Premelting-Induced Smoothening of the Ice-Vapor Interface

We perform computer simulations of the quasiliquid layer of ice formed at the ice-vapor interface close to the ice Ih-liquid-vapor triple point of water. Our study shows that the two distinct surfaces bounding the film behave at small wavelengths as atomically rough and independent ice-water and water-vapor interfaces. For long wavelengths, however, the two surfaces couple, large scale parallel fluctuations are inhibited, and the ice-vapor interface becomes smooth. Our results could help explain the complex morphology of ice crystallites.

Premelting-Induced Smoothening of the Ice-Vapor Interface

We perform computer simulations of the quasi-liquid layer of ice formed at the ice/vapor interface close to the ice Ih/liquid/vapor triple point of water. Our study shows that the two distinct surfaces bounding the film behave at small wave-lengths as atomically rough and independent ice/water and water/vapor interfaces. For long wave-lengths, however, the two surfaces couple, large scale parallel fluctuations are inhibited and the ice/vapor interface becomes smooth. Our results could help explaining the complex morphology of ice crystallites.

Reconfigurable computing for Monte Carlo simulations: results and prospects of the Janus project

We describe Janus, a massively parallel FPGA-based computer optimized for the simulation of spin glasses, theoretical models for the behavior of glassy materials. FPGAs (as compared to GPUs or many-core processors) provide a complementary approach to massively parallel computing. In particular, our model problem is formulated in terms of binary variables, and floating-point operations can be (almost) completely avoided. The FPGA architecture allows us to run many independent threads with almost no latencies in memory access, thus updating up to 1024 spins per cycle. We describe Janus in detail and we summarize the physics results obtained in four years of operation of this machine; we discuss two types of physics applications: long simulations on very large systems (which try to mimic and provide understanding about the experimental non equilibrium dynamics), and low-temperature equilibrium simulations using an artificial parallel tempering dynamics. The time scale of our non-equilibrium simulations spans eleven orders of magnitude (from picoseconds to a tenth of a second). On the other hand, our equilibrium simulations are unprecedented both because of the low temperatures reached and for the large systems that we have brought to equilibrium. A finite-time scaling ansatz emerges from the detailed comparison of the two sets of simulations. Janus has made it possible to perform spin glass simulations that would take several decades on more conventional architectures. The paper ends with an assessment of the potential of possible future versions of the Janus architecture, based on state-of-the-art technology.

Simulating spin systems on IANUS, an FPGA-based computer

We describe the hardwired implementation of algorithms for Monte Carlo simulations of a large class of spin models. We have implemented these algorithms as VHDL codes and we have mapped them onto a dedicated processor based on a large FPGA device. The measured performance on one such processor is comparable to O(100) carefully programmed high-end PCs: it turns out to be even better for some selected spin models. We describe here codes that we are currently executing on the IANUS massively parallel FPGA-based system.