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Elektron is a lightweight, power-aware, pluggable Mesos framework that behaves as a playground to experiment with different scheduling policies to schedule ad-hoc jobs in docker containers.

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Pradyumna Kaushik 1c4b6f0f01 refined README and removed unwanted scheduling policies.		2017-09-26 00:05:19 -04:00
constants	Removed the hardcoded nodes and their powerclasses from the PowerClasses map as now it will populated dynamically	2017-03-24 16:25:24 -04:00
def	formatted files	2017-08-26 22:33:06 -04:00
pcp	Got rid of commented code	2017-03-24 17:28:53 -04:00
powerCapping	Changed the loop as the Hosts is now a map and not a list and now looping over the keys is required.	2017-03-23 22:03:03 -04:00
rapl	changed the type of percentage in rapl.Cap(...) from int to float64. Retrofitted power-capping strategies to cap using a float64 value instead of an int. Moved common functions in loganddynamiccap.go and logAndProgressiveExtrema.go into pcp/utils.go. New power-capping strategy that builds on top of extrema, where it caps the victims at different until it can't cap further, in which case it starts uncapping them in the reverse order of capping.	2017-02-15 19:22:56 -05:00
schedulers	refined README and removed unwanted scheduling policies.	2017-09-26 00:05:19 -04:00
utilities	Removed the import statement which was importing offerUtils from electron-archive. This results in build failure is electron-archive is a local package	2017-03-25 21:11:24 -04:00
config	basic configuration for pcp	2016-12-22 22:58:58 -05:00
README.md	refined README and removed unwanted scheduling policies.	2017-09-26 00:05:19 -04:00
scheduler.go	fixed indentation	2017-08-22 12:56:36 -04:00
workload_sample.json	Adding node class mapping for Watts as a resource in binpack	2016-12-23 21:04:15 -05:00

README.md

Elektron: A Pluggable Mesos framework with power-aware capabilities

Elektron is a Mesos framework that behaves as a playground for developers to experiment with different scheduling policies to launch ad-hoc jobs. Elektron is designed as a lightweight, configurable framework, which can be used in conjunction with built-in power-capping policies to reduce the peak power and/or energy usage of co-scheduled tasks.

#Features

Pluggable Scheduling policies
Pluggable Power-Capping strategies
Cluster resource monitoring