Adaptive Optimization in the Jalapeño JVM Matthew Arnold Stephen Fink David Grove Michael Hind Peter F. Sweeney Presentation by Michael Bond Talk overview Introduction: Background & Jalapeño JVM Adaptive Optimization System (AOS) Multi-level recompilation Miscellaneous issues
Peter F. Sweeney
Presentation by Michael Bond
“Distributed, asynchronous, object-oriented design” useful for managing lots of data, say authors
Each successive pipeline (from raw data to compilation decisions) performs increasingly complex analysis on decreasing amounts of dataAOS: Design
Code with no method calls or back edges
Ti = Tf * Pm
Pm estimated from sampling
Tj = Ti * Si / Sj
Cj = aj * size(m), where aj = constant for level j
You’re so useful for managing lots of data, say authorshot!
Adaptively optimize me all night long!