gpuCost computation error

[ElieLiabeuf]

Describe the bug
gpuCost in /costDataModel is not computed correctly.

To Reproduce
I'm using g5.2xlarge instance on AWS with nvidia GPU operator v23.9.1.
Hourly instance cost is 1.3529600000

Specs:

{
   "memory":"32 GiB",
   "vcpu":"8",
   "gpu":"1"
}

Node has the following status.capacity:

apiVersion: v1
kind: Node
status:
  capacity:
    cpu: '8'
    memory: 32500272Ki
    nvidia.com/gpu: '1'

and the following labels:

apiVersion: v1
kind: Node
metadata:
  labels:
    beta.kubernetes.io/arch: amd64
    beta.kubernetes.io/instance-type: g5.2xlarge
    beta.kubernetes.io/os: linux
    feature.node.kubernetes.io/cpu-cpuid.ADX: 'true'
    feature.node.kubernetes.io/cpu-cpuid.AESNI: 'true'
    feature.node.kubernetes.io/cpu-cpuid.AVX: 'true'
    feature.node.kubernetes.io/cpu-cpuid.AVX2: 'true'
    feature.node.kubernetes.io/cpu-cpuid.CLZERO: 'true'
    feature.node.kubernetes.io/cpu-cpuid.CMPXCHG8: 'true'
    feature.node.kubernetes.io/cpu-cpuid.FMA3: 'true'
    feature.node.kubernetes.io/cpu-cpuid.FP256: 'true'
    feature.node.kubernetes.io/cpu-cpuid.FXSR: 'true'
    feature.node.kubernetes.io/cpu-cpuid.FXSROPT: 'true'
    feature.node.kubernetes.io/cpu-cpuid.HYPERVISOR: 'true'
    feature.node.kubernetes.io/cpu-cpuid.IBPB: 'true'
    feature.node.kubernetes.io/cpu-cpuid.IBRS: 'true'
    feature.node.kubernetes.io/cpu-cpuid.IBRS_PREFERRED: 'true'
    feature.node.kubernetes.io/cpu-cpuid.IBRS_PROVIDES_SMP: 'true'
    feature.node.kubernetes.io/cpu-cpuid.LAHF: 'true'
    feature.node.kubernetes.io/cpu-cpuid.MCOMMIT: 'true'
    feature.node.kubernetes.io/cpu-cpuid.MOVBE: 'true'
    feature.node.kubernetes.io/cpu-cpuid.MOVU: 'true'
    feature.node.kubernetes.io/cpu-cpuid.OSXSAVE: 'true'
    feature.node.kubernetes.io/cpu-cpuid.RDPRU: 'true'
    feature.node.kubernetes.io/cpu-cpuid.SHA: 'true'
    feature.node.kubernetes.io/cpu-cpuid.SPEC_CTRL_SSBD: 'true'
    feature.node.kubernetes.io/cpu-cpuid.SSE4A: 'true'
    feature.node.kubernetes.io/cpu-cpuid.STIBP: 'true'
    feature.node.kubernetes.io/cpu-cpuid.SYSCALL: 'true'
    feature.node.kubernetes.io/cpu-cpuid.SYSEE: 'true'
    feature.node.kubernetes.io/cpu-cpuid.TOPEXT: 'true'
    feature.node.kubernetes.io/cpu-cpuid.WBNOINVD: 'true'
    feature.node.kubernetes.io/cpu-cpuid.X87: 'true'
    feature.node.kubernetes.io/cpu-cpuid.XGETBV1: 'true'
    feature.node.kubernetes.io/cpu-cpuid.XSAVE: 'true'
    feature.node.kubernetes.io/cpu-cpuid.XSAVEC: 'true'
    feature.node.kubernetes.io/cpu-cpuid.XSAVEOPT: 'true'
    feature.node.kubernetes.io/cpu-hardware_multithreading: 'true'
    feature.node.kubernetes.io/cpu-model.family: '23'
    feature.node.kubernetes.io/cpu-model.id: '49'
    feature.node.kubernetes.io/cpu-model.vendor_id: AMD
    feature.node.kubernetes.io/kernel-config.NO_HZ: 'true'
    feature.node.kubernetes.io/kernel-config.NO_HZ_IDLE: 'true'
    feature.node.kubernetes.io/kernel-version.full: 5.15.0-1045-aws
    feature.node.kubernetes.io/kernel-version.major: '5'
    feature.node.kubernetes.io/kernel-version.minor: '15'
    feature.node.kubernetes.io/kernel-version.revision: '0'
    feature.node.kubernetes.io/pci-10de.present: 'true'
    feature.node.kubernetes.io/pci-1d0f.present: 'true'
    feature.node.kubernetes.io/storage-nonrotationaldisk: 'true'
    feature.node.kubernetes.io/system-os_release.ID: ubuntu
    feature.node.kubernetes.io/system-os_release.VERSION_ID: '20.04'
    feature.node.kubernetes.io/system-os_release.VERSION_ID.major: '20'
    feature.node.kubernetes.io/system-os_release.VERSION_ID.minor: '04'
    gpu-g5-2xlarge: 'true'
    k8s.amazonaws.com/accelerator: nvidia-a10g
    kubernetes.io/arch: amd64
    kubernetes.io/os: linux
    node.kubernetes.io/instance-type: g5.2xlarge
    nvidia.com/cuda.driver.major: '535'
    nvidia.com/cuda.driver.minor: '129'
    nvidia.com/cuda.driver.rev: '03'
    nvidia.com/cuda.runtime.major: '12'
    nvidia.com/cuda.runtime.minor: '2'
    nvidia.com/gfd.timestamp: '1709634570'
    nvidia.com/gpu.compute.major: '8'
    nvidia.com/gpu.compute.minor: '6'
    nvidia.com/gpu.count: '1'
    nvidia.com/gpu.deploy.container-toolkit: 'true'
    nvidia.com/gpu.deploy.dcgm: 'true'
    nvidia.com/gpu.deploy.dcgm-exporter: 'true'
    nvidia.com/gpu.deploy.device-plugin: 'true'
    nvidia.com/gpu.deploy.driver: 'true'
    nvidia.com/gpu.deploy.gpu-feature-discovery: 'true'
    nvidia.com/gpu.deploy.node-status-exporter: 'true'
    nvidia.com/gpu.deploy.nvsm: ''
    nvidia.com/gpu.deploy.operator-validator: 'true'
    nvidia.com/gpu.family: ampere
    nvidia.com/gpu.machine: g5.2xlarge
    nvidia.com/gpu.memory: '23028'
    nvidia.com/gpu.present: 'true'
    nvidia.com/gpu.product: NVIDIA-A10G
    nvidia.com/gpu.replicas: '1'
    nvidia.com/mig.capable: 'false'
    nvidia.com/mig.strategy: single

