Stochastic gradient descent without full data shuffle: with applications to in-database machine learning and deep learning systems

Article

HexGen: Generative Inference of Large-Scale Foundation Model over Heterogeneous Decentralized Environment

Conference paper

Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training

Conference paper

Serving Deep Learning Models from Relational Databases

Conference paper

Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning

Conference paper

CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks

Conference paper

Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time

Conference paper

High-throughput Generative Inference of Large Language Models with a Single GPU

Conference paper

Decentralized Training of Foundation Models in Heterogeneous Environments

Conference paper

Distributed Learning of Fully Connected Neural Networks using Independent Subnet Training

Conference paper

Efficient flow scheduling in distributed deep learning training with echelon formation

Conference paper

Fine-tuning Language Models over Slow Networks using Activation Quantization with Guarantees

Conference paper

In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle

Conference paper

Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters

Conference paper

Distributed numerical and machine learning computations via two-phase execution of aggregated join trees

Article

Automatic Optimization of Matrix Implementations for Distributed Machine Learning and Linear Algebra

Conference paper

BAGUA: Scaling up Distributed Learning with System Relaxations

Conference paper

Lachesis: automatic partitioning for UDF-centric analytics

Conference paper

Tensor relational algebra for distributed machine learning system design

Conference paper

Declarative Recursive Computation on an RDBMS: or, Why You Should Use a Database For Distributed Machine Learning

Article

Declarative Recursive Computation on an RDBMS or, Why You Should Use a Database For Distributed Machine Learning

Conference paper

PlinyCompute: A platform for high-performance, distributed, data-intensive tool development

Conference paper

Abridging source code

Article

Effective video retargeting with jittery assessment

Article