Code to run experiments for Euro-Par 2018 paper: Global-Local View: Scalable Consistency for Concurrent Data Types

This dataset contains the source code that is used for the evaluation described in the Euro-Par 2018 conference paper entitled "Global-Local View: Scalable Consistency for<br>Concurrent Data Types". <div><br></div><div>The paper describes a model to leverage existing patterns for concurrent access to objects in a shared memory system. In this model, each thread maintains different views on the shared object: a thread-local view and a global view. As the thread-local view is not shared, it can be updated without incurring synchronization costs. These local updates become visible to other threads only after the thread-local view is merged with the global view.</div><div><div>Several data types are evaluated for performance and scalability compared to linearizable implementations.</div><div><br></div><div>The code is provided in two folders:</div><div>csrc/ has the source code of the experiments for mergeable counter in C++.</div><div>javasrc/ has the source code of the experiments for other data types in Java.</div><div><br></div><div>The files are in .java. SH, . R, and .PLOT formats. Images of the plots which are included in the accompanying paper are also included in .PNG format. </div><div><br></div><div>A PDF README file is included which provides instructions on how to compile, run and plot the experiments described in the accompanying paper, using a multi-core processor with at least 8 cores.</div></div>