Nanotechnology has the potential to revolutionize our lives and to provide technological solutions to our problems in energy, the environment and medicine. This paper describes a swarm intelligence-based control mechanism for medical nanorobots that operates as artificial platelets to search for wounds within the human body. We present a coloured perceptive particle swarm (CPPSO) algorithm to control the movement of nanorobots in self-assembly. To predict emergent nanorobot behaviors, we designed a parallel simulator that models how nanorobots interact with each other and the environment. We will show that due to their implicitly parallel structure, swarm intelligence algorithms can benefit from GPU-based implementations. The algorithm is implemented with CUDA. With the GPU-based implementation adopted here, we find that CPPSO is faster than a PPSO implementation.

Controlling swarms of medical nanorobots using CPPSO on a GPU

Spezzano G
2016

Abstract

Nanotechnology has the potential to revolutionize our lives and to provide technological solutions to our problems in energy, the environment and medicine. This paper describes a swarm intelligence-based control mechanism for medical nanorobots that operates as artificial platelets to search for wounds within the human body. We present a coloured perceptive particle swarm (CPPSO) algorithm to control the movement of nanorobots in self-assembly. To predict emergent nanorobot behaviors, we designed a parallel simulator that models how nanorobots interact with each other and the environment. We will show that due to their implicitly parallel structure, swarm intelligence algorithms can benefit from GPU-based implementations. The algorithm is implemented with CUDA. With the GPU-based implementation adopted here, we find that CPPSO is faster than a PPSO implementation.
2016
Gpu computing Smarm intelligence medical nanorobot
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/317644
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