Explore a conference talk from OSDI '22 that introduces MemLiner, a runtime technique designed to enhance far-memory systems' performance. Learn how this innovative approach aligns memory accesses from applications and garbage collection to reduce local-memory working sets and improve remote-memory prefetching. Discover the challenges faced in modern datacenters regarding large memory footprints and resource utilization, and understand how MemLiner addresses these issues. Examine the implementation of MemLiner in OpenJDK's G1 and Shenandoah garbage collectors, and review the impressive performance improvements achieved in widely-deployed cloud systems. Gain insights into object classification, barriers, and the key design ideas behind this award-winning research that promises to revolutionize far-memory techniques in high-level language environments.