Programs running on different cores in a multicore serverare often forced to share resources like off-chip memory,caches, I/O devices, etc. This resource sharing often leadsto degraded performance, a slowdown, for the programsthat share the resources. A job scheduler can improve performance by co-scheduling programs that use different resources on the same server. The most common approachto solve this co-scheduling problem has been to make jobschedulers resource aware, finding ways to characterize andquantify a program’s resource usage. We have earlier suggested a simple, program and resource agnostic, scheme asa stepping stone to solving this problem: Avoid TerribleTwins, i.e., avoid co-schedules that contain several instancesfrom the same program. This scheme showed promising results when applied to dual-core servers. In this paper, weextend the analysis and evaluation to also cover quad-coreservers. We present a probabilistic model and empirical datathat show that execution slowdowns get worse as the numberof instances of the same program increases. Our schedulingsimulations show that if all co-schedules containing multiple instances of the same program are removed, the averageslowdown is decreased from 54% to 46% and that the worstcase slowdown is decreased from 173% to 108%.