Efficient Profiling of Actor-based Applications in Parallel and Distributed Systems
Applications employing the actor model of concurrent computation are becoming popular nowadays. On the one hand, the foundational characteristics of the actor model make it attractive in parallel and distributed settings. On the other hand, effective investigation of poor performance in actor-based applications requires dedicated metrics and profiling methods. Unfortunately, little research has been conducted on this topic to date, and developers are forced to investigate suboptimal performance with general-purpose profilers that fall short in locating scalability bottlenecks and performance inefficiencies. This position paper advocates the need for dedicated profiling techniques and tools for actor-based applications, focusing specifically on inter-actor communication and actor utilization. Our preliminary results support the importance of dedicated actor profiling and motivate further research on this topic.
Preprint (icooolps-final7.pdf) | 125KiB |
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16:00 - 16:30 Talk | TruffleReloader: A Low-Overhead Language-Neutral Reloader ICOOOLPS Tõnis PoolZeroTurnaround / University of Tartu, Allan Raundahl GregersenZeroTurnaround, Vesal VojdaniUniversity of Tartu Media Attached File Attached | ||
16:30 - 17:00 Talk | Sulong - Execution of LLVM-Based Languages on the JVM ICOOOLPS Manuel RiggerJohannes Kepler University, Linz, Austria, Matthias GrimmerJohannes Kepler University Linz, Hanspeter MössenböckJohannes Kepler University Linz Media Attached File Attached | ||
17:00 - 17:30 Talk | Efficient Profiling of Actor-based Applications in Parallel and Distributed Systems ICOOOLPS Andrea RosàUniversità della Svizzera italiana, Lydia Y. ChenIBM Research Lab Zurich, Walter BinderUniversity of Lugano Media Attached File Attached |