Efficient parallel algorithm for robot inverse dynamics computation
IEEE Transactions on Systems, Man and Cybernetics
On the complexity of integer programming
Journal of the ACM (JACM)
Computer Algorithms: Introduction to Design and Analysis
Computer Algorithms: Introduction to Design and Analysis
VLSI and Modern Signal Processing
VLSI and Modern Signal Processing
VLSI for Pattern Recognition and Image Processing
VLSI for Pattern Recognition and Image Processing
Introduction to VLSI Systems
The Design and Analysis of Computer Algorithms
The Design and Analysis of Computer Algorithms
Datapath scheduling for two-level pipelining
DAC '91 Proceedings of the 28th ACM/IEEE Design Automation Conference
A Polynomial Algorithm for Balancing Acyclic Data Flow Graphs
IEEE Transactions on Computers
Buffer assignment for data driven architectures
ICCAD '93 Proceedings of the 1993 IEEE/ACM international conference on Computer-aided design
Buffer Assignment Algorithms on Data Driven ASICs
IEEE Transactions on Computers
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An efficient decomposition technique that provides a more systematic approach in solving the optimal buffer assignment problem of an acyclic data-flow graph (ADFG) with a large number of computational nodes is presented. The buffer assignment problem is formulated as an integer linear optimization problem that can be solved in pseudopolynomial time. However, if the size of an ADFG increases, then integer linear constraint equations may grow exponentially, making the optimization problem more intractable. The decomposition approach utilizes the critical path concept to decompose a directed ADFG into a set of connected subgraphs, and the integer linear optimization technique can be used to solve the buffer assignment problem in each subgraph. Thus, a large-scale integer linear optimization problem is divided into a number of smaller-scale subproblems, each of which can be easily solved in pseudopolynomial time. Examples are given to illustrate the proposed decomposition technique.