Janus: An FPGA-Based System for High-Performance Scientific Computing

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.

[1]  E. M.,et al.  Statistical Mechanics , 2021, Manual for Theoretical Chemistry.

[2]  R. L. Brooks On colouring the nodes of a network , 1941, Mathematical Proceedings of the Cambridge Philosophical Society.

[3]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[4]  Eytan Domany,et al.  Classification of Order-Disorder Transitions in Common Adsorbed Systems: Realization of the Four-State Potts Model , 1977 .

[5]  Giorgio Parisi,et al.  Effects of the random number generator on computer simulations , 1985 .

[6]  Cecilia R. Aragon,et al.  Optimization by Simulated Annealing: An Experimental Evaluation; Part I, Graph Partitioning , 1989, Oper. Res..

[7]  Cecilia R. Aragon,et al.  Optimization by Simulated Annealing: An Experimental Evaluation; Part II, Graph Coloring and Number Partitioning , 1991, Oper. Res..

[8]  Voges,et al.  Effect of random quenched impurities on the critical behavior of a four-state Potts system in two dimensions: An experimental study. , 1994, Physical review letters.

[9]  Voges,et al.  Effect of oxygen impurities on the critical properties of the (2 x 2)-2H/Ni(111) order-disorder phase transition. , 1995, Physical review. B, Condensed matter.

[10]  Hiroshi Harada,et al.  The design and evaluation of high performance communication using a Gigabit Ethernet , 1999, ICS '99.

[11]  C. L. Ullod,et al.  SUE: A special purpose computer for spin glass models , 2001 .

[12]  Geppino Pucci,et al.  The Potential of On-Chip Multiprocessing for QCD Machines , 2005, HiPC.

[13]  K. Binder,et al.  A Guide to Monte Carlo Simulations in Statistical Physics , 2000 .

[14]  Samuel Williams,et al.  The Landscape of Parallel Computing Research: A View from Berkeley , 2006 .

[15]  Denis Navarro,et al.  Ianus: an adaptive FPGA computer , 2006, Computing in Science & Engineering.

[16]  N. Eicker,et al.  QCD on the Cell Broadband Engine , 2007 .

[17]  G. Parisi,et al.  Nonequilibrium spin-glass dynamics from picoseconds to a tenth of a second. , 2008, Physical review letters.

[18]  Denis Navarro,et al.  Simulating spin systems on IANUS, an FPGA-based computer , 2007, Comput. Phys. Commun..