The increasing reliance on parallel computing for scientific simulation and experimentation has made high performance cluster computing an integral part of the scientific process. The result of this explosion in demand is that multiple clusters often co-exist within the same research campus. As more and more computational power is demanded by researchers, effectively leveraging existing cluster resources becomes critical to supplying needed cycles. One way to improve cluster utilization is to forward and span jobs across multiple clusters. However, software heterogeneity is often a barrier to implementing these capabilities. Dynamic Virtual Clustering is presented as the solution to enable forwarding and spanning in arbitrary clusters by using virtual machines to abstract software environment differences. Although the use of virtual machines incurs a performance loss, the ability to span and forward jobs improves throughput and turnaround thereby increasing the performance seen by common cluster workloads.