Processing Neocognitron of Face Recognition on High Performance Environment Based on GPU with CUDA Architecture

This work presents an implementation of Neocognitron Neural Network, using a high performance computing architecture based on GPU (Graphics Processing Unit). Neocognitron is an artificial neural network, proposed by Fukushima and collaborators, constituted of several hierarchical stages of neuron layers, organized in twodimensional matrices called cellular planes. For the high performance computation of Face Recognition application using Neocognitron it was used CUDA (Compute Unified Device Architecture) as API (Application Programming Interface) between the CPU and the GPU, from GeForce 8800 GTX of NVIDIA company, with 128 ALU’s. As face image databases it was used a face database created at UFSCar, and the CMU-PIE (Carnegie Mellon University Pose, Illumination and Expression) database. The load balancing was achieved through the use of cellular connections as threads organized in blocks, following the CUDA philosophy of development. The results showed the feasibility of this typ...

• Type: Conference
• Year: 2008
• Where: sbacpad
• Authors: Gustavo Poli, José Hiroki Saito, João F. Mari, Marcelo R. Zorzan
• Keywords: Computer Architecture, Hardware, Neocognitron Neural Network, Neural Network, Performance Computing Architecture, SBACPAD 2008