9 citations · 22 across the 6 of their papers we have counts for
6 papers
GPUNet: Searching the Deployable Convolution Neural Networks for GPUs
Linnan Wang, Chenhan Yu, Satish Salian +3
Customizing Convolution Neural Networks (CNN) for production use has been a challenging task for DL practitioners. This paper intends to expedite the model customization with a mod…
Fast Approximation of the Gauss-Newton Hessian Matrix for the Multilayer Perceptron
Chao Chen, Severin Reiz, Chenhan Yu +2
We introduce a fast algorithm for entry-wise evaluation of the Gauss-Newton Hessian (GNH) matrix for the fully-connected feed-forward neural network. The algorithm has a precomputa…
Implementing Strassen's Algorithm with CUTLASS on NVIDIA Volta GPUs
Jianyu Huang, Chenhan D. Yu, Robert A. van de Geijn
Conventional GPU implementations of Strassen's algorithm (Strassen) typically rely on the existing high-performance matrix multiplication (GEMM), trading space for time. As a resul…
Geometry-Oblivious FMM for Compressing Dense SPD Matrices
Chenhan D. Yu, James Levitt, Severin Reiz +1
We present GOFMM (geometry-oblivious FMM), a novel method that creates a hierarchical low-rank approximation, "compression," of an arbitrary dense symmetric positive definite (SPD)…
An Parallel Fast Direct Solver for Kernel Matrices
Chenhan D. Yu, William B. March, George Biros
Kernel matrices appear in machine learning and non-parametric statistics. Given points in dimensions and a kernel function that requires work to evaluate,…
Inv-ASKIT: A Parallel Fast Diret Solver for Kernel Matrices
Chenhan D. Yu, William B. March, Bo Xiao +1
We present a parallel algorithm for computing the approximate factorization of an -by- kernel matrix. Once this factorization has been constructed (with work),…