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05/26/2021
Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale
Tremendous success of machine learning (ML) and the unabated growth in M...
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02/27/2021
Efficient Soft-Error Detection for Low-precision Deep Learning Recommendation Models
Soft error, namely silent corruption of signal or datum in a computer sy...
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10/21/2020
Mixed-Precision Embedding Using a Cache
In recommendation systems, practitioners observed that increase in the n...
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10/18/2020
Fast Distributed Training of Deep Neural Networks: Dynamic Communication Thresholding for Model and Data Parallelism
Data Parallelism (DP) and Model Parallelism (MP) are two common paradigm...
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04/12/2019
Leveraging the bfloat16 Artificial Intelligence Datatype For Higher-Precision Computations
In recent years fused-multiply-add (FMA) units with lower-precision mult...
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05/23/2018
Dictionary Learning by Dynamical Neural Networks
A dynamical neural network consists of a set of interconnected neurons t...
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02/15/2018
A Progressive Batching L-BFGS Method for Machine Learning
The standard L-BFGS method relies on gradient approximations that are no...
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05/15/2017
Sparse Coding by Spiking Neural Networks: Convergence Theory and Computational Results
In a spiking neural network (SNN), individual neurons operate autonomous...
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02/28/2017
Enabling Sparse Winograd Convolution by Native Pruning
Sparse methods and the use of Winograd convolutions are two orthogonal a...
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08/04/2016
