Regions are a means of combining many objects into a single unit of memory allocation. As a form of memory management, they provide many of the efficiency benefits of stack allocation, yet regions also provide more flexibility for objects that outlive their stack frame. Although conceptually simple, regions have proven useful in a variety of applications. The Apache web server uses regions to amortize the cost of deallocation for large data structures. Regions have been used in ML to statically place allocation and deallocation points and avoid the need for a tracing garbage collector. Cyclone uses regions to eliminate dangling pointer references.

In my talk, I will provide a brief overview of region-based memory management, including approaches to region influence. I will discuss how different projects have used regions to achieve their goals. Finally, I will provide some speculation on how regions might be used to support richer data structures and efficient memory movement for GPU computing in Harlan.