The exponential growth in processor performance seems to have reached a turning point. Nowadays, energy efficiency is as important as performance and has become a critical aspect to the development of scalable systems. These strict energy constraints paved the way for the development of multi and manycore processors. Research on the performance and the energy efficiency of numerical kernels on multicores are common but studies in the context of manycores are sparse. Unlike these works, in this paper we analyze a well-known irregular NP-complete problem, the Traveling-Salesman Problem (TSP). This study investigates two aspects of the TSP on multicore, NUMA, and manycore processors. First, we concentrate on the nontrivial task of adapting this application to a manycore, specifically the novel MPPA-256 manycore processor. Then, we analyze its performance and energy consumption on different platforms that comprise general-purpose and low-power multicores, a NUMA machine, and the MPPA-256 manycore. Our results show that applications able to fully use the resources of a manycore can have better performance and may consume 9.8 and 13 times less energy when compared to low-power and general-purpose multicore processors, respectively.