Memory management for high-performance applications

textMemory managers are a source of performance and robustness problems for application software. Current general-purpose memory managers do not scale on multiprocessors, cause false sharing of heap objects, and systematically leak memory. Even on uniprocessors, the memory manager is often a performance bottleneck. General-purpose memory managers also do not provide the bulk deletion semantics required by many applications, including web servers and compilers. The approaches taken to date to address these and other memory management problems have been largely ad hoc. Programmers often attempt to work around these problems by writing custom memory managers. This approach leads to further difficulties, including data corruption caused when programmers inadvertently free custom-allocated objects to the general-purpose memory manager. In this thesis, we develop a framework for analyzing and designing high-quality memory managers. We develop a memory management infrastructure called heap layers that allows programmers to compose efficient memory managers from reusable and independently testable components. We conduct the first comprehensive examination of custom memory managers and show that most of these achieve slight or no performance improvements over a state-of-the-art general-purpose memory manager. Building on the knowledge gained in this study, we develop a hybrid memory management abstraction called reaps that combines the best of both approaches, allowing server applications to manage memory quickly and flexibly while avoiding memory leaks. We identify a number of previously unnoticed problems with concurrent memory management and analyze previous work in the light of these discoveries. We then present a concurrent memory manager called Hoard and prove that it avoids these problems.Computer Science