In this work we present a predictive analytical model that encompasses the performance and scaling characteristics of a nondeterministic particle transport application, MCNP (Mont...
We review the recently developed technique of Monte Carlo model checking and show how it can be applied to the implementation problem for I/O Automata. We then consider some open ...
Many scientific and engineering applications involve inverting large matrices or solving systems of linear algebraic equations. Solving these problems with proven algorithms for d...
Simon Branford, Cihan Sahin, Ashish Thandavan, Chr...
The visibility function in direct illumination describes the binary visibility over a light source, e.g., an environment map. Intuitively, the visibility is often strongly correla...
With technology scaling down to 90nm and below, many yield-driven design and optimization methodologies have been proposed to cope with the prominent process variation and to incr...
Fang Gong, Hao Yu, Yiyu Shi, Daesoo Kim, Junyan Re...
Small-world networks have become an important model for understanding many complex phenomena in science and in sociological contexts. One tool for exploring the critical and phase...
Descriptive Sampling (DS), a Monte Carlo sampling technique based on a deterministic selection of the input values and their random permutation, represents a deep conceptual chang...
Image filtering is often applied as a post-process to Monte Carlo generated pictures, in order to reduce noise. In this paper we present an algorithm based on density estimation t...
The calculation of value-at-risk (VAR) for large portfolios of complex instruments is among the most demanding and widespread computational challenges facing the financial industr...
Paul Glasserman, Philip Heidelberger, Perwez Shaha...
We present the results in embedding a multigrid solver for Poisson's equation into the parallel 3D Monte Carlo device simulator, PMC-3D. First we have implemented the sequent...