Department of Information Technology

Synchronization Modeling

Motivation

Synchronization is an indispensable part of parallel programs. Understanding the influence of synchronization is important for understanding the scalability of parallel programs.
For instance, locks are often necessary for protecting shared data, but they introduce lock contention, which causes performance issues. It would be desirable to have techniques that can assess how much a program would suffer from lock contention on aamulti-core systems. It would be even better if such assessment could be performed, based on information obtainable from profiling a run on a single core. If lock contention is shown to be a performance bottleneck, one of the ways to mitigate it is to use another lock implementation. Similarly, it would be desirable to have techniques for estimating cache performance under different cache configurations, given by cache size, associativity and replacement policy.

Approach

We develop techniques to answer what-if questions about performance via performance modeling. In performance modeling, the behavior of the software on some platform is represented by a model, which describes key features of this behavior at some level of abstraction. Thereafter, the model is instantiated with parameters of the software, usually obtained via observation or measurement.

In this project, we develop models that on the one hand can be analyzed to estimate performance for a range of platform configurations, and on the other hand can be constructed by low-cost software profiling on any available platform. We focus on two essential aspects of multi-core performance: cache performance and synchronization cost

We also develop techniques for efficient synchronization in parallel programs running on multicores. We focus on parallel discrete event simulation (PDES), which is a particularly challenging application, when it comes to parallelization. In collaboration with the Parallel Algorithms project in UPMARC, we realize these techniques to build an efficient simulator for spatial stochastic simulation.

Collaboration

Publications

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Funding

This project is funded by SSF (the Swedish Foundation for Strategic Research) as part of the project CoDeR-MP

Updated  2016-10-25 18:24:39 by Bengt Jonsson.