2 citations · 3 across the 6 of their papers we have counts for
6 papers
A Proposed Framework for Advanced (Multi)Linear Infrastructure in Engineering and Science (FAMLIES)
Devin A. Matthews, Tze Meng Low, Margaret E. Myers +2
We leverage highly successful prior projects sponsored by multiple NSF grants and gifts from industry: the BLAS-like Library Instantiation Software (BLIS) and the libflame efforts…
Enabling Pivoting in the Formal Derivation of LU factorization
Robert van de Geijn, Margaret E. Myers, Devangi N. Parikh +2
The FLAME methodology for deriving linear algebra algorithms from specification, first introduced around 2000, has been successfully applied to a broad cross section of operations.…
Cascading GEMM: High Precision from Low Precision
Devangi N. Parikh, Robert A. van de Geijn, Greg M. Henry
This paper lays out insights and opportunities for implementing higher-precision matrix-matrix multiplication (GEMM) from (in terms of) lower-precision high-performance GEMM. The d…
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 Simple Methodology for Computing Families of Algorithms
Devangi N. Parikh, Margaret E. Myers, Richard Vuduc +1
Discovering "good" algorithms for an operation is often considered an art best left to experts. What if there is a simple methodology, an algorithm, for systematically deriving a f…
Deriving Correct High-Performance Algorithms
Devangi N. Parikh, Maggie E. Myers, Robert A. van de Geijn
Dijkstra observed that verifying correctness of a program is difficult and conjectured that derivation of a program hand-in-hand with its proof of correctness was the answer. We il…