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Leveraging Non-Volatile Memory in Modern Storage Management Architectures
Non-volatile memory technologies (NVM) introduce a novel class of devices that combine characteristics of both storage and main memory. Like storage, NVM is not only persistent, but also denser and cheaper than DRAM. Like DRAM, NVM is byte-addressable and has lower access latency. In recent years, NVM has gained a lot of attention both in academia and in the data management industry, with views ranging from skepticism to over excitement. Some critics claim that NVM is not cheap enough to replace flash-based SSDs nor is it fast enough to replace DRAM, while others see it simply as a storage device. Supporters of NVM have observed that its low latency and byte-addressability requires radical changes and a complete rewrite of storage management architectures.
This thesis takes a moderate stance between these two views. We consider that, while NVM might not replace flash-based SSD or DRAM in the near future, it has the potential to reduce the gap between them. Furthermore, treating NVM as a regular storage media does not fully leverage its byte-addressability and low latency. On the other hand, completely redesigning systems to be NVM-centric is impractical. Proposals that attempt to leverage NVM to simplify storage management result in completely new architectures that face the same challenges that are already well-understood and addressed by the traditional architectures. Therefore, we take three common storage management architectures as a starting point, and propose incremental changes to enable them to better leverage NVM. First, in the context of log-structured merge-trees, we investigate the impact of storing data in NVM, and devise methods to enable small granularity accesses and NVM-aware caching policies. Second, in the context of B+Trees, we propose to extend the buffer pool and describe a technique based on the concept of optimistic consistency to handle corrupted pages in NVM. Third, we employ NVM to enable larger capacity and reduced costs in a index+log key-value store, and combine it with other techniques to build a system that achieves low tail latency. This thesis aims to describe and evaluate these techniques in order to enable storage management architectures to leverage NVM and achieve increased performance and lower costs, without major architectural changes.:1 Introduction
1.1 Non-Volatile Memory
1.2 Challenges
1.3 Non-Volatile Memory & Database Systems
1.4 Contributions and Outline
2 Background
2.1 Non-Volatile Memory
2.1.1 Types of NVM
2.1.2 Access Modes
2.1.3 Byte-addressability and Persistency
2.1.4 Performance
2.2 Related Work
2.3 Case Study: Persistent Tree Structures
2.3.1 Persistent Trees
2.3.2 Evaluation
3 Log-Structured Merge-Trees
3.1 LSM and NVM
3.2 LSM Architecture
3.2.1 LevelDB
3.3 Persistent Memory Environment
3.4 2Q Cache Policy for NVM
3.5 Evaluation
3.5.1 Write Performance
3.5.2 Read Performance
3.5.3 Mixed Workloads
3.6 Additional Case Study: RocksDB
3.6.1 Evaluation
4 B+Trees
4.1 B+Tree and NVM
4.1.1 Category #1: Buffer Extension
4.1.2 Category #2: DRAM Buffered Access
4.1.3 Category #3: Persistent Trees
4.2 Persistent Buffer Pool with Optimistic Consistency
4.2.1 Architecture and Assumptions
4.2.2 Embracing Corruption
4.3 Detecting Corruption
4.3.1 Embracing Corruption
4.4 Repairing Corruptions
4.5 Performance Evaluation and Expectations
4.5.1 Checksums Overhead
4.5.2 Runtime and Recovery
4.6 Discussion
5 Index+Log Key-Value Stores
5.1 The Case for Tail Latency
5.2 Goals and Overview
5.3 Execution Model
5.3.1 Reactive Systems and Actor Model
5.3.2 Message-Passing Communication
5.3.3 Cooperative Multitasking
5.4 Log-Structured Storage
5.5 Networking
5.6 Implementation Details
5.6.1 NVM Allocation on RStore
5.6.2 Log-Structured Storage and Indexing
5.6.3 Garbage Collection
5.6.4 Logging and Recovery
5.7 Systems Operations
5.8 Evaluation
5.8.1 Methodology
5.8.2 Environment
5.8.3 Other Systems
5.8.4 Throughput Scalability
5.8.5 Tail Latency
5.8.6 Scans
5.8.7 Memory Consumption
5.9 Related Work
6 Conclusion
Bibliography
A PiBenc
Efficient Logging in Non-Volatile Memory by Exploiting Coherency Protocols
Non-volatile memory (NVM) technologies such as PCM, ReRAM and STT-RAM allow
processors to directly write values to persistent storage at speeds that are
significantly faster than previous durable media such as hard drives or SSDs.
Many applications of NVM are constructed on a logging subsystem, which enables
operations to appear to execute atomically and facilitates recovery from
failures. Writes to NVM, however, pass through a processor's memory system,
which can delay and reorder them and can impair the correctness and cost of
logging algorithms.
Reordering arises because of out-of-order execution in a CPU and the
inter-processor cache coherence protocol. By carefully considering the
properties of these reorderings, this paper develops a logging protocol that
requires only one round trip to non-volatile memory while avoiding expensive
computations. We show how to extend the logging protocol to building a
persistent set (hash map) that also requires only a single round trip to
non-volatile memory for insertion, updating, or deletion
Elevating commodity storage with the SALSA host translation layer
To satisfy increasing storage demands in both capacity and performance,
industry has turned to multiple storage technologies, including Flash SSDs and
SMR disks. These devices employ a translation layer that conceals the
idiosyncrasies of their mediums and enables random access. Device translation
layers are, however, inherently constrained: resources on the drive are scarce,
they cannot be adapted to application requirements, and lack visibility across
multiple devices. As a result, performance and durability of many storage
devices is severely degraded.
In this paper, we present SALSA: a translation layer that executes on the
host and allows unmodified applications to better utilize commodity storage.
SALSA supports a wide range of single- and multi-device optimizations and,
because is implemented in software, can adapt to specific workloads. We
describe SALSA's design, and demonstrate its significant benefits using
microbenchmarks and case studies based on three applications: MySQL, the Swift
object store, and a video server.Comment: Presented at 2018 IEEE 26th International Symposium on Modeling,
Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS
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