The effect of Intel® Hyper-Threading (HT) technology on a system?s performance varies according to the characteristics of the application running on the system and the configuration of the system. High performance computing (HPC) clusters introduce additional variables, such as the math libraries used in solving linear algebra equations that can affect the performance of scientific and engineering applications in particular. In this paper, we study the effect of HT on MPI-based applications by varying the math library. We configured an Intel-based HPC cluster and used the High Performance Linpack (HPL) benchmark to study the performance characteristics without changing hardware or communication parameters, but by linking the application with different math libraries. What we have found is that, even though the application or hardware parameters remain the same, HT may help or hinder the overall performance of the cluster depending on the computational efficiency of the mathematical functions. For instance, enabling HT in a cluster made up of Intel Xeon™ based machines using the ATLAS library with high performance Linpack (HPL), improved performance in our testing. For the same application, if mathematical libraries that more efficiently utilize the processor resources are used, then HT may relatively degrade the performance due to resource sharing in virtual processors.