Malleable Memory Mapping: User-Level Control of Memory Bounds for Effective Program Adaptation

This paper presents a user-level runtime system which provides memory malleability to programs running on non-dedicated computational environments. Memory malleability is analogous to processor malleability in the memory space, i.e. it lets a program shrink and expand its resident set size in response to runtime events, without affecting the correct execution of the program. Malleability becomes relevant in the context of grid computing, where loosely coupled distributed programs assume to run on busy computational nodes with fluctuating CPU and memory loads. User-level malleable memory is proposed as a portable solution to obtain as much as possible out of the available memory of a computational node, without reverting to more drastic solutions such as job suspension or migration, and without causing the system to thrash. Malleable memory mapping is also a solution to cope with the unpredictable behavior of existing virtual memory management policies under oversized memory loads. The current prototype is simple but leaves plenty of room for application-independent or application-specific optimizations, compiler support and other extensions. Our performance evaluation is a proof of concept that grid programs with malleable memory can improve their performance by an order of magnitude as opposed to grid programs that let their memory being reclaimed and reallocated by the OS.