TagsArticle Source
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, deep learning, search, and sorting.
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 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
Hong Kong University of Science and Technology
Where GPUs are deployed
