A two-dimensional Ising model with nearest-neighbors ferromagnetic interactions is implemented in a Field Programmable Gate Array (FPGA) board. Extensive Monte Carlo simulations were carried out using an efficient hardware representation of individual spins and a combined global-local LFSR random number generator. Consistent results regarding the descriptive properties of magnetic systems, like energy, magnetization and susceptibility are obtained while a speed-up factor of approximately six times is achieved in comparison to previous FPGA-based published works and almost 104 times in comparison to a standard CPU simulation. A detailed description of the logic design used is given together with a careful analysis of the quality of the random number generator used. The obtained results confirm the potential of FPGAs for analyzing the statistical mechanics of magnetic systems.
FPGA Hardware Acceleration of Monte Carlo Simulations for the Ising Model / Ortega-Zamorano F.; Montemurro M.A.; Cannas S.A.; Jerez J.M.; Franco L.. - In: IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS. - ISSN 1045-9219. - ELETTRONICO. - 27:9(2016), pp. 7347434.2618-7347434.2627. [10.1109/TPDS.2015.2505725]
FPGA Hardware Acceleration of Monte Carlo Simulations for the Ising Model
Montemurro M. A.Membro del Collaboration Group
;
2016
Abstract
A two-dimensional Ising model with nearest-neighbors ferromagnetic interactions is implemented in a Field Programmable Gate Array (FPGA) board. Extensive Monte Carlo simulations were carried out using an efficient hardware representation of individual spins and a combined global-local LFSR random number generator. Consistent results regarding the descriptive properties of magnetic systems, like energy, magnetization and susceptibility are obtained while a speed-up factor of approximately six times is achieved in comparison to previous FPGA-based published works and almost 104 times in comparison to a standard CPU simulation. A detailed description of the logic design used is given together with a careful analysis of the quality of the random number generator used. The obtained results confirm the potential of FPGAs for analyzing the statistical mechanics of magnetic systems.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