The default.json (cost model ratio) are the following:

{
   "CPU":"0.031611",
   "RAM":"0.004237",
   "GPU":"0.95"
}

/costDataModel is giving:

{
   "hourlyCost":"1.3529600000",
   "CPU":"8",
   "CPUHourlyCost":"0.111315",
   "RAM":"32 GiB",
   "RAMBytes":"33280282624.000000",
   "RAMGBHourlyCost":"0.014920",
   "storage":"1 x 450 GB NVMe SSD",
   "storageHourlyCost":"",
   "usesDefaultPrice":false,
   "baseCPUPrice":"0.031611",
   "baseRAMPrice":"0.004237",
   "baseGPUPrice":"0.95",
   "usageType":"ondemand",
   "gpu":"1",
   "gpuName":"",
   "gpuCost":"3.345316",
   "vgpu":"1",
   "instanceType":"g5.2xlarge",
   "region":"eu-west-1",
   "providerID":"aws:///eu-west-1a/i-xxxxxx",
   "archType":"amd64"
}

Expected behavior
gpuCost is 3.345316 (greater than the instance cost) instead of 0.96028296.

Potential solution
GPU cost is computed in this part: https://github.com/opencost/opencost/blob/v1.109.0/pkg/costmodel/costmodel.go#L1172
According to the cost I get it acts as gpuc is 0.
It seems that given the node labels, we enter in this case: https://github.com/opencost/opencost/blob/v1.109.0/pkg/costmodel/costmodel.go#L1087 and gpuc is never set.
Adding gpuc = float64(q.Value()) at https://github.com/opencost/opencost/blob/v1.109.0/pkg/costmodel/costmodel.go#L1098 does solve the problem.

Which version of OpenCost are you using?
v1.109.0

Additional context
Add any other context about the problem here. Kubernetes versions and which public clouds you are working with are especially important.

[AjayTripathy]

Thanks for the find! If you could send a PR with that suggested change I'm happy to get it reviewed ASAP.