RESUMO
The reconfigurable computing paradigm, which exploits the flexibility and versatility of field-programmable gate arrays (FPGAs), has emerged as a powerful solution for speeding up time-critical algorithms. This paper describes a reconfigurable computing solution for processing raw mass spectrometric data generated by MALDI-TOF instruments. The hardware-implemented algorithms for denoising, baseline correction, peak identification, and deisotoping, running on a Xilinx Virtex-2 FPGA at 180 MHz, generate a mass fingerprint that is over 100 times faster than an equivalent algorithm written in C, running on a Dual 3-GHz Xeon server. The results obtained using the FPGA implementation are virtually identical to those generated by a commercial software package MassLynx.
RESUMO
Avalanching systems are treated analytically using the renormalization group (in the self-organized-criticality regime) or mean-field approximation, respectively. The latter describes the state in terms of the mean number of active and passive sites, without addressing the inhomogeneity in their distribution. This paper goes one step further by proposing a kinetic description of avalanching systems making use of the distribution function for clusters of active sites. We illustrate an application of the kinetic formalism to a model proposed for the description of the avalanching processes in the reconnecting current sheet of the Earth's magnetosphere. A description of avalanching systems is proposed that makes use of the distribution function for clusters of active sites. A general kinetic equation is derived that describes the temporal evolution of the distribution function, in terms of growth and shrinking probabilities. The distribution of clusters is derived for the stationary regime, for a quite general class of avalanching systems or arbitrary dimensionality. The approach, including the probability calculation, is illustrated by an application of the kinetic description to the recently proposed burning model.
