Minimizing memory requirements for program and data are critical objectives when synthesizing software for embedded DSP applications. Previously, it has been demonstrated that for graphical programs based on the widely-used synchronous dataflow model, an important class of minimum code size implementations can be viewed as parenthesizations of lexical orderings of the computational blocks. Such...

The induced width along an elimination ordering is an important factor in the space and time complexity of many inference algorithms for graphical models. Indeed, slight changes in induced width can sometimes dictate whether a particular problem is feasible (i.e. will t in memory) using variable elimination methods. For this reason, generating low width elimination orders has received extensive...

This paper presents an algorithm for nding parallel elimination orderings for Gaussian elimination. Viewing a system of equations as a graph, the algorithm can be applied directly to interval graphs and chordal graphs. For general graphs, the algorithm can be used to parallelize the ordering produced by some other heuristic such as minimum degree. In this case, the algorithm is applied to the c...

This paper presents an algorithm for nding parallel elimination orderings for Gaussian elimination. Viewing a system of equations as a graph, the algorithm can be applied directly to interval graphs and chordal graphs. For general graphs, the algorithm can be used to parallelize the ordering produced by some other heuristic such as minimum degree. In this case, the algorithm is applied to the c...

In this paper we address the minimum-energy broadcast problem. To increase the energy efficiency, we allow nodes that are out of the transmission range of a transmitter to collect the energy of unreliably received overheard signals. As a message is forwarded through the network, a node will have multiple opportunities to reliably receive the message by collecting energy during each retransmissi...

Divide-and-conquer approximation algorithms for vertex ordering problems partition the vertex set of graphs, compute recursively an ordering of each part, and “glue” the orderings of the parts together. The computed ordering is specified by a decomposition tree that describes the recursive partitioning of the subproblems. At each internal node of the decomposition tree, there is a degree of fre...

One of the most important and well studied problems related to sparse Cholesky factorization is to compute elimination orderings that give as few nonzero entries as possible in the resulting factors. We study the problem of modifying a given elimination ordering through local reorderings. We present new theoretical results on equivalent orderings, including a new characterization of such orderi...

In this paper we prove some stochastic comparisons results for progressive type II censored order statistics. The problem of stochastically comparing concomitants of the two progressive type II censored order statistics with possibly different schemes, under different kinds of dependence between X and Y is considered and it is proved that if Y is stochastically increasing (decreasing) in X, ...

We study a single-product periodic-review inventory model in which the ordering quantity is either zero or at least a minimum order size+ The ordering cost is a linear function of the ordering quantity, and the demand in different time periods are independent random variables+ The objective is to characterize the inventory policies that minimize the total discounted ordering, holding, and backo...

Divide-and-conquer approximation algorithms for vertex ordering problems partition the vertex set of graphs, compute recursively an ordering of each part, and “glue” the orderings of the parts together. The computed ordering is specified by a decomposition tree that describes the recursive partitioning of the subproblems. At each internal node of the decomposition tree, there is a degree of fre...