Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

AIFM - High-Performance, Application-Integrated Far Memory

USENIX via YouTube

Overview

Explore a groundbreaking approach to memory management in datacenter servers through this 20-minute conference talk from OSDI '20. Dive into the concept of Application-Integrated Far Memory (AIFM), a high-performance solution that addresses memory scarcity and underutilization in modern datacenters. Learn how AIFM enables applications to access remote memory resources with local RAM-like latency, avoiding read and write amplification issues common in paging-based systems. Discover the innovative API that allows developers to create remoteable, hybrid near/far memory data structures while maintaining transparency and ease of use. Examine the key insights behind AIFM's efficiency, including the exposure of application-level semantics to a high-performance runtime. Explore real-world applications of AIFM, including a web application frontend, NYC taxi data analytics, a memcached-like key-value cache, and Snappy compression. Compare AIFM's performance against state-of-the-art kernel-integrated, paging-based far memory systems, and understand its potential to revolutionize memory utilization in datacenter environments.

Syllabus

Intro
In-Memory Applications
Memory Is Inelastic
Trending Solution: Far Memory
Existing Far-Memory Systems Perform Poorly
Why Do Existing Systems Waste Performance?
Challenge 1: Semantic Gap
Challenge 2: High Kernel Overheads
Design Space
Remoteable Data Structure Library
Userspace Runtime
Pauseless Evacuator
Remote Agent
Sample Code
Implementation
Evaluation
Performance on Different Compute Intensities
NYC Taxi Analysis (C++ DataFrame)
Other Experiments
Related Work
Conclusion

Taught by

USENIX

Reviews

Start your review of AIFM - High-Performance, Application-Integrated Far Memory

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.