Performance tuning used to be a tedious task. Project ASCAR seeks to do automated performance tuning using machine learning.
The Pilot Framework
Pilot is a framework that is designed for collecting precise benchmark results in the shortest possible time. This is useful when a designer or administrator needs to evaluate many candidate parameters. Pilot analyzes time series data in real time and tells you when the desired width of confidence interval is reached. Pilot can also automate many benchmark chores, such as measuring the overhead, detecting warm-up and tear-down phases, discovering bottleneck of the system, and comparing very close benchmark results. It comes with an easy-to-use scriptable interface with C/C++/Python bindings.
We will begin a closed alpha test in late June, 2016, and plan to make the first public release in or before September, 2016. Join the mailing list to receive future release announcements: