Titulo Estágio
Development of Support Vector Machines (SVMs) in Graphics Processing Units for Object Recognition
Área Tecnológica
Reconhecimento de Padrões
Local do Estágio
LARN - Laboratório de Redes Neuronais
Enquadramento
The graphics processing unit (GPU) has become an integral part of today's mainstream computing systems. GPUs are optimized to perform floating-point operations in parallel on large data sets using the paradigm Single Instruction Multiple Data (SIMD). This is extremely important for machine learning algorithms (such as Support Vector Machines (SVMs), neural networks, etc.) which are often complex, placing high demands on memory and computing resources.
However, this architectural difference (between both platforms) leads to more complex programming tasks. To simplify this task, NVIDIA developed CUDA (Compute United Device Architecture) which provides an architecture and a programming model for developing general purpose applications on the GPU (GPGPU) using C/C++, extended with keywords that designate data-parallel functions.
Objetivo
In this context, the goal of this thesis is to design, develop and implement a component to integrate/support GPUMLib (http://gpumlib.sourceforge.net/) - an open source Graphic Processing Unit Machine Learning Library - which aims to provide users with a Library of machine learning tools taking advantage of their fast implementation in the GPUs. More specifically, the component to be developed includes the implementation, test and experimentation. Tests will be held in an object recognition problem in order to compare both the performances in the GPU and in an SVM standalone CPU version.
Plano de Trabalhos - Semestre 1
1) Introduction to CUDA,
2) Review of the state-of-the-art
3) Analysis and Specification of SVMs in the GPUMlib
4) Proposal Thesis Writing
Plano de Trabalhos - Semestre 2
3)Development and integration of the software component in GPUMLib
4)Tests and Experimentation on images databases
5)Thesis Report
Condições
The work will be in the Department of Informatics Engineering, in the Adaptive Systems Group, Laboratory of Neural Networks (LARN) at the Center for Informatics and Systems of the University of Coimbra. No grant available for this internship.
Internship Proposal – Edition 2011/2012
MEI- Mestrado em Eng. Informática – DEI/FCTUC
Orientador
Bernardete Ribeiro
bribeiro@dei.uc.pt 📩