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Recent innovations focused around {\em parallel} processing, either throughsystems containing multiple processors or processors containing multiple cores,hold great promise for enhancing the performance of the trigger at the LHC andextending its physics program. The flexibility of the CMS/ATLAS trigger systemallows for easy integration of computational accelerators, such as NVIDIA'sTesla Graphics Processing Unit (GPU) or Intel's \xphi, in the High LevelTrigger. These accelerators have the potential to provide faster or more energyefficient event selection, thus opening up possibilities for new complextriggers that were not previously feasible. At the same time, it is crucial toexplore the performance limits achievable on the latest generation multicoreCPUs with the use of the best software optimization methods. In this article, anew tracking algorithm based on the Hough transform will be evaluated for thefirst time on a multi-core Intel Xeon E5-2697v2 CPU, an NVIDIA Tesla K20c GPU,and an Intel \xphi\ 7120 coprocessor. Preliminary time performance will bepresented.

First Evaluation of the CPU, GPGPU and MIC Architectures for Real Time Particle Tracking based on Hough Transform at the LHC