activity
20182024
most citedFull Stack Optimization of Transformer Inference: a Survey

27 citations · 48 across the 6 of their papers we have counts for

collaborators

6 papers

cs.MS2024

Interface for Sparse Linear Algebra Operations

Ahmad Abdelfattah, Willow Ahrens, Hartwig Anzt +32

The standardization of an interface for dense linear algebra operations in the BLAS standard has enabled interoperability between different linear algebra libraries, thereby boosti…

cs.MS2023★ 1 cited

Tackling the Matrix Multiplication Micro-kernel Generation with Exo

Adrián Castelló, Julian Bellavita, Grace Dinh +2

The optimization of the matrix multiplication (or GEMM) has been a need during the last decades. This operation is considered the flagship of current linear algebra libraries such…

cs.CL2023★ 27 cited

Full Stack Optimization of Transformer Inference: a Survey

Sehoon Kim, Coleman Hooper, Thanakul Wattanawong +9

Recent advances in state-of-the-art DNN architecture design have been moving toward Transformer models. These models achieve superior accuracy across a wide range of applications.…

cs.DC2022★ 2 cited

Communication Bounds for Convolutional Neural Networks

Anthony Chen, James Demmel, Grace Dinh +2

Convolutional neural networks (CNNs) are important in a wide variety of machine learning tasks and applications, so optimizing their performance is essential. Moving words of data…

cs.DS2020

Communication-Optimal Tilings for Projective Nested Loops with Arbitrary Bounds

Grace Dinh, James Demmel

Reducing communication - either between levels of a memory hierarchy or between processors over a network - is a key component of performance optimization (in both time and energy)…

cs.DS2018★ 18 cited

Communication-Optimal Convolutional Neural Nets

James Demmel, Grace Dinh

Efficiently executing convolutional neural nets (CNNs) is important in many machine-learning tasks. Since the cost of moving a word of data, either between levels of a memory hiera…