Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
Another list highlighting Open Source Software Releases.
Second GraphLab workshop should be even bigger than the first! GraphLab is a new programming framework for graph-style data analytics.
Scaling Up Clustered Network Appliances with ScaleBricks
ACM SIGCOMM Conference on Computer Communications (SIGCOMM 2015), London, United Kingdom, August 2015.
Dong Zhou, Bin Fan, Hyeontaek Lim, David G. Andersen, Michael Kaminsky†, Michael D. Mitzenmacher**, Ren Wang†, Ajaypal Singh‡
Carnegie Mellon University
† Intel Labs
** Harvard University
‡ Connectem, Inc.
This paper presents ScaleBricks, a new design for building scalable, clustered network appliances that must “pin” flow state to a specific handling node without being able to choose which node that should be. ScaleBricks applies a new, compact lookup structure to route packets directly to the appropriate handling node, without incurring the cost of multiple hops across the internal interconnect. Its lookup structure is many times smaller than the alternative approach of fully replicating a forwarding table onto all nodes. As a result, ScaleBricks is able to improve throughput and latency while simultaneously increasing the total number of flows that can be handled by such a cluster. This architecture is effective in practice: Used to optimize packet forwarding in an existing commercial LTE-to-Internet gateway, it increases the throughput of a four-node cluster by 23%, reduces latency by up to 10%, saves memory, and stores up to 5.7x more entries in the forwarding table.
FULL PAPER: pdf