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>

test/e2e_node/perf/workloads/npb_is.go

@@ -44,11 +44,11 @@ func (w npbISWorkload) PodSpec() v1.PodSpec {
 		Image: "gcr.io/kubernetes-e2e-test-images/node-perf/npb-is:1.0",
 		Resources: v1.ResourceRequirements{
 			Requests: v1.ResourceList{
-				v1.ResourceName(v1.ResourceCPU):    resource.MustParse("16000m"),
+				v1.ResourceName(v1.ResourceCPU):    resource.MustParse("15000m"),
 				v1.ResourceName(v1.ResourceMemory): resource.MustParse("48Gi"),
 			},
 			Limits: v1.ResourceList{
-				v1.ResourceName(v1.ResourceCPU):    resource.MustParse("16000m"),
+				v1.ResourceName(v1.ResourceCPU):    resource.MustParse("15000m"),
 				v1.ResourceName(v1.ResourceMemory): resource.MustParse("48Gi"),
 			},
 		},