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
Automated Diagnosis without Predictability is a Recipe for Failure
Proceedings of the 4th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud '12), June 12-13, 2012, Boston, MA.
Raja R. Sambasivan & Gregory R. Ganger
Carnegie Mellon University
Automated management is critical to the success of cloud computing, given its scale and complexity. But, most systems do not satisfy one of the key properties required for automation: predictability, which in turn relies upon low variance. Most automation tools are not ešective when variance is consistently high. Using automated performance diagnosis as a concrete example, this position paper argues that for automation to become a reality, system builders must treat variance as an important metric and make conscious decisions about where to reduce it. To help with this task, we describe a framework for reasoning about sources of variance in distributed systems and describe an example tool for helping identify them.
FULL PAPER: pdf
