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synchronously (e.g., greedy graph coloring) or converge way faster when executed
asynchronously (e.g., dynamic PageRank), GraphLab becomes a superior option as
opposed to Pregel. Finally, for graph and iterative oriented applications that converge
faster if serializability (which entails that for every parallel/distributed execution,
there is an equivalent sequential execution) is ensured or even necessitate serializ-
ability for correctness (e.g., Gibbs sampling, a very common algorithm in machine
learning and data mining problems), GraphLab remains a supreme alternative vs.
Pregel.
REFERENCES
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