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| author | Niels Thiele <noleu66@posteo.net> | 2025-06-22 12:31:21 +0200 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2025-06-22 12:31:21 +0200 |
| commit | 0203254b709614fa732c114aa25916f61b8b3275 (patch) | |
| tree | 63232140a8e60e16e1668a51eb58954d8609fbdc /opendc-web/opendc-web-runner | |
| parent | 8f846655347195bf6f22a4a102aa06f0ab127da1 (diff) | |
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
Diffstat (limited to 'opendc-web/opendc-web-runner')
| -rw-r--r-- | opendc-web/opendc-web-runner/src/main/kotlin/org/opendc/web/runner/OpenDCRunner.kt | 7 |
1 files changed, 4 insertions, 3 deletions
diff --git a/opendc-web/opendc-web-runner/src/main/kotlin/org/opendc/web/runner/OpenDCRunner.kt b/opendc-web/opendc-web-runner/src/main/kotlin/org/opendc/web/runner/OpenDCRunner.kt index 406c9772..309763f1 100644 --- a/opendc-web/opendc-web-runner/src/main/kotlin/org/opendc/web/runner/OpenDCRunner.kt +++ b/opendc-web/opendc-web-runner/src/main/kotlin/org/opendc/web/runner/OpenDCRunner.kt @@ -36,10 +36,10 @@ import org.opendc.compute.topology.specs.HostSpec import org.opendc.compute.topology.specs.PowerSourceSpec import org.opendc.compute.workload.ComputeWorkloadLoader import org.opendc.experiments.base.runner.replay -import org.opendc.simulator.compute.cpu.CpuPowerModels import org.opendc.simulator.compute.models.CpuModel import org.opendc.simulator.compute.models.MachineModel import org.opendc.simulator.compute.models.MemoryUnit +import org.opendc.simulator.compute.power.PowerModels import org.opendc.simulator.kotlin.runSimulation import org.opendc.web.proto.runner.Job import org.opendc.web.proto.runner.Scenario @@ -353,14 +353,15 @@ public class OpenDCRunner( } val energyConsumptionW = machine.cpus.sumOf { it.energyConsumptionW } - val powerModel = CpuPowerModels.linear(2 * energyConsumptionW, energyConsumptionW * 0.5) + val cpuPowerModel = PowerModels.linear(2 * energyConsumptionW, energyConsumptionW * 0.5) val spec = HostSpec( "node-$clusterId-$position", clusterId, MachineModel(processors, memoryUnits[0]), - powerModel, + cpuPowerModel, + null, ) res += spec |
