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Tuned npb is workload resources
Lowering the amount of cpu allocated to this workload will set the resources allocated to be similar to the other npb and tf workload in this tests. This will also allow to run all three workloads in a n1-standard-12 gcp instance - which has 16 cpus and 60 GB. Signed-off-by: alejandrox1 <alarcj137@gmail.com>
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@ -44,11 +44,11 @@ func (w npbISWorkload) PodSpec() v1.PodSpec {
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Image: "gcr.io/kubernetes-e2e-test-images/node-perf/npb-is:1.0",
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Resources: v1.ResourceRequirements{
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Requests: v1.ResourceList{
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v1.ResourceName(v1.ResourceCPU): resource.MustParse("16000m"),
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v1.ResourceName(v1.ResourceCPU): resource.MustParse("15000m"),
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v1.ResourceName(v1.ResourceMemory): resource.MustParse("48Gi"),
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},
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Limits: v1.ResourceList{
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v1.ResourceName(v1.ResourceCPU): resource.MustParse("16000m"),
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v1.ResourceName(v1.ResourceCPU): resource.MustParse("15000m"),
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v1.ResourceName(v1.ResourceMemory): resource.MustParse("48Gi"),
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},
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},
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