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HyPR: Hybrid Page Ranking on Evolving Graphs : NOTES

Highlighted notes on:
A Parallel Algorithm Template for Updating Single-Source Shortest Paths in Large-Scale Dynamic Networks.
While doing research work with Prof. Dip Sankar Banerjee, Prof, Kishore Kothapalli.

In Hybrid Pagerank the vertices are divided in 3 groups, V_old, V_border, V_new. Scaling for old, border vertices is N/N_new, and 1/N_new for V_new (i do this too ). Then PR is run only on V_border, V_new.

"V_border which is the set of nodes which have edges in Bi connecting V_old and V_new and is reachable using a breadth first traversal." Does that mean V_border = V_batch(i) ∩ V_old? BFS from where?

"We can assume that the new batch of updates is topologically sorted since the PR scores of the new nodes in Bi is guaranteed to be lower than those in Co." Is sum(PR) in V_old > sum(PR) in V_new always?

"For performing the comparisons with GPMA and GPMA+, we configure the experiment to run HyPR on the same platform as used in [1] which is a Intel Xeon CPU connected to a Titan X Pascal GPU, and also the same datasets." Old GPUs are going to be slower ...

Like we were discussing last time, it is not possible to scale old ranks, and skip the unchanged components (or here V_old). Please check this simple counter example that shows skipping leads to incorrect ranks. https://github.com/puzzlef/pagerank-levelwise-skip-unchanged-components

Another omission in the paper is that Hybrid PR (just like STICD) wont work for graphs which have dead ends. This is a pre-condition for the algorithm.

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