The problem of the optimization of complex data-paths relative to a repertoire of specified operations is discussed. Data-paths can be simplified if interconnections are functionally redundant. Redundancy is detected ...
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The problem of the optimization of complex data-paths relative to a repertoire of specified operations is discussed. Data-paths can be simplified if interconnections are functionally redundant. Redundancy is detected by means of the universal quantification of ROBDD representations of the data-path and of the specified operations. The full logical complexity of ALU's described at the gate-level is considered. A 0-1 ILP formulation of the minimization problem is given and solved by means of ROBDD's. A solution of the prelogic rectification problem for control-signals is presented.
In this paper, a new approach to the problem of allocating multiport memory modules for data storage is presented. Previous approaches divide the allocation problem into two separate steps: (i) grouping the variables ...
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In this paper, a new approach to the problem of allocating multiport memory modules for data storage is presented. Previous approaches divide the allocation problem into two separate steps: (i) grouping the variables (or registers) to form memory modules and (ii) determining the interconnections between the memory modules and functional units. Yet, there is no easy way to predict the result of step (ii) during step (i). In our approach, we place primary importance on the cost of interconnections. Consequently, we try to minimize the cost of interconnections first and then to group the variables to form memory modules later. For a number of benchmark problems, it has been shown that this approach is quite effective.
An extended zero-one linearprogramming (O/1 LP) model for the scheduling problem in high-level synthesis is presented. As an extension to former approaches, the 0/1 LP model can handle multifunctional function units ...
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An extended zero-one linearprogramming (O/1 LP) model for the scheduling problem in high-level synthesis is presented. As an extension to former approaches, the 0/1 LP model can handle multifunctional function units as well as different execution times for different instances of the same operation type. These extensions are very important for the applicability of general high-level synthesis tools in real design tasks. The computing time for solving the optimization problems is also acceptable for the new powerful model, since new lower bounds have been introduced that drastically reduce the search space. Some experimental results are shown.< >
Previous researches assumed that the more nets being routed over the cells, the greater the reduction in channel density. In fact, only the routing of critical nets will contribute to the reduction of channel density....
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ISBN:
(纸本)0780309782
Previous researches assumed that the more nets being routed over the cells, the greater the reduction in channel density. In fact, only the routing of critical nets will contribute to the reduction of channel density. The authors propose a heuristic method to find critical nets and use free terminals to further reduce the channel density. Experimental results show that their approach reduces more channel density than previous researches and can speed up the process of over-the-cell routing.< >
Presents a general treatment of the combinatorial approach to the scheduling problem, enhancing previous formulations in the literature. The focus of this paper is a formal analysis of the integer linear programming (...
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Presents a general treatment of the combinatorial approach to the scheduling problem, enhancing previous formulations in the literature. The focus of this paper is a formal analysis of the integer linear programming (ILP) approach, which we use to evaluate the structure of our formulation. Polyhedral theory and duality theory are used to demonstrate that efficient solutions of the scheduling problem can be expected from a carefully formulated integerlinear program. Furthermore, we use the theory of valid inequalities to tighten the constraints and make the formulation more efficient.< >
Most of the sophisticated optimization tools dealing with data dependence analysis, parallelization and data locality exploitation cannot provide satisfactory solutions to a number of problems because they are, in gen...
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Most of the sophisticated optimization tools dealing with data dependence analysis, parallelization and data locality exploitation cannot provide satisfactory solutions to a number of problems because they are, in general, unable to precisely handle some complex systems of linear equations coming from dependence equations between array subscripts. For such cases, these algorithms either provide rough estimates or resort to unefficient and therefore costly enumeration strategies. In this paper, we present an efficient technique, named Fast Determination, for dealing with the enumeration problem which degrades the behavior of sophisticated algorithms. Incorporating Fast Determination would enhance the performance and accuracy of existing algorithms, and widen their scope of application.
integer linear programming (ILP) techniques have recently been proposed to solve the single iteration scheduling problem. In the present work, the integer linear programming formulation is generalized to support unfol...
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integer linear programming (ILP) techniques have recently been proposed to solve the single iteration scheduling problem. In the present work, the integer linear programming formulation is generalized to support unfolded schedules. A new time assignment formulation which automatically pipelines and retimes the dataflow graph (DFG) is presented. A new processor allocation formulation which automatically unfolds the DFG is also presented. It is noted that this is the first time that systematic unfolding is proposed for improving processor utilization on digital signal processing architectures. These models fully optimize the processor utilization for a specific iteration period.
Edge-valued binary-decision diagrams (EVBDDs) are directed acyclic graphs which can represent and manipulate integer functions as effectively as ordered binary-decision diagrams (OBDDs) do for Boolean functions. They ...
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ISBN:
(纸本)9780818644900
Edge-valued binary-decision diagrams (EVBDDs) are directed acyclic graphs which can represent and manipulate integer functions as effectively as ordered binary-decision diagrams (OBDDs) do for Boolean functions. They have been used to perform logic verification and compute the decomposability of Boolean functions. In this paper, we present a new EVBDD application for solving integerlinear programs (ILP), which is an NP-hard problem that appears in many applications. Our approach is to combine the benefits of the EVBDD data structure (in terms of subgraph sharing and caching of computational results) with the state-of-the-art ILP solving techniques. Our program, called FGILP (Function Graph ILP) has been implemented in C under the SIS environment. The preliminary results of FGILP are comparable to those of LINDO.
We describe a new linearprogramming (LP)-based hierarchical pitchmatching method. With a simplified treatment of the inter-cell constraints, the size of the LP problems is significantly smaller than the best known me...
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We describe a new linearprogramming (LP)-based hierarchical pitchmatching method. With a simplified treatment of the inter-cell constraints, the size of the LP problems is significantly smaller than the best known methods. In particular, the pitchmatching problem is decomposed into independent sub-problems by the natural slicing structure in layout. Each sub-problem is folded further to reduce the LP problem size. Experiments show that the LP problem size can be 10 times smaller than the best known result.
integer linear programming (ILP) has long been an important tool for operations research akin to the AI search heuristics for NP-hard problems. However, there has been relatively little incentive to use it in AI, even...
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integer linear programming (ILP) has long been an important tool for operations research akin to the AI search heuristics for NP-hard problems. However, there has been relatively little incentive to use it in AI, even though it also deals with optimization. The problem stems from the misperception that because the general ILP problem is difficult to solve, then it will be difficult for all cases. It is known that AI search at first glance also seems this way until one begins to apply it to a specific domain. Clearly, there are many gains to be had from studying the problem with a different perspective like ILP. The authors look at probabilistic reasoning with Bayesian networks. For some time now, they have been stalled by its computational complexities. Algorithms have been designed for small classes of networks, but have been mainly inextensible to the general case. In particular, the authors consider belief revision in Bayesian networks which is the search for the most probable explanation for some given evidence. They present a new approach for computing belief revision from the ILP point of view. By observing various properties inherent in Bayesian networks, one can successfully develop a hill-climbing strategy which does not require an energy function. This approach can handle the entire class of Bayesian networks. Furthermore, experimental results indicate that finding the most probable explanation can be accomplished fairly easily.
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