-					LockSupport.park()
-					continue
-				}
-
-				next.execute()
-			}
-		}
-
-		init {
-			for (i in 0 until Runtime.getRuntime().availableProcessors()) {
-				Thread(::thread, "Starbound Lighting Thread $i").also { threads.add(it); it.isDaemon = true }.start()
-			}
-
-			val rand = Random(System.nanoTime())
-
-			for (i in threads.indices) {
-				clusterColors.add(RGBAColor(rand.nextFloat() * 0.5f + 0.5f, rand.nextFloat() * 0.5f + 0.5f, rand.nextFloat() * 0.5f + 0.5f))
-			}
 		}
 	}
 }