NVAlloc: rethinking heap metadata management in persistent memory allocators

Abstract

Persistent memory allocation is a fundamental building block for developing high-performance and in-memory applications. Existing persistent memory allocators suffer from suboptimal heap organizations that introduce repeated cache line flushes and small random accesses in persistent memory. Worse, many allocators use static slab segregation resulting in a dramatic increase in memory consumption when allocation request size is changed. In this paper, we design a novel allocator, named NVAlloc, to solve the above issues simultaneously. First, NVAlloc eliminates cache line reflushes by mapping contiguous data blocks in slabs to interleaved metadata entries stored in different cache lines. Second, it writes small metadata units to a persistent bookkeeping log in a sequential pattern to remove random heap metadata accesses in persistent memory. Third, instead of using static slab segregation, it supports slab morphing, which allows slabs to be transformed between size classes to significantly improve slab usage. NVAlloc is complementary to the existing consistency models. Results on 6 benchmarks demonstrate that NVAlloc improves the performance of state-of-the-art persistent memory allocators by up to 6.4x and 57x for small and large allocations, respectively. Using NVAlloc reduces memory usage by up to 57.8%. Besides, we integrate NVAlloc in a persistent FPTree. Compared to the state-of-the-art allocators, NVAlloc improves the performance of this application by up to 3.1x. CCS CONCEPTS• Software and its engineering → Allocation / deallocation strategies; • Hardware → Non-volatile memory.

Structured storage for ubiquitous operating systems

“…而在此之 前, 开发者需要手动实现复杂的内核模块来支持类似的功能. 此外, PMDK, Ralloc [47] 和 NVAlloc [48] , 与 Makalu [45] 和 Nvm malloc [46] 相比, 吞吐量提升了 1.3∼3.7 倍. 这是因为后两者是基于模拟器的系 统, 模拟器往往无法完全模拟真实设备的硬件特性和性能特征, 导致系统性能表现不佳.…”

“…这是因为后两者是基于模拟器的系 统, 模拟器往往无法完全模拟真实设备的硬件特性和性能特征, 导致系统性能表现不佳. 最后, Hyte 与 PMDK, Ralloc [47] 和 NVAlloc [48] 相比, 实现了 1.5∼3.9 倍的吞吐量提升. 这一显著优势主要得益于 Hyte 从全栈角度进行跨层的优化设计, 通过去除文件抽象并直接在设备上构建表结构, Hyte 消除了 诸如 mmap 系统调用、文件元数据、冗余日志等开销, 轻量化了软件栈, 从而实现了系统性能的大幅 提升.…”