Καλησπέρα σε όλους,
On 24/01/2018 05:41 μμ, Giagkos
Mytilinis wrote:
Νίκο,
αν θες, στείλε στη λίστα title/abstract σχετικά με την παρουσίαση
που ετοιμάζεις.
Ευχαριστώ για την πάσα Γιάγκο!
Έχω ετοιμάσει για την Παρασκευή το "CherryPick: Adaptively
Unearthing the Best Cloud Configurations for Big Data Analytics"
των Alipourfard, Liu, Chen, Venkataraman, Yu, Zhang.
Παρουσιάστηκε στο NSDI 2017.
Abstract:
Picking the right cloud configuration for recurring big data
analytics jobs running in clouds is hard, because there can be
tens of possible VM instance types and even more cluster sizes to
pick from. Choosing poorly can significantly degrade performance and
increase the cost to run a job by 2-3x on average, and as much as
12x in the worst-case. However, it is challenging to automatically
identify the best configuration for a broad spectrum of applications
and cloud configurations with low search cost. CherryPick is a
system that leverages Bayesian Optimization to build performance
models for various applications, and the models are just accurate
enough to distinguish the best or close-to-the-best configuration
from the rest with only a few test runs. Our experiments on five
analytic applications in AWS EC2 show that CherryPick has a 45-90%
chance to find optimal configurations, otherwise near-optimal,
saving up to 75% search cost compared to existing solutions.
N.