GPGPU implementation of growing neural gas: application to 3D scene reconstruction

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6× compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.

Evidence of Intracrystalline Mesostructured Porosity in Zeolites by Advanced Gas Sorption, Electron Tomography and Rotation Electron Diffraction

The small size of micropores (typically <1 nm) in zeolites causes slow diffusion of reactant and product molecules in and out of the pores and negatively impacts the product selectivity of zeolite based catalysts, for example, fluid catalytic cracking (FCC) catalysts. Size-tailored mesoporosity was introduced into commercial zeolite Y crystals by a simple surfactant-templating post-synthetic mesostructuring process. The resulting mesoporous zeolite Y showed significantly improved product selectivity in both laboratory testing and refinery trials. Advanced characterization techniques such as electron tomography, three-dimensional rotation electron diffraction, and high resolution gas adsorption coupled with hysteresis scanning and density functional theory, unambiguously revealed the intracystalline nature and connectivity of the introduced mesopores. They can be considered as molecular highways that help reactant and product molecules diffuse quickly to and away from the catalytically active sites within the zeolite crystals and, thus, shift the selectivity to favor the production of more of the valuable liquid fuels at reduced yields of coke and unconverted feed.