Evangelos Georganas

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Efficient and Generic 1D Dilated Convolution Layer for Deep Learning

Convolutional neural networks (CNNs) have found many applications in tas...
04/16/2021 ∙ by Narendra Chaudhary, et al. ∙ 0 ∙ share

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DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks

Full-batch training on Graph Neural Networks (GNN) to learn the structur...
04/14/2021 ∙ by Vasimuddin Md, et al. ∙ 29 ∙ share

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Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads

During the past decade, novel Deep Learning (DL) algorithms/workloads an...
04/12/2021 ∙ by Evangelos Georganas, et al. ∙ 11 ∙ share

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Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures

During the last two years, the goal of many researchers has been to sque...
05/10/2020 ∙ by Dhiraj Kalamkar, et al. ∙ 0 ∙ share

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The Parallelism Motifs of Genomic Data Analysis

Genomic data sets are growing dramatically as the cost of sequencing con...
01/20/2020 ∙ by Katherine Yelick, et al. ∙ 0 ∙ share

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High-Performance Deep Learning via a Single Building Block

Deep learning (DL) is one of the most prominent branches of machine lear...
06/15/2019 ∙ by Evangelos Georganas, et al. ∙ 9 ∙ share

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A Study of BFLOAT16 for Deep Learning Training

This paper presents the first comprehensive empirical study demonstratin...
05/29/2019 ∙ by Dhiraj Kalamkar, et al. ∙ 0 ∙ share

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ISA Mapper: A Compute and Hardware Agnostic Deep Learning Compiler

Domain specific accelerators present new challenges and opportunities fo...
10/12/2018 ∙ by Matthew Sotoudeh, et al. ∙ 0 ∙ share

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Extreme Scale De Novo Metagenome Assembly

Metagenome assembly is the process of transforming a set of short, overl...
09/19/2018 ∙ by Evangelos Georganas, et al. ∙ 0 ∙ share

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Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures

Convolution layers are prevalent in many classes of deep neural networks...
08/16/2018 ∙ by Evangelos Georganas, et al. ∙ 0 ∙ share

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Mixed Precision Training of Convolutional Neural Networks using Integer Operations

The state-of-the-art (SOTA) for mixed precision training is dominated by...
02/03/2018 ∙ by Dipankar Das, et al. ∙ 0 ∙ share

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