Scalable Correct Memory Ordering via Relativistic Programming

We propose and document a new concurrent programming model, relativistic programming. This model allows readers to run concurrently with writers, without blocking or using expensive synchronization. Relativistic programming builds on existing synchronization primitives that allow writers to wait for current readers to finish with minimal reader overhead. Our methodology models data structures as graphs, and reader algorithms as traversals of these graphs; from this foundation we show how writers can implement arbitrarily strong ordering guarantees for the visibility of their writes, up to and including total ordering.