Mako: a low-pause, high-throughput evacuating collector for memory-disaggregated datacenters
Mako: a low-pause, high-throughput evacuating collector for memory-disaggregated datacenters
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DOI：
10.1145/3519939.3523441
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发表时间：
2022-06
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通讯作者：
Haoran Ma;Chenxi Wang;Yifan Qiao;Miryung Kim
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作者：
Haoran Ma;Chenxi Wang;Yifan Qiao;Miryung Kim
作为新兴数据中心体系结构，资源分析已获得了很多吸引力，因为它改善了资源利用率并简化了在资源分类，不同类型的资源（内存，CPU等）下采用的硬件。记忆分解给并发垃圾收集带来效率挑战（GC）应用程序，因为GC和突变器线程仅仅运行并不断争夺内存和交换资源。当CPU服务器执行突变器线程时，同时运行这些任务。共享记忆。我们以一组围绕间接桌的新技术来应对这一挑战（命中），其中条目为您的评估提供了一个跳高的间接信息。吞吐量平均超过3×的表现。
Resource disaggregation has gained much traction as an emerging datacenter architecture, as it improves resource utilization and simplifies hardware adoption. Under resource disaggregation, different types of resources (memory, CPUs, etc.) are disaggregated into dedicated servers connected by high-speed network fabrics. Memory disaggregation brings efficiency challenges to concurrent garbage collection (GC), which is widely used for latency-sensitive cloud applications, because GC and mutator threads simultaneously run and constantly compete for memory and swap resources. Mako is a new concurrent and distributed GC designed for memory-disaggregated environments. Key to Mako’s success is its ability to offload both tracing and evacuation onto memory servers and run these tasks concurrently when the CPU server executes mutator threads. A major challenge is how to let servers efficiently synchronize as they do not share memory. We tackle this challenge with a set of novel techniques centered around the heap indirection table (HIT), where entries provide one-hop indirection for heap pointers. Our evaluation shows that Mako achieves 12 ms at the 90th-percentile pause time and outperforms Shenandoah by an average of 3× in throughput.