GraphLab

Turi
Developer(s)Carnegie Mellon University
Stable release
v2.2 / July 1, 2013 (2013-07-01)
Written inC++
Operating systemLinux, macOS
TypeMachine learning platform
LicenseProprietary
Websiteturi.com

Turi is a graph-based, high performance, distributed computation framework written in C++. The GraphLab project was started by Prof. Carlos Guestrin of Carnegie Mellon University in 2009. It is an open source project that uses the Apache License. While GraphLab was originally developed for machine learning tasks, it has also been developed for other data-mining tasks.[1][2]

Motivation

As the amounts of collected data and computing power grow (multicore, GPUs, clusters, clouds), modern datasets no longer fit into one computing node. Efficient distributed parallel algorithms for handling large-scale data are required. The GraphLab framework is a parallel programming abstraction targeted for sparse iterative graph algorithms. GraphLab provides a programming interface, allowing deployment of distributed machine learning algorithms.[3] The main design considerations behind the design of GraphLab are:

  • Sparse data with local dependencies
  • Iterative algorithms
  • Potentially asynchronous execution

GraphLab toolkits

On top of GraphLab, several implemented libraries of algorithms:

Turi

Turi (formerly called Dato and before that GraphLab Inc.) is a company that was founded by Prof. Carlos Guestrin from University of Washington in May 2013 to continue development support of the GraphLab open source project. Dato Inc. raised a $6.75M Series A from Madrona Venture Group and New Enterprise Associates (NEA). They raised a $18.5M Series B from Vulcan Capital and Opus Capital, with participation from Madrona and NEA.[10] On August 5, 2016, Turi was acquired by Apple Inc. for $200,000,000.[11][12]

References

  1. ^ Joseph Gonzalez, Yucheng Low, Haijie Gu, Danny Bickson, Carlos Guestrin (2012). "PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs." Proceedings of Operating Systems Design and Implementation (OSDI).
  2. ^ Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin and Joseph M. Hellerstein (2012). "Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud." Proceedings of Very Large Data Bases (PVLDB).
  3. ^ Y. Low, J. Gonzalez, A. Kyrola, D. Bickson, C. Guestrin and J. Hellerstein. GraphLab: A New Framework for Parallel Machine Learning. In the 26th Conference on Uncertainty in Artificial Intelligence (UAI), Catalina Island, USA, 2010
  4. ^ "GraphLab: Distributed Graph-Parallel API: Topic Modeling". Archived from the original on 2013-06-04. Retrieved 2013-05-14.
  5. ^ "GraphLab: Distributed Graph-Parallel API: Graph Analytics". Archived from the original on 2013-02-18. Retrieved 2013-05-14.
  6. ^ "GraphLab Clustering Library". Archived from the original on 2016-12-21. Retrieved 2016-12-01.
  7. ^ "GraphLab: Collaborative filtering library using matrix factorization methods". Archived from the original on 2016-12-20. Retrieved 2016-12-01.
  8. ^ "GraphLab: Distributed Graph-Parallel API: Graphical Models". Archived from the original on 2013-05-12. Retrieved 2013-05-14.
  9. ^ "GraphLab: Distributed Graph-Parallel API: Computer Vision". Archived from the original on 2013-01-23. Retrieved 2013-05-14.
  10. ^ Gage, Deborah (2015-01-08). "GraphLab, Now Dato, Raises $18.5M for Machine-Learning Applications". WSJ Blogs. Retrieved 2018-04-11.
  11. ^ Clover, Juli. "Apple Acquires Machine Learning and AI Startup Turi". Retrieved 2016-08-06.
  12. ^ "Exclusive: Apple acquires Turi in major exit for Seattle-based machine learning and AI startup". 2016-08-05. Retrieved 2016-08-06.