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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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04/12/2021
Software-Hardware Co-design for Fast and Scalable Training of Deep Learning Recommendation Models
Deep learning recommendation models (DLRMs) are used across many busines...
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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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01/13/2021
FBGEMM: Enabling High-Performance Low-Precision Deep Learning Inference
Deep learning models typically use single-precision (FP32) floating poin...
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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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05/31/2019
Deep Learning Recommendation Model for Personalization and Recommendation Systems
With the advent of deep learning, neural network-based recommendation mo...
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05/29/2019
A Study of BFLOAT16 for Deep Learning Training
This paper presents the first comprehensive empirical study demonstratin...
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08/24/2018
Implementing Strassen's Algorithm with CUTLASS on NVIDIA Volta GPUs
Conventional GPU implementations of Strassen's algorithm (Strassen) typi...
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04/11/2017
Strassen's Algorithm for Tensor Contraction
Tensor contraction (TC) is an important computational kernel widely used...
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11/03/2016
Generating Families of Practical Fast Matrix Multiplication Algorithms
Matrix multiplication (GEMM) is a core operation to numerous scientific ...
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09/01/2016
BLISlab: A Sandbox for Optimizing GEMM
Matrix-matrix multiplication is a fundamental operation of great importa...
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05/03/2016
