# MIND: In-Network Memory Management for Disaggregated Data Centers * Resource disaggregation * High resource utilization, ease to manage, elastic scalability * Memory disaggregation * Need for memory disaggregation * Now: suffer from low utilization, unbalanced usage, energy consumption * Timely problem (storage disaggregation is already popular) * Goal: * Performance (CPU <--> memory): high throughput and low latency * Transparent elasticity: flexible resource allocation * Existing approach * Distributed shared memory (DSM) * Good elasticity but not good performance * Recent disaggregated memory schemes * Compromise elasticity by high throughput (no sharing0 * Key insight: in-network memory management (MMU) * Central location: global view & processing directly in the data path * Programmable switching ASIC: flexible processing at line rate * Similarity between network functions and memory management * ![](/files/DRKrPZQJ7UyigYWwQ9Ao) * MIND: in-network memory management * ![](/files/4U1SRntKANy6EAXJnfJz) * Address translation: where is the data * Memory protection: is this access permitted or valid? * Cache coherence protocol: how to keep data synchronized? * Challenges in Building In-network MMU * Limited amount of in-network resources * Limited size of in-network memory * Tens of MB --> not sufficient to store metadata in a traditional way * Limited computation capability * Switching ASIC --> not sufficient to directly port traditional MMU functions * **3 Principles for System Design** * **P1: decouple memory management functionalities** * Each function has the data structure suitable to its purpose * **P2: Leverage global view of network** * Make better decisions for memory management * **P3: Exploit network-centric hardware primitives** * Reuse network hardware highly optimized for network functions * Challenges * Address translation * Small: too many entries, huge page: load balancing * Apply * Static huge partition * Fine-grained, range-based translation * Memory protection * Small: too many entries, huge page: inflexible protection * Solve: VMA-granularity protection * Cache directory * Small cache line: too many entries, large cache line: false sharing * Solve: access granularity, coherence granularity (dynamic resizing), with theoretical bound of O(log2) * Performance evaluation * Low contention, high contention * Conclusion * Trade-off between resource elasticity and performance in memory aggregation * MIND: in-network MMU by leveraging programmable network * Match the performance of prior proposals and provide transparent elasticity --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://sliu583.gitbook.io/blog/specific-work/seminar-and-talk/fall-21-reading-list/mind-in-network-memory-management-for-disaggregated-data-centers.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.