SEARCH
ISTC-CC NEWSLETTER
RESEARCH HIGHLIGHTS
Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
ISTC-CC provides a listing of useful benchmarks for cloud computing.
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.
ISTC-CC Abstract
Small Cache, Big Effect: Provable Load Balancing for
Randomly Partitioned Cluster Services
Proceedings of the ACM Symposium on Cloud Computing (SOCC'11), Cascais, Portugal, October 2011.
Bin Fan, Hyeontaek Lim, David G. Andersen, Michael Kaminsky*
Carnegie Mellon University
*Intel Labs
Load balancing requests across a cluster of back-end servers is critical for avoiding performance bottlenecks and meeting servicelevel objectives (SLOs) in large-scale cloud computing services. This paper shows how a small, fast popularity-based front-end cache can ensure load balancing for an important class of such services; furthermore, we prove an O(n log n) lower-bound on the necessary cache size and show that this size depends only on the total number of back-end nodes n, not the number of items stored in the system. We validate our analysis through simulation and empirical results running a key-value storage system on an 85-node cluster.
FULL PAPER: pdf
