Simplified the WorkloadLoader implementation

opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/ComputeWorkloadLoader.kt

@@ -48,11 +48,11 @@ import kotlin.math.roundToLong
  * @param baseDir The directory containing the traces.
  */
 public class ComputeWorkloadLoader(
-    private val baseDir: File,
+    private val pathToFile: File,
     private val checkpointInterval: Long,
     private val checkpointDuration: Long,
     private val checkpointIntervalScaling: Double,
-) {
+) : WorkloadLoader() {
     /**
      * The logger for this instance.
      */
@@ -61,7 +61,7 @@ public class ComputeWorkloadLoader(
     /**
      * The cache of workloads.
      */
-    private val cache = ConcurrentHashMap<String, SoftReference<List<Task>>>()
+    private val cache = ConcurrentHashMap<File, SoftReference<List<Task>>>()
 
     /**
      * Read the fragments into memory.
@@ -157,21 +157,18 @@ public class ComputeWorkloadLoader(
     }
 
     /**
-     * Load the trace with the specified [name] and [format].
+     * Load the trace at the specified [pathToFile].
      */
-    public fun get(
-        name: String,
-        format: String,
-    ): List<Task> {
+    override fun load(): List<Task> {
         val ref =
-            cache.compute(name) { key, oldVal ->
+            cache.compute(pathToFile) { key, oldVal ->
                 val inst = oldVal?.get()
                 if (inst == null) {
-                    val path = baseDir.resolve(key)
+//                    val path = baseDir.resolve(key)
 
-                    logger.info { "Loading trace $key at $path" }
+                    logger.info { "Loading trace $key at $pathToFile" }
 
-                    val trace = Trace.open(path, format)
+                    val trace = Trace.open(pathToFile, "opendc-vm")
                     val fragments = parseFragments(trace)
                     val vms = parseMeta(trace, fragments)
 

opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/internal/LoadSampledComputeWorkload.kt → opendc-compute/opendc-compute-workload/src/main/kotlin/org/opendc/compute/workload/WorkloadLoader.kt

@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2021 AtLarge Research
+ * Copyright (c) 2025 AtLarge Research
  *
  * Permission is hereby granted, free of charge, to any person obtaining a copy
  * of this software and associated documentation files (the "Software"), to deal
@@ -20,28 +20,19 @@
  * SOFTWARE.
  */
 
-package org.opendc.compute.workload.internal
-
+package org.opendc.compute.workload
 import mu.KotlinLogging
-import org.opendc.compute.workload.ComputeWorkload
-import org.opendc.compute.workload.ComputeWorkloadLoader
-import org.opendc.compute.workload.Task
-import java.util.random.RandomGenerator
 
-/**
- * A [ComputeWorkload] that is sampled based on total load.
- */
-internal class LoadSampledComputeWorkload(val source: ComputeWorkload, val fraction: Double) : ComputeWorkload {
-    /**
-     * The logging instance of this class.
-     */
+public abstract class WorkloadLoader {
     private val logger = KotlinLogging.logger {}
 
-    override fun resolve(
-        loader: ComputeWorkloadLoader,
-        random: RandomGenerator,
-    ): List<Task> {
-        val vms = source.resolve(loader, random) // fixme: Should be shuffled, otherwise the first fraction is always chosen
+    public abstract fun load(): List<Task>
+
+    /**
+     * Load the workload at sample tasks until a fraction of the workload is loaded
+     */
+    public fun sampleByLoad(fraction: Double): List<Task> {
+        val vms = this.load()
         val res = mutableListOf<Task>()
 
         val totalLoad = vms.sumOf { it.totalLoad }