Fri 30 Oct 2015 14:15 - 14:37 at Grand Station 2 - 12. Performance Chair(s): Tiark Rompf

Efficient mapping of message passing concurrency (MPC) abstractions to Java Virtual Machine (JVM) threads is critical for performance, scalability, and CPU utilization; but tedious and time consuming to perform manually. In general, this mapping cannot be found in polynomial time, but we show that by exploiting the local characteristics of MPC abstractions and their communication patterns this mapping can be determined effectively. We describe our MPC abstraction to thread mapping technique, its realization in two frame- works (Panini and Akka), and its rigorous evaluation using several benchmarks from representative MPC frameworks. We also compare our technique against four default mapping techniques: thread-all, round-robin-task-all, random-task-all and work-stealing. Our evaluation shows that our mapping technique can improve the performance by 30%-60% over default mapping techniques. These improvements are due to a number of challenges addressed by our technique namely: i) balancing the computations across JVM threads, ii) reducing the communication overheads, iii) utilizing information about cache locality, and iv) mapping MPC abstractions to threads in a way that reduces the contention between JVM threads.

Fri 30 Oct

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13:30 - 15:00
12. PerformanceOOPSLA at Grand Station 2
Chair(s): Tiark Rompf Purdue & Oracle Labs
13:30
22m
Talk
Automating Ad-hoc Data Representation TransformationsOOPSLA Artifact
OOPSLA
Vlad Ureche EPFL, Switzerland, Aggelos Biboudis University of Athens, Yannis Smaragdakis University of Athens, Martin Odersky EPFL, Switzerland
Pre-print Media Attached
13:52
22m
Talk
Tracing vs. Partial Evaluation: Comparing Meta-compilation Approaches for Self-Optimizing InterpretersOOPSLA Artifact
OOPSLA
Stefan Marr INRIA, France, St├ęphane Ducasse INRIA, France
Link to publication Media Attached
14:15
22m
Talk
Effectively Mapping Linguistic Abstractions for Message-Passing Concurrency to Threads on the Java Virtual Machine
OOPSLA
Ganesha Upadhyaya Iowa State University, USA, Hridesh Rajan Iowa State University, USA
DOI Pre-print Media Attached
14:37
22m
Talk
Partial Evaluation of Machine Code
OOPSLA
Venkatesh Srinivasan University of Wisconsin-Madison, USA, Thomas Reps University of Wisconsin - Madison and Grammatech Inc.
DOI Media Attached