Data Flow Technology Research Articles

Design of sports posture real-time monitoring system based on sensor data flow

Traditional motion posture monitoring system has some problems such as time-consuming monitoring, low monitoring accuracy and poor monitoring effect. Therefore, this paper designs a real-time motion posture monitoring system based on sensor data flow. In the aspect of hardware, the whole structure of human motion posture monitoring system is designed. The mPU-92/65 six-axis motion processing sensor is selected to collect motion posture, and the module of human motion status detection is designed by MEMS sensor. In software, according to the amplitude fusion information of sensor output and correlation mining, fuzzy fusion model of motion posture data acquisition is established by using correlation component detection method, and real-time monitoring of motion posture is realized by combining sensor data flow technology. The experimental results show that when the number of iterations is 300, the motion posture monitoring accuracy of the designed system can reach 99.57%, the motion posture monitoring time is only 31 ms, and the motion posture monitoring recall rate is as high as 98.65%, indicating that the designed system can improve the motion posture monitoring effect.

Quantum Chemistry in Dataflow: Density-Fitting MP2.

We demonstrate the use of dataflow technology in the computation of the correlation energy in molecules at the Møller-Plesset perturbation theory (MP2) level. Specifically, we benchmark density fitting (DF)-MP2 for as many as 168 atoms (in valinomycin) and show that speed-ups between 3 and 3.8 times can be achieved when compared to the MOLPRO package run on a single CPU. Acceleration is achieved by offloading the matrix multiplications steps in DF-MP2 to Dataflow Engines (DFEs). We project that the acceleration factor could be as much as 24 with the next generation of DFEs.

Research on the Food Safety Information Management System based on the Data Flow Technology

Food is the paramount necessity of the people. Food is the material foundation of human survival and food safety is the most basic insurance. Food safety crisis management mechanism of local government has an important significance on deepening the theoretical research of food safety crisis management perfecting the food safety management function and management mechanism. This study conducted a deep research on the food security issues from public management crisis management theory, institutional economics and other theories; and based on the food security crisis management it carried a research on mechanism in order to put forward feasible policies and suggestions on food safety problem for local government. The food safety information management system based on data flow technology is also constructed in this study.

MUSKEL: an expandable skeleton environment

Programming models based on algorithmic skeletons promise to raise the level of abstraction perceived by programmers when implementing parallel applications, while guaranteeing good performance figures. At the same time, however, they restrict the freedom of programmers to implement arbitrary parallelism exploitation patterns. In fact, efficiency is achieved by restricting the parallelism exploitation patterns provided to the programmer to the useful ones for which efficient implementations, as well as useful and efficient compositions, are known. In this work we introduce muskel , a full Java library targeting workstation clusters, networks and grids and providing the programmers with a skeleton based parallel programming environment. muskel is implemented exploiting (macro) data flow technology, rather than the more usual skeleton technology relying on the use of implementation templates. Using data flow, muskel easily and efficiently implements both classical, predefined skeletons, and user-defined parallelism exploitation patterns. This provides a means to overcome some of the problems that Cole identified in his skeleton manifesto as the issues impairing skeleton success in the parallel programming arena. We discuss fully how user-defined skeletons are supported by exploiting a data flow implementation, experimental results and we also discuss extensions supporting the further characterization of skeletons with non-functional properties, such as security, through the use of Aspect Oriented Programming and annotations.