Far-memory techniques that enable applications to use remote memory are increasingly appealing in modern datacenters, supporting applications’ large memory footprint and improving machines’ resource utilization. Unfortunately, most far-memory techniques focus on OS-level optimizations and are agnostic to managed runtimes and garbage collections (GC) underneath applications written in high-level languages. With different object-access patterns from applications, GC can severely interfere with existing far-memory techniques, breaking prefetching algorithms and causing severe local-memory misses.
We developed MemLiner, a runtime technique that improves the performance of far-memory systems by “lining up” memory accesses from the application and the GC so that they follow similar memory access paths, thereby (1)reducing the local-memory working set and (2) improving remote-memory prefetching through simplified memory access patterns. We implemented MemLiner in two widely-used GCs in OpenJDK: G1 and Shenandoah. Our evaluation with a range of widely-deployed cloud systems shows MemLiner improves applications’ end-to-end performance by up to 2.5x.
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Semeru: A Memory-Disaggregated Managed Runtime
Resource-disaggregated architectures have risen in popularity for large datacenters. However, prior disaggregation systems are designed for native applications; in addition, all of them require applications to possess excellent locality to be efficiently executed. In contrast, programs written in managed languages are subject to periodic garbage collection (GC), which is a typical graph workload with poor locality. Although most datacenter applications are written in managed languages, current systems are far from delivering acceptable performance for these applications.
This paper presents Semeru, a distributed JVM that can dramatically improve the performance of managed cloud applications in a memory-disaggregated environment. Its design possesses three major innovations: (1) a universal Java heap, which provides a unified abstraction of virtual memory across CPU and memory servers and allows any legacy program to run without modifications; (2) a distributed GC, which offloads object tracing to memory servers so that tracing is performed closer to data; and (3) a swap system in the OS kernel that works with the runtime to swap page data efficiently. An evaluation of Semeru on a set of widely-deployed systems shows very promising results.
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- Award ID(s):
- 1764077
- NSF-PAR ID:
- 10227338
- Date Published:
- Journal Name:
- 14th USENIX Symposium on Operating Systems Design and Implementation, OSDI 2020, Virtual Event, November 4-6, 2020
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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