9 citations · 19 across the 5 of their papers we have counts for
5 papers
The MOMMS Family of Matrix Multiplication Algorithms
Tyler M. Smith, Robert A. van de Geijn
As the ratio between the rate of computation and rate with which data can be retrieved from various layers of memory continues to deteriorate, a question arises: Will the current b…
Supporting mixed-datatype matrix multiplication within the BLIS framework
Field G. Van Zee, Devangi N. Parikh, Robert A. van de Geijn
We approach the problem of implementing mixed-datatype support within the general matrix multiplication (GEMM) operation of the BLIS framework, whereby each matrix operand A, B, an…
A Case for Malleable Thread-Level Linear Algebra Libraries: The LU Factorization with Partial Pivoting
Sandra Catalán, José R. Herrero, Enrique S. Quintana-Ortí +2
We propose two novel techniques for overcoming load-imbalance encountered when implementing so-called look-ahead mechanisms in relevant dense matrix factorizations for the solution…
Generating Families of Practical Fast Matrix Multiplication Algorithms
Jianyu Huang, Leslie Rice, Devin A. Matthews +1
Matrix multiplication (GEMM) is a core operation to numerous scientific applications. Traditional implementations of Strassen-like fast matrix multiplication (FMM) algorithms often…
BLISlab: A Sandbox for Optimizing GEMM
Jianyu Huang, Robert A. van de Geijn
Matrix-matrix multiplication is a fundamental operation of great importance to scientific computing and, increasingly, machine learning. It is a simple enough concept to be introdu…