5 papers
Accurate Models of NVIDIA Tensor Cores
Faizan A. Khattak, Mantas Mikaitis
Matrix multiplication is a fundamental operation in both training of neural networks and inference. To accelerate matrix multiplication, Graphical Processing Units (GPUs) provide i…
Decoupled Azimuth Elevation AoA Estimation Exploiting Kronecker Separable Steering Matrices
Faizan A. Khattak, Ian K. Proudler, Stephan Weiss +1
Uniform rectangular arrays (URA), structured non-uniform rectangular arrays (NURA), and parallelogram shaped (UPgA and NUPgA) arrays admit steering vectors that can be expressed as…
Generalized Methodology for Determining Numerical Features of Hardware Floating-Point Matrix Multipliers: Part I
Faizan A Khattak, Mantas Mikaitis
Numerical features of matrix multiplier hardware units in NVIDIA and AMD data centre GPUs have recently been studied. Features such as rounding, normalisation, and internal precisi…
Least-Squares Khatri-Rao Factorization of a Polynomial Matrix
Faizan A. Khattak, Fazal-E-Asim, Stephan Weiss +1
The Khatri-Rao product is extensively used in array processing, tensor decomposition, and multi-way data analysis. Many applications require a least-squares (LS) Khatri-Rao factori…
Impact of Estimation Errors of a Matrix of Transfer Functions onto Its Analytic Singular Values and Their Potential Algorithmic Extraction
Mohammed Bakhit, Faizan A. Khattak, Ian K. Proudler +1
A matrix of analytic functions A(z), such as the matrix of transfer functions in a multiple-input multiple-output (MIMO) system, generally admits an analytic singular value decompo…