Darrell R. Ulm

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This paper describes a parallelization of the sequential dynamic programming method for solving a 2D knapsack problem where multiples of n rectangular objects are optimally packed into a knapsack of size L W and are only obtainable with guillotine-type side to side cuts. The parallel algorithm is described and analyzed for the associative model. The(More)
The ASC model for parallel computation supports a generalization of an associative style of computing that has been used since the introduction of associative SIMD computers in the early 1970's. In particular, this model supports data parallelism, constant time maximum and minimum operations, one or more instruction streams ISs which are sent to an equal(More)
Summary form only given. This paper describes a parallel solution of the sequential dynamic programming method for solving a NP class, 2D knapsack (or cutting-stock) problem which is the optimal packing of multiples of n rectangular objects into a knapsack of size L/spl times/W and are only obtainable with guillotine-type (side to side) cuts. Here, we(More)
Parallel random access memory, or PRAM, is a now venerable model of parallel computation that that still retains its usefulness for the design and analysis of parallel algorithms. Parallel computational models proposed after PRAM address short comings of PRAM in terms of modeling realism of actual machines. In this work, we propose a multiple instruction(More)
Parallel random access memory, or PRAM, is a now venerable model of parallel computation that that still retains its usefulness for the design and analysis of parallel algorithms. Parallel computational models proposed after PRAM address short comings of PRAM in terms of modeling realism of actual machines. In this work, we propose a multiple instruction(More)
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