312 research outputs found
PrismDB: Read-aware Log-structured Merge Trees for Heterogeneous Storage
In recent years, emerging hardware storage technologies have focused on
divergent goals: better performance or lower cost-per-bit of storage.
Correspondingly, data systems that employ these new technologies are optimized
either to be fast (but expensive) or cheap (but slow). We take a different
approach: by combining multiple tiers of fast and low-cost storage technologies
within the same system, we can achieve a Pareto-efficient balance between
performance and cost-per-bit.
This paper presents the design and implementation of PrismDB, a novel
log-structured merge tree based key-value store that exploits a full spectrum
of heterogeneous storage technologies (from 3D XPoint to QLC NAND). We
introduce the notion of "read-awareness" to log-structured merge trees, which
allows hot objects to be pinned to faster storage, achieving better tiering and
hot-cold separation of objects. Compared to the standard use of RocksDB on
flash in datacenters today, PrismDB's average throughput on heterogeneous
storage is 2.3 faster and its tail latency is more than an order of
magnitude better, using hardware than is half the cost
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
Distributed Multi-writer Multi-reader Atomic Register with Optimistically Fast Read and Write
A distributed multi-writer multi-reader (MWMR) atomic register is an
important primitive that enables a wide range of distributed algorithms. Hence,
improving its performance can have large-scale consequences. Since the seminal
work of ABD emulation in the message-passing networks [JACM '95], many
researchers study fast implementations of atomic registers under various
conditions. "Fast" means that a read or a write can be completed with 1
round-trip time (RTT), by contacting a simple majority. In this work, we
explore an atomic register with optimal resilience and "optimistically fast"
read and write operations. That is, both operations can be fast if there is no
concurrent write.
This paper has three contributions: (i) We present Gus, the emulation of an
MWMR atomic register with optimal resilience and optimistically fast reads and
writes when there are up to 5 nodes; (ii) We show that when there are > 5
nodes, it is impossible to emulate an MWMR atomic register with both
properties; and (iii) We implement Gus in the framework of EPaxos and Gryff,
and show that Gus provides lower tail latency than state-of-the-art systems
such as EPaxos, Gryff, Giza, and Tempo under various workloads in the context
of geo-replicated object storage systems
Simurgh: a fully decentralized and secure NVMM user space file system
The availability of non-volatile main memory (NVMM) has started a new era for storage systems and NVMM specific file systems can support extremely high data and metadata rates, which are required by many HPC and data-intensive applications. Scaling metadata performance within NVMM file systems is nevertheless often restricted by the Linux kernel storage stack, while simply moving metadata management to the user space can compromise security or flexibility. This paper introduces Simurgh, a hardware-assisted user space file system with decentralized metadata management that allows secure metadata updates from within user space. Simurgh guarantees consistency, durability, and ordering of updates without sacrificing scalability. Security is enforced by only allowing NVMM access from protected user space functions, which can be implemented through two proposed instructions. Comparisons with other NVMM file systems show that Simurgh improves metadata performance up to 18x and application performance up to 89% compared to the second-fastest file system.This work has been supported by the European Comission’s BigStorage project H2020-MSCA-ITN2014-642963. It is also supported by the Big Data in Atmospheric Physics (BINARY) project, funded by the Carl Zeiss Foundation under Grant No.: P2018-02-003.Peer ReviewedPostprint (author's final draft
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