Power-Aware Embedded Computing

2009 ◽  
pp. 11-1-11-25
Author(s):  
Anand Ramachandran ◽  
Margarida Jacome
Keyword(s):  
Embedded Computing

Evaluating the potential of graphics processors for high performance embedded computing

2011 ◽  
Author(s):  
Shuai Mu ◽  
Chenxi Wang ◽  
Ming Liu ◽  
Dongdong Li ◽  
Maohua Zhu ◽  
...  
Keyword(s):  
High Performance ◽  
Graphics Processors ◽  
Embedded Computing

scholarly journals Embedded GPU Implementation for High-Performance Ultrasound Imaging

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 884
Author(s):  
Stefano Rossi ◽  
Enrico Boni
Keyword(s):  
High Performance ◽  
Graphics Processing Unit ◽  
Digital Signal ◽  
Processing Unit ◽  
Embedded Computing ◽  
Field Programmable ◽  
Peripheral Component Interconnect ◽  
Programmable Gate Arrays ◽  
Graphics Processing ◽  
Signal Processors

Methods of increasing complexity are currently being proposed for ultrasound (US) echographic signal processing. Graphics Processing Unit (GPU) resources allowing massive exploitation of parallel computing are ideal candidates for these tasks. Many high-performance US instruments, including open scanners like ULA-OP 256, have an architecture based only on Field-Programmable Gate Arrays (FPGAs) and/or Digital Signal Processors (DSPs). This paper proposes the implementation of the embedded NVIDIA Jetson Xavier AGX module on board ULA-OP 256. The system architecture was revised to allow the introduction of a new Peripheral Component Interconnect Express (PCIe) communication channel, while maintaining backward compatibility with all other embedded computing resources already on board. Moreover, the Input/Output (I/O) peripherals of the module make the ultrasound system independent, freeing the user from the need to use an external controlling PC.

scholarly journals Reconfiguring Smart Structures Using Approximate Heteroclinic Connections in a Spring-Mass Model

2015 ◽  
Author(s):  
Jiaying Zhang ◽  
Colin R. McInnes
Keyword(s):  
Optimal Control ◽  
Control Method ◽  
Smart Structures ◽  
Polynomial Method ◽  
Reference Trajectory ◽  
Sensors And Actuators ◽  
Embedded Computing ◽  
Equal Energy ◽  
Optimal Control Method ◽  
Heteroclinic Connection

Several new methods are proposed to reconfigure smart structures with embedded computing, sensors and actuators. These methods are based on heteroclinic connections between equal-energy unstable equilibria in an idealised spring-mass smart structure model. Transitions between equal-energy unstable (but actively controlled) equilibria are considered since in an ideal model zero net energy input is required, compared to transitions between stable equilibria across a potential barrier. Dynamical system theory is used firstly to identify sets of equal-energy unstable configurations in the model, and then to connect them through heteroclinic connection in the phase space numerically. However, it is difficult to obtain such heteroclinic connections numerically in complex dynamical systems, so an optimal control method is investigated to seek transitions between unstable equilibria, which approximate the ideal heteroclinic connection. The optimal control method is verified to be effective through comparison with the results of the exact heteroclinic connection. In addition, we explore the use of polynomials of varying order to approximate the heteroclinic connection, and then develop an inverse method to control the dynamics of the system to track the polynomial reference trajectory. It is found that high order polynomials can provide a good approximation to true heteroclinic connections and provide an efficient means of generating such trajectories. The polynomial method is envisaged as being computationally efficient to form the basis for real-time reconfiguration of real, complex smart structures with embedded computing, sensors and actuators.

Study of Data Fusion Mechanism Based on the WSN

2013 ◽  
Vol 321-324 ◽  
pp. 600-603
Author(s):  
Wei Liu ◽  
Qin Sheng Du ◽  
Le Le Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Wireless Sensor ◽  
Network Technology ◽  
Fusion Method ◽  
Simulation Test ◽  
Embedded Computing ◽  
New Type

Wireless sensor networks integrated four technologies including sensor, embedded computing, network technology and wireless communication. It is a new type of non-infrastructure wireless network. In this paper, a data fusion method has been brought forward based on wireless sensor networks, and through an algorithm simulation test, It is proved that the algorithm is effective to reduce the energy consumption of the network, and extend the lifetime of the network.

Embedded Computing in the Mechanical Engineering Curriculum: A Course Featuring Structured Laboratory Exercises

1997 ◽  
Vol 86 (3) ◽  
pp. 285-290 ◽  
Author(s):  
William R. Murray ◽  
Joseph L. Garbini
Keyword(s):  
Mechanical Engineering ◽  
Engineering Curriculum ◽  
Embedded Computing

Power Aware Embedded Computing

2005 ◽  
pp. 449-474
Keyword(s):  
Embedded Computing
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