We consider a distributed server system and ask which policy should be used for assigning tasks to hosts. In our server, tasks are not preemptible. Also, the task's service demand is not known a priori. We are particularly concerned with the case where the workload is heavy-tailed, as is characteristic of many empirically measured computer workloads. We analyze several natural task assignment policies and propose a new one TAGS Task Assignment based on Guessing Size. The TAGS algorithm is counterintuitive in many respects, including load unbalancing, non-work-conserving, and fairness. We nd that under heavy-tailed workloads, TAGS can outperform all task assignment policies known to us by several orders of magnitude with respect to mean response time and mean slowdown, provided the system load is not too high. We also introduce a new practical performance metric for distributed servers called server expansion. Under the server expansion metric, TAGS signi cantly outperforms all ...