merge: Enable re-use of virtual machine workload helpers

This pull request enables re-use of virtual machine workload helpers by extracting the helpers into a 
separate module which may be used by other experiments.

- Support workload/machine CPU count mismatch
- Extract common code out of Capelin experiments
- Support flexible topology creation
- Add option for optimizing SimHost simulation
- Support creating CPU-optimized topology
- Make workload sampling model extensible
- Add support for extended Bitbrains trace format 
- Add support for Azure VM trace format
- Add support for internal OpenDC VM trace format
- Optimize OpenDC VM trace format
- Add tool for converting workload traces
- Remove dependency on SnakeYaml 

**Breaking API Changes**

-   `RESOURCE_NCPU` and `RESOURCE_STATE_NCPU` are renamed to `RESOURCE_CPU_COUNT` and `RESOURCE_STATE_CPU_COUNT` respectively.

2 files changed, 23 insertions, 3 deletions

diff --git a/opendc-compute/opendc-compute-simulator/src/main/kotlin/org/opendc/compute/simulator/SimHost.kt b/opendc-compute/opendc-compute-simulator/src/main/kotlin/org/opendc/compute/simulator/SimHost.kt
index 793db907..ff55c585 100644
--- a/opendc-compute/opendc-compute-simulator/src/main/kotlin/org/opendc/compute/simulator/SimHost.kt
+++ b/opendc-compute/opendc-compute-simulator/src/main/kotlin/org/opendc/compute/simulator/SimHost.kt
@@ -68,7 +68,8 @@ public class SimHost(
     scalingGovernor: ScalingGovernor = PerformanceScalingGovernor(),
     powerDriver: PowerDriver = SimplePowerDriver(ConstantPowerModel(0.0)),
     private val mapper: SimWorkloadMapper = SimMetaWorkloadMapper(),
-    interferenceDomain: VmInterferenceDomain? = null
+    interferenceDomain: VmInterferenceDomain? = null,
+    private val optimize: Boolean = false
 ) : Host, AutoCloseable {
     /**
      * The [CoroutineScope] of the host bounded by the lifecycle of the host.
@@ -98,7 +99,7 @@ public class SimHost(
     /**
      * The machine to run on.
      */
-    public val machine: SimBareMetalMachine = SimBareMetalMachine(interpreter, model, powerDriver)
+    public val machine: SimBareMetalMachine = SimBareMetalMachine(interpreter, model.optimize(), powerDriver)
 
     /**
      * The hypervisor to run multiple workloads.
@@ -319,6 +320,25 @@ public class SimHost(
         val processingUnits = (0 until cpuCount).map { originalCpu.copy(id = it, node = processingNode) }
         val memoryUnits = listOf(MemoryUnit("Generic", "Generic", 3200.0, memorySize))
 
+        return MachineModel(processingUnits, memoryUnits).optimize()
+    }
+
+    /**
+     * Optimize the [MachineModel] for simulation.
+     */
+    private fun MachineModel.optimize(): MachineModel {
+        if (!optimize) {
+            return this
+        }
+
+        val originalCpu = cpus[0]
+        val freq = cpus.sumOf { it.frequency }
+        val processingNode = originalCpu.node.copy(coreCount = 1)
+        val processingUnits = listOf(originalCpu.copy(frequency = freq, node = processingNode))
+
+        val memorySize = memory.sumOf { it.size }
+        val memoryUnits = listOf(MemoryUnit("Generic", "Generic", 3200.0, memorySize))
+
         return MachineModel(processingUnits, memoryUnits)
     }
 
diff --git a/opendc-compute/opendc-compute-simulator/src/main/kotlin/org/opendc/compute/simulator/failure/StochasticVictimSelector.kt b/opendc-compute/opendc-compute-simulator/src/main/kotlin/org/opendc/compute/simulator/failure/StochasticVictimSelector.kt
index 87903623..fcd9dd7e 100644
--- a/opendc-compute/opendc-compute-simulator/src/main/kotlin/org/opendc/compute/simulator/failure/StochasticVictimSelector.kt
+++ b/opendc-compute/opendc-compute-simulator/src/main/kotlin/org/opendc/compute/simulator/failure/StochasticVictimSelector.kt
@@ -24,8 +24,8 @@ package org.opendc.compute.simulator.failure
 
 import org.apache.commons.math3.distribution.RealDistribution
 import org.opendc.compute.simulator.SimHost
+import java.util.*
 import kotlin.math.roundToInt
-import kotlin.random.Random
 
 /**
  * A [VictimSelector] that stochastically selects a set of hosts to be failed.