ExtMem: Enabling Application-Aware Virtual Memory Management for Data-Intensive Applications
Sepehr Jalalian, Shaurya Patel, Milad Rezaei Hajidehi, Margo I. Seltzer, Alexandra Fedorova
Abstract
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 memoryintensive applications. Past attempts to provide applicationspecific memory management either required significant inkernel changes or suffered from high overhead. We present EXTMEM, a flexible framework for providing applicationspecific 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.
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