NV-Heaps: making persistent objects fast and safe with next-generation, non-volatile memories

By Joel Coburn, Adrian M. Caulfield, Ameen Akel, Laura M. Grupp, Rajesh K. Gupta, Ranjit Jhala, Steven Swanson. ASPLOS XVI, 2011

794 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Neurology

View Paper: https://www.semanticscholar.org/paper/94783d113951822195d4ba44599a8fcbdef9d4bf

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cardiology and Cardiovascular Medicine

1. Steven Swanson

In Neurology

1. Steven Swanson
2. Vipin Kumar

Citations in the corpus

• Trends in big data analytics (2014, background): “On the other hand, the capability of durable memory writes reduces isolation; this issue could be addressed via durablememory transactions [93,24].”
• Approximate storage in solid-state memories (2013, background): “In the main memory case and when using object-based persistent stores like NV-heaps [10], objects may consist of interleaved precise and approximate data.”
• A simpler, safer programming and execution model for intermittent systems (2015, background): “NV-Heaps [8] considers the safety of memory-mapped non-volatile heaps, focusing on pointer integrity, and provides a programming construct for nonvolatile transactions based on BPFS’s architectural support.”
• NV-Tree: Reducing Consistency Cost for NVM-based Single Level Systems (2015, background): “NV-Heaps [12] is another way to consistently manage NVM directly by programmers based on epoch.”
• Evaluating STT-RAM as an energy-efficient main memory alternative (2013, methodology): “Phase change memory (PCRAM) has been proposed as a promising alternative to commodity DRAM [10], [12], [59], and there has been significant effort in making optimizations to PCRAM-based main memory to improve its latency, energy, and endurance.”
• An Empirical Guide to the Behavior and Use of Scalable Persistent Memory (2019, methodology): “Common ways to emulate NVM include adding delays to memory accesses in software [32,36,49], using software emulators [43,47], using software simulation [12,31,40], using hardware emulators such as Intel’s Persistent Memory Emulator Platform (PMEP) [21] to limit latency and bandwidth [54, 55, 60], us”
• Overview of emerging nonvolatile memory technologies (2014, background): “Nonvolatile memory is a computer memory that can retain the stored information even when not powered [3,19,20].”
• Atlas (2014, methodology): “This is essential to accommodating existing code, and a significant extension over prior work in this area [14, 37], which requires all updates to NVRAM to be within failure-atomic sections.”
• Basic Performance Measurements of the Intel Optane DC Persistent Memory Module (2019, methodology): “Over the past decade, they have written a slew of papers proposing new programming models [4, 31], file systems [33, 34, 32, 30, 5, 13], libraries [2, 3, 25], and applications built to exploit the performance and flexibility that NVDIMMs promised to deliver.”
• FPTree: A Hybrid SCM-DRAM Persistent and Concurrent B-Tree for Storage Class Memory (2016, neutral): “Several works proposed global solutions to these challenges, such as NVHeap [10], Mnemosyne [26], and REWIND [7], which are based on garbage collection and software transactional memory.”
• UNITY: Unified Memory and File Space (2017, methodology): “NV-Heaps [10] provides an object system for NVRAM and a set of common data types such as search trees, hash tables, and sparse graphs.”
• NOVA: A Log-structured File System for Hybrid Volatile/Non-volatile Main Memories (2016, methodology): “Researchers have proposed several approaches to integrating NVMs into computer systems [11] [13] [19] [31] [36] [41] [58] [67], and the most exciting proposals place NVMs on the processor's memory bus alongside conventional DRAM, leading to hybrid volatile/non-volatile main memory systems [4] [51]…”
• Alpaca: intermittent execution without checkpoints (2017, background): “…managing data structures in non-volatile memory, and for building consistent memory and file systems out of byte-addressable non-volatile memory [Coburn et al. 2011; Condit et al. 2009; Doshi and Varman 2012; Dulloor et al. 2014; Moraru et al. 2013; Narayanan and Hodson 2012; Venkataraman et…”
• In-Memory Big Data Management and Processing: A Survey (2015, background): “General libraries and programming interfaces are proposed to expose NVRAM as a persistent heap, enabling NVRAM adoption in an easy-to-use manner, such as NV-heaps [214], Mnemosyne [215], NVMalloc [216], and recovery and durable structures [213], [217].”
• Persistent B+-Trees in Non-Volatile Main Memory (2015, methodology): “There are wide-spread discussions on incorporating NVM technologies to substitute or complement DRAM as the main memory in future computer systems [5, 9, 36, 15, 26, 7, 31, 8, 33, 29, 20].”