Incomparability in parallel computation

Parallel computation framework for optimizing trailer routes in bulk transportation

We consider a rich tanker trailer routing problem with stochastic transit times for chemicals and liquid bulk orders. A typical route of the tanker trailer comprises of sourcing a cleaned and prepped trailer from a pre-wash location, pickup and delivery of chemical orders, cleaning the tanker trailer at a post-wash location after order delivery and prepping for the next order. Unlike traditiona...

Parallel CRC Computation in FPGAs

This paper presents how to compute n-bit CRC checksums on FPGAs in parallel. For this task, a specialized logic minimization strategy is outlined. It achieves signiicantly better results than standard logic optimizers. For n 96, CRC designs with an n-bit I/O interface are poorly routable. However, for smaller I/O interfaces even a 128-bit CRC can be implemented.

Mixed Volume Computation in Parallel

Efficient algorithms for computing mixed volumes, via the computation of mixed cells, have been implemented in DEMiCs [18] and MixedVol-2.0 [13]. While the approaches in those two packages are somewhat different, they follow the same theme and are both highly serial. To fit the need for the parallel computing, a reformulation of the algorithms is inevitable. This article proposes a reformulatio...

Parallel Computation in Definitive Models

Superlinear Speedup in Parallel Computation

Speedup of a parallel computation is defined as Sp = T/Tp [2], where T is the sequential time of a problem and Tp is the parallel time to solve the same problem using p processors. Tp was argued to be no greater than P in [3]. However, in practice, people observed “superlinear speedup”, i.e. the speedup with P processors is greater than P. Two main reasons for superlinear speedup are shown in [...