Implemented Single GPU Support & outline of host-level allocation policies (#342)

* renamed performance counter to distinguish different resource types

* added GPU, modelled similar to CPU

* added GPUs to machine model

* list of GPUs instead of single instance

* renamed memory speed to bandwidth

* enabled parsing of GPU resources

* split powermodel into cpu and GPU powermodel

* added gpu parsing tests

* added idea of host level scheduling

* added tests for multi gpu parsing

* renamed powermodel to cpupowermodel

* clarified naming of cpu and gpu components

* added resource type to flow suplier and edge

* added resourcetype

* added GPU components and resource type to fragments

* added GPU to workload and updated resource usage retrieval

* implemented first version of multi resource

* added name to workload

* renamed perfomance counters

* removed commented out code

* removed deprecated comments

* included demand and supply into calculations

* resolving rebase mismatches

* moved resource type from flowedge class to common package

* added available resources to machinees

* cleaner separation if workload is started of simmachine or vm

* Replaced exception with dedicated enum

* Only looping over resources that are actually used

* using hashmaps to handle resourcetype instead of arrays for readability

* fixed condition

* tracking finished workloads per resource type

* removed resource type from flowedge

* made supply and demand distribution resource specific

* added power model for GPU

* removed unused test setup

* removed depracated comments

* removed unused parameter

* added ID for GPU

* added GPUs and GPU performance counters (naively)

* implemented capturing of GPU statistics

* added reminders for future implementations

* renamed properties for better identification

* added capturing GPU statistics

* implemented first tests for GPUs

* unified access to performance counters

* added interface for general compute resource handling

* implemented multi resource support in simmachine

* added individual edge to VM per resource

* extended compute resource interface

* implemented multi-resource support in PSU

* implemented generic retrieval of computeresources

* implemented mult-resource suppport in vm

* made method use more resource specific

* implemented simple GPU tests

* rolled back frquency and demand use

* made naming independent of used resource

* using workloads resources instead of VMs to determine available resource

* implemented determination of used resources in workload

* removed logging statements

* implemented reading from workload

* fixed naming for host-level allocation

* fixed next deadline calculation

* fixed forwarding supply

* reduced memory footprint

* made GPU powermodel nullable

* maded Gpu powermodel configurable in topology

* implemented tests for basic gpu scheduler

* added gpu properties

* implemented weights, filter and simple cpu-gpu scheduler

* spotless apply

* spotless apply pt. 2

* fixed capitalization

* spotless kotlin run

* implemented coloumn export

* todo update

* removed code comments

* Merged PerformanceCounter classes into one & removed interface

* removed GPU  specific powermodel

* Rebase master: kept both versions of TopologyFactories

* renamed CpuPowermodel to resource independent Powermodel

Moved it from Cpu package to power package

* implementated default of getResourceType & removed overrides if possible

* split getResourceType into Consumer and Supplier

* added power as resource type

* reduced supply demand from arrayList to single value

* combining GPUs into one large GPU, until full multi-gpu support

* merged distribution policy enum with corresponding factory

* added comment

* post-rebase fixes

* aligned naming

* Added GPU metrics to task output

* Updates power resource type to uppercase.

Standardizes the `ResourceType.Power` enum to `ResourceType.POWER`
for consistency with other resource types and improved readability.

* Removes deprecated test assertions

Removes commented-out assertions in GPU tests.

These assertions are no longer needed and clutter the test code.

* Renames MaxMinFairnessStrategy to Policy

Renames MaxMinFairnessStrategy to MaxMinFairnessPolicy for
clarity and consistency with naming conventions. This change
affects the factory and distributor to use the updated name.

* applies spotless

* nulls GPUs as it is not used

1 files changed, 20 insertions, 21 deletions

diff --git a/opendc-simulator/opendc-simulator-compute/src/test/kotlin/org/opendc/simulator/compute/SimMachineTest.kt b/opendc-simulator/opendc-simulator-compute/src/test/kotlin/org/opendc/simulator/compute/SimMachineTest.kt
index 173c60e7..eb3d3377 100644
--- a/opendc-simulator/opendc-simulator-compute/src/test/kotlin/org/opendc/simulator/compute/SimMachineTest.kt
+++ b/opendc-simulator/opendc-simulator-compute/src/test/kotlin/org/opendc/simulator/compute/SimMachineTest.kt
@@ -22,32 +22,31 @@
 
 package org.opendc.simulator.compute
 
-import org.junit.jupiter.api.BeforeEach
-import org.opendc.simulator.compute.models.CpuModel
 import org.opendc.simulator.compute.models.MachineModel
-import org.opendc.simulator.compute.models.MemoryUnit
 
 /**
  * Test suite for the [SimBareMetalMachine] class.
  */
+
 class SimMachineTest {
     private lateinit var machineModel: MachineModel
-
-    @BeforeEach
-    fun setUp() {
-        machineModel =
-            MachineModel(
-                CpuModel(
-                    0,
-                    2,
-                    1000.0,
-                    "Intel",
-                    "Xeon",
-                    "amd64",
-                ),
-                MemoryUnit("Crucial", "MTA18ASF4G72AZ-3G2B1", 3200.0, 32_000 * 4),
-            )
-    }
+//
+//    @BeforeEach
+//    fun setUp() {
+//        machineModel =
+//            MachineModel(
+//                CpuModel(
+//                    0,
+//                    2,
+//                    1000.0,
+//                    "Intel",
+//                    "Xeon",
+//                    "amd64",
+//                ),
+//                MemoryUnit("Crucial", "MTA18ASF4G72AZ-3G2B1", 3200.0, 32_000 * 4),
+//                null
+//            )
+//    }
 
 //    @Test
 //    fun testFlopsWorkload() =
@@ -104,10 +103,10 @@ class SimMachineTest {
 //            val cpuNode = machineModel.cpu
 //            val machineModel =
 //                MachineModel(
-//                    List(cpuNode.coreCount * 2) {
+//                    List(cpuNode.cpuCoreCount * 2) {
 //                        CpuModel(
 //                            it,
-//                            cpuNode.coreCount,
+//                            cpuNode.cpuCoreCount,
 //                            1000.0,
 //                        )
 //                    },