Abstract: Embodiments include computing devices, apparatus, and methods implemented by the apparatus for memory reduction for fixed point matrix multiply on a computing device. The computing device may implement a partial matrix multiplication using a first block of fixed point data of a first matrix and a second block of fixed point data of a second matrix using full precision resulting in a first intermediate result. The computing device may down convert the first intermediate result by converting fixed point data of the first intermediate result to fixed point data using lower precision resulting in a first down converted intermediate result.

Abstract: Embodiments include computing devices, apparatus, and methods implemented by the apparatus for memory reduction for fixed point matrix multiply on a computing device. The computing device may implement a partial matrix multiplication using a first block of fixed point data of a first matrix and a second block of fixed point data of a second matrix using full precision resulting in a first intermediate result. The computing device may down convert the first intermediate result by converting fixed point data of the first intermediate result to fixed point data using lower precision resulting in a first down converted intermediate result.

Abstract: Embodiments include computing devices, apparatus, and methods implemented by the apparatus for accelerating machine learning on a computing device. Raw data may be received in the computing device from a raw data source device. The apparatus may identify key features as two dimensional matrices of the raw data such that the key features are mutually exclusive from each other. The key features may be translated into key feature vectors. The computing device may generate a feature vector from at least one of the key feature vectors. The computing device may receive a first partial output resulting from an execution of a basic linear algebra subprogram (BLAS) operation using the feature vector and a weight factor. The first partial output may be combined with a plurality of partial outputs to produce an output matrix. Receiving the raw data on the computing device may include receiving streaming raw data.