FFTPL: An Analytic Placement Algorithm Using Fast Fourier Transform for Density Equalization

We propose a flat nonlinear placement algorithm FFTPL using fast Fourier transform for density equalization. The placement instance is modeled as an electrostatic system with the analogy of density cost to the potential energy. A well-defined Poisson's equation is proposed for gradient and cost computation. Our placer outperforms state-of-the-art placers with better solution quality and efficiency

Process migration in UNIX environments

To support process migration in UNIX environments, the main problem is how to encapsulate the location dependent features of the system in such a way that a host independent virtual environment is maintained by the migration handlers on the behalf of each migrated process. An object-oriented approach is used to describe the interaction between a process and its environment. More specifically, environmental objects were introduced in UNIX systems to carry out the user-environment interaction. The implementation of the migration handlers is based on both the state consistency criterion and the property consistency criterion

Correctness criteria for process migration

Two correctness criteria, the state consistency criterion and the property consistency criterion for process migration are discussed. The state machine approach is used to model the interactions between a user process and its environment. These criteria are defined in terms of the model. The idea of environment view was introduced to distinguish what a user process observes about its environment from what its environment state really is and argue that a consistent view of the environment must be maintained for every migrating process

Efficient Processing of k Nearest Neighbor Joins using MapReduce

k nearest neighbor join (kNN join), designed to find k nearest neighbors from a dataset S for every object in another dataset R, is a primitive operation widely adopted by many data mining applications. As a combination of the k nearest neighbor query and the join operation, kNN join is an expensive operation. Given the increasing volume of data, it is difficult to perform a kNN join on a centralized machine efficiently. In this paper, we investigate how to perform kNN join using MapReduce which is a well-accepted framework for data-intensive applications over clusters of computers. In brief, the mappers cluster objects into groups; the reducers perform the kNN join on each group of objects separately. We design an effective mapping mechanism that exploits pruning rules for distance filtering, and hence reduces both the shuffling and computational costs. To reduce the shuffling cost, we propose two approximate algorithms to minimize the number of replicas. Extensive experiments on our in-house cluster demonstrate that our proposed methods are efficient, robust and scalable.Comment: VLDB201

Long-Run Purchasing Power Parity with Asymmetric Adjustment: Evidence from Mainland China and Taiwan

This study applies threshold cointegration test advanced by Enders and Siklos (2001) to investigate the properties of asymmetric adjustment in long-run purchasing power parity (PPP) for both Mainland China and Taiwan during the January 1986 to October 2009 period. Although there is evidence of long-run PPP for both Mainland China and Taiwan, the adjustment mechanism is asymmetric. These results have important policy implications for both Mainland China and Taiwan under study.threshold cointegration test; Purchasing Power Parity; asymmetric adjustment; Mainland China; Taiwan