GPUMLib  0.2.2
GPU Machine Learning Library
Class Hierarchy
This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 12]
 CArgumentThis class acts like a placeholder for an argument, composed of a parameter and a attribute/value
 CBackPropagationRepresents a feed-forward network that can be trained using the CUDA implementation of the Back-Propagation algorithm
 CMultipleBackPropagationRepresents a multiple feed-forward network that can be trained using the CUDA implementation of the Multiple Back-Propagation algorithm
 CBaseArray< Type >Base class for HostArray and DeviceArray classes (Array base class)
 CDeviceArray< cudafloat * >
 CDeviceArray< int >
 CDeviceArray< Type >Create an array of any type, on the device, that automatically manages the memory used to hold its elements
 CHostArray< Type >Create an array of any type, on the host, that automatically manages the memory used to hold its elements
 CBaseArray< bool >
 CHostArray< bool >
 CBaseArray< cudafloat >
 CDeviceArray< cudafloat >
 CHostArray< cudafloat >
 CBaseArray< float >
 CDeviceArray< float >
 CHostArray< float >
 CBaseArray< GPUMLib::RBM * >
 CHostArray< GPUMLib::RBM * >
 CBaseArray< GPUMLib::RBMhost * >
 CHostArray< GPUMLib::RBMhost * >
 CBaseArray< Layer >
 CHostArray< Layer >
 CBaseMatrix< Type >Base class for HostMatrix and DeviceMatrix classes (Matrix base class)
 CDeviceMatrix< Type >Create a matrix of any type, on the device, that automatically manages the memory used to hold its elements
 CHostMatrix< Type >Create a matrix of any type, on the host, that automatically manages the memory used to hold its elements
 CBaseMatrix< cudafloat >
 CDeviceMatrix< cudafloat >
 CHostMatrix< cudafloat >
 CBaseMatrix< float >
 CDeviceMatrix< float >
 CHostMatrix< float >
 CCudaArray< Type >Create an array of any type, that automatically manages the memory used to hold its elements (data will be stored both on the host and on the device)
 CCudaArray< cudafloat >
 CCudaMatrix< Type >Create a matrix of any type, that automatically manages the memory used to hold its elements (data will be stored both on the host and on the device)
 CCudaMatrix< cudafloat >
 CCudaStreamRepresents a CUDA stream
 CDBNRepresents a Deep Belief Network (Device - GPU)
 CDBNhostRepresents a Deep Belief Network (Host - CPU)
 CDeviceAccessibleVariable< Type >Represents a variable residing in memory that is page-locked and accessible to the device
 CDeviceAccessibleVariable< bool >
 CDeviceAccessibleVariable< cudafloat >
 CDeviceAccessibleVariable< float >
 CDeviceAccessibleVariable< int >
 CKMeansRepresents a clustering algorithm using the K-Means technique, implemented in CUDA
 CNMFBase class for all Non-Negative Matrix Factorization classes
 CNMF_AdditiveDivergenceRepresents a Non-Negative Matrix Factorization (NMF) algorithm that uses additive update rules and the (Kullback-Leibler) divergence metric
 CNMF_AdditiveEuclidianRepresents a Non-Negative Matrix Factorization (NMF) algorithm that uses additive update rules and the Euclidean distance metric
 CNMF_MultiplicativeDivergenceRepresents a Non-Negative Matrix Factorization (NMF) algorithm that uses multiplicative update rules and the (Kullback-Leibler) divergence metric
 CNMF_MultiplicativeEuclidianDistanceRepresents a Non-Negative Matrix Factorization (NMF) algorithm that uses multiplicative update rules and the Euclidean distance metric
 CRadialBasisFunctionRepresents a radial basis function network that can be trained using the CUDA implementation of the Radial Basis Function algorithm
 CRandomClass for generating random values on the device. Uses the CURAND library
 CRBMRepresents a Restricted Boltzman Machine (GPU)
 CRBMhostRepresents a Restricted Boltzman Machine (Host - CPU)
 CReductionProvides reduction functions (Sum, Average, Max, Min, ...)
 CResourceAllocatingNetworkRepresents a resource allocating network with long term memory that can be trained using a CUDA implementation of the algorithm
 CSettingsUtility class to parse main()'s arguments, store them in a convenient list and access when needed
 CSVMRepresents an SVM which can be used to train and classify datasets on the GPU device