Sepehr Jalalian, Shaurya Patel, Milad Rezaei Hajidehi, Margo Seltzer, and Alexandra Fedorova, University of British Columbia
For over forty years, researchers have demonstrated that operating system memory managers often fall short in supporting memory-hungry applications. The problem is even more critical today, with disaggregated memory and new memory technologies and in the presence of tera-scale machine learning models, large-scale graph processing, and other memory-intensive applications. Past attempts to provide application-specific memory management either required significant in-kernel changes or suffered from high overhead. We present ExtMem, a flexible framework for providing application-specific memory management. It differs from prior solutions in three ways: (1) It is compatible with today’s Linux deployments, (2) it is a general-purpose substrate for addressing various memory and storage backends, and (3) it is performant in multithreaded environments. ExtMem allows for easy and rapid prototyping of new memory management algorithms, easy collection of memory patterns and statistics, and immediate deployment of isolated custom memory management.
