Project Summary
A framework for large-scale machine learning and graph computation.
The GraphLab project started at Carnegie Mellon University in 2009 to develop a new parallel computation abstraction tailored to machine learning. GraphLab 1.0 presented our first shared memory design which, through the addition of several matrix factorization toolkits, started to grow a community of users.
In the last couple of years, we have focused our development effort on the distributed environment. In GraphLab 2.1, we completely redesign of the GraphLab 1 framework for the distributed environment. The implementation is distributed by design and a "shared-memory" execution is essentially running a distributed system on a cluster of a single machine
In a Nutshell, graphlab.org...
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took an estimated 25 years of effort (COCOMO model)
starting with its first commit in August, 2010
ending with its most recent commit almost 8 years ago
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30 Day SummaryMar 24 2024 — Apr 23 2024
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12 Month SummaryApr 23 2023 — Apr 23 2024
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