The Community for Technology Leaders
RSS Icon
Issue No.01 - January/February (2009 vol.11)
pp: 48-58
Janus is a modular, massively parallel, and reconfigurable FPGA-based computing system. Each Janus module has one computational core and one host. Janus is tailored to, but not limited to, the needs of a class of hard scientific applications characterized by regular code structure, unconventional data-manipulation requirements, and a few Megabits database. The authors discuss this configurable system's architecture and focus on its use for Monte Carlo simulations of statistical mechanics, as Janus performs impressively on this class of application.
ubiquitous computing, field programmable gate arrays, mathematics computing, Monte Carlo methods, scientific information systems, statistical mechanics,statistical mechanics, Janus, FPGA-based system, high-performance scientific computing, Megabits database, Monte Carlo simulations,Scientific computing, Computational modeling, Lattices, Monte Carlo methods, Parallel processing, Physics computing, Computer simulation, Pervasive computing, Biology computing, Application software,Janus, Monte Carlo simulations, field-programmable gate array, FPGA, scientific computing
F. Belletti, M. Cotallo, A. Cruz, L.A. Fernandez, A. Gordillo-Guerrero, M. Guidetti, A. Maiorano, F. Mantovani, E. Marinari, V. Martin-Mayor, A. Muoz-Sudupe, D. Navarro, G. Parisi, S. Perez-Gaviro, M. Rossi, J.J. Ruiz-Lorenzo, S.F. Schifano, D. Sciretti, A. Tarancon, R. Tripiccione, J.L. Velasco, D. Yllanes, G. Zanier, "Janus: An FPGA-Based System for High-Performance Scientific Computing", Computing in Science & Engineering, vol.11, no. 1, pp. 48-58, January/February 2009, doi:10.1109/MCSE.2009.11
1. P. Young, Spin Glasses and Random Fields, World Scientific, 1998.
2. K. Asanovic et al., The Landscape of Parallel Computing Research: A View from Berkeley, tech. report UCB/EECS-2006-183, College of Eng., Univ. of Calif. Berkeley, 2006; EECS-2006-183.html.
3. E. Domany, M. Schick, and J.S. Walker, "Classification of Order-Disorder Transitions in Common Adsorbed Systems: Realization of the Four-State Potts Model," Physics Rev. Letters, vol. 38, 1997, p. 1148.
4. R.L. Park et al., Ordering in Two Dimensions, S.K. Sinha ed., , North-Holland, 1980, p.17.
5. L. Schwenger et al., "Effect of Random Quenched Impurities on the Critical Behavior of a Four-State Potts SYSTEm in Two Dimensions: An Experimental Study," Physics Rev. Letters, vol. 73, 1994, p. 296.
6. K. Budde et al., "Effect of Oxygen Impurities on the Critical Properties of the (2×2)-2H/Ni(111) Order-Disorder Phase Transition," Physics Rev. B, vol. 52, 1995, p. 9275.
7. R.L. Brooks, "On Colouring the Nodes of a Network," Proc. Cambridge Philosophical Soc., vol. 37, 1941, pp. 194–197.
8. K. Huang, Statistical Mechanics, 2nd ed., Wiley, 1987.
9. N. Metropolis et al., "Equation of State Calculation by Fast Computing Machines," J. Chemical Physics, vol. 21, no. 6, 1953, pp. 1087–1092.
10. A. Cruz et al., "SUE: A Special Purpose Computer for Spin Glass Models," Computer Physics Comm., vol. 133, nos 2–3, 2001, p. 165–176.
11. F. Belletti et al., "Ianus: An Adaptive FPGA Computer," Computing in Science and Eng., vol. 8, no. 1, 2006, pp. 41–48.
12. F. Belletti et al., "Nonequilibrium Spin Glass Dynamics form Picoseconds to 0.1 Seconds," Physical Rev. Letters, vol. 101, 2008, p. 157–201.
13. Belletti et al., "Simulating Spin Systems on IANUS, an FPGA-Based Computer," Computer Physics Comm., vol. 178, no. 3, 2008, p. 208–216.
14. G. Parisi and F. Rapuano, "Effects of the Random Number Generator on Computer Simulations," Physics Letters B, vol. 157, no. 4 1985, p. 301–302.
15. F. Belletti et al., "QCD on the Cell Broadband Engine," Proc. Science (PoS), Lattice, 2007.
57 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool