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In this theory, parallel interactions across time (coarticulation) and parallel interactions across space (dual-task interference) are viewed as two aspects of a common underlying process. It describes a dynamical system which is embodied as a "parallel distributed processing" or "connectionist" ...
The large-scale data centers (e.g., Google, Amazon’s EC2) follow this commonly accepted approach to SunwayMR overview The HPC clustering system for running SunwayMR ought to include several computing nodes and desktops, etc., as depicted in Fig. 1. Parallel machines are networked together ...
This paper presents a distributed approach to optimal power flow (OPF) in an electrical network, suitable for application in a future smart grid scenario where access to resource and control is decentralized. The non-convex OPF problem is solved by an au
This study proposes a faster image classification approach that parallelizes the traditional Adaboost-Backpropagation (BP) neural network using the MapReduce parallel programming model. First, we construct a strong classifier by assembling the outputs of 15 BP neural networks (which are individually ...
and users simultaneously download small chunks of the file from multiple peers who can transmit it the fastest. A distributed approach ensures that files are available even if some of the peers are offline, and by downloading in parallel, the system is able to ensure that the aggregate system ...
joins, on top of parallel retrieval of underlying partitioned datasets. In this paper, we address these points by: (i) using the polyglot approach of the CloudMdsQL query language that allows native queries to be expressed as inline scripts and combined with SQL statements for ad-hoc ...
(another message) to another program or user, or create a new actor altogether. This design facilitates sharding within the Gear networks. The Actor model provides a cohesive framework for parallel and distributed computing, ensuring a unified approach. Due to actors having private states, the ...
In the parallel and distributed system MapReduce (Bendechache et al., 2018) has become the most common platform for large-scale mining. MapReduce can be used on CPU, GPUs, GRIDs and the cloud on multi-core devices. Many other large-scale data processing systems have also been developed to...