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GPU Applications

Data Science

A growing number of data scientists are using GPUs for big data analytics to make better, real-time business decisions. This page highlights customer use cases and their techniques in big data analytics, such as machine learning, search, and sorting.

 
 
10x SPEED-UP ON IMAGE DETECTION USING NEURAL NETWORKS

10x SPEED-UP ON IMAGE DETECTION USING NEURAL NETWORKS
Dr. Dan Ciresan, Swiss Al Lab IDSIA, Switzerland

WORLD'S LARGEST ARTIFICIAL NEURAL NETWORKS WITH GPUS

WORLD'S LARGEST ARTIFICIAL NEURAL NETWORKS WITH GPUS
Adam Cotes et al Sanford Al Lab, U.S.A. – LEARN MORE

 
 
 

For information on key data science applications, please visit the GPU Applications page.

 
ARTICLES
> DataInformed: Fast Database Emerges from MIT Class, GPUs and Student's Invention
> Press Release: NVIDIA GPUs, Big-Data Analytics And Search, Shazam, Salesforce, Cortexica
> Blog: IDSIA, How bio-inspired deep learning keeps winning competitions
 
 
TECHNICAL REPORTS AND TALKS ON DATA SCIENCE

Data Mining & Analytics

> GPU-accelerated Keyword Matching and Expression Evaluation for Real-time Text Search, Brenden Wood, Salesforce.com
> Building Accelerated DSLs and GPU Compilers with libNVVM, Yuan Lin, NVIDIA
> GPU-Accelerated Large Scale Analytics, Ren Wu, HP Laboratories
> Exploiting Graphic Card Processor Technology to Accelerate Data Mining in SAP NetWeaver BIA, Christoph Weyerhaeuser, SAP

Search & Sorting

> Efficient Parallel Lists Intersection and Index Compression Algorithms using GPU, Naiyong Ao, Baidu-Naikai Joint Lab
> Scalable GPU Graph Traversal, Duane Merrill, NVIDIA
> Efficient Sorting Algorithms for Manycore GPUs, Nadathur Satish, UC Berkeley
> A Fast, Flexible Sorting Algorithm with CUDA, Shifu Chen
> Sorting using BItonic network wIth CUDA, Ranieri Baraglia, ISTI-CNR

Databases

> Video: Red Fox: An Execution Environment for Relational Query Processing on GPUs, Haicheng Wu, Georgia Institute of Technology
> Video: Histograms in CUDA: privatized for Fast, Level Performance, Nicholas Wilt, Amazon
> Video: Packet-based Network Traffic Monitoring & Analysis with GPUs, Wenji Wu, Fermilab
> Video: Real-Time Quantification Filters for Multidimensional Databases, Peter Strohm, Jedox AG
> Video: Parallel Lossless Compression Using GPUs, Eva Sitaridi, Columbia University
> Video: GPUs and Regular Expression Matching for Big Data Analytics, Alon Housfater, IBM
> Video: Indexing Documents on GPU – Can You Index Web in Real-Time, Michael Frumkin, NVIDIA
> Video: Evaluation of Parallel Hashing Techniques, Rajesh Bordawekar, IBM T.J. Watson Research Center
> Video: A High Level API for Fast Development of High Performance Graphic Analytics on GPUs, Zhisong Fu, SYSTAP
> Video: Getting Big Data Done On a GPU-Based Database, Netzer, SQream Technologies
> Video: Parallel Decomposition Strategies in Modern GPU, Sean Baxter, NVIDIA
> Video: Map-D: A GPU Database for Real-time Big Data Analytics and Interactive Visualization, Thomas Graham, Map-D

Map-Reduce / Hadoop

> Whitepaper: Multi-GPU MapReduce on GPU Clusters, Jeff Stuart, UC. Davis
> Whitepaper: Pipelined Multi-GPU MapReduce for Big-Data Processing, Yi Chen 
> Whitepaper: Optimizing Map Reduce for GPUs with Effective Shared Memory, Linchuan Chen
> Whitepaper: A Map-Reduce Based Framework for Heterogeneous Processing Element Cluster Environments, Yu Shyang Tan
 
 
Where GPU Research happens
Georgia Tech

Georgia Tech

Hong Kong University of Science and Technology

Hong Kong University of Science and Technology

IDSIA

IDSIA

Nankai University

Nankai University

New York University

New York University

Ohio State University

Ohio State University

Stanford

Stanford

University of Michigan

University of Michigan

University of Montreal

University of Montreal

University of Toronto

University of Toronto

Virginia Tech

Virginia Tech

 
 
 
Where GPUs are deployed
Baidu

Baidu

Cortexica

Cortexica

Jedox

Jedox

Nuance

Nuance

Onuma

Onuma

Salesforce

Salesforce

Shazam

Shazam

Yandex

Yandex

 
 
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