This talk provides a taxonomy of filesystem and storage development from 1979 to the present with the BSD Fast Filesystem as its focus. It describes the early performance work done by increasing the disk block size and by being aware of the disk geometry and using that knowledge to optimize rotational layout. With the abstraction of the geometry in the late 1980's and the ability of the hardware to cache and handle multiple requests, filesystems performance ceased trying to track geometry and instead sought to maximize performance by doing contiguous file layout. Small file performance was optimized through the use of techniques such as journaling and soft updates. By the late 1990's, filesystems had to be redesigned to handle the ever growing disk capacities. The addition of snapshots allowed for faster and more frequent backups. The increasingly harsh environment of the Internet required greater data protection provided by access-control lists and mandatory-access controls. The talk concludes with a discussion of the addition of symmetric multi-processing support needed to utilize all the CPUs found in the increasingly ubiquitous multi-core processors.

Dr. Marshall Kirk McKusick's work with Unix and BSD development spans over four decades. It begins with his first paper on the implementation of Berkeley Pascal in 1979, goes on to his pioneering work in the eighties on the BSD Fast File System, the BSD virtual memory system, the final release of 4.4BSD-Lite from the UC Berkeley Computer Systems Research Group, and carries on with his work on FreeBSD. A key figure in Unix and BSD development, his experiences chronicle not only the innovative technical achievements but also the interesting personalities and philosophical debates in Unix over the past thirty-five years.

Dr. McKusick’s second edition of The Design and Implementation of the FreeBSD Operating System was released in September 2014.

Writing data to a page not present in the file-system page cache causes the operating system to synchronously fetch the page into memory first. Synchronous page fetch defines both policy (when) and mechanism (how), and always blocks the writing process. Non-blocking writes eliminate such blocking by buffering the written data elsewhere in memory and unblocking the writing process immediately. Subsequent reads to the updated page locations are also made non-blocking. This new handling of writes to non-cached pages allow processes to overlap more computation with I/O and improves page fetch I/O throughput by increasing fetch parallelism. Our empirical evaluation demonstrates the potential of nonblocking writes in improving the overall performance of systems with no loss of performance when workloads cannot benefit from it. Across the Filebench write workloads, non-blocking writes improve benchmark throughput by 7X on average (up to 45.4X) when using disk drives and by 2.1X on average (up to 4.2X) when using SSDs. For the SPECsfs2008 benchmark, non-blocking writes decrease overall average latency of NFS operations between 3.5% and 70% and average write latency between 65% and 79%. When replaying the MobiBench file system traces, non-blocking writes decrease average operation latency by 20-60%.

Virtualization systems should be responsible for satisfying the service level objectives (SLOs) for each VM. Performance SLOs, in particular, are generally achieved by isolating the underlying hardware resources among the VMs. In this paper, we show through empirical evaluation that performance SLOs cannot be satisfied with current commercial SSDs. We show that garbage collection is the source of this problem and that this cannot be easily controlled because of the interaction between VMs. To control the effect of garbage collection on VMs, we propose a scheme called OPS isolation. OPS isolation allocates flash memory blocks so that blocks of one VM do not interfere with blocks of other VMs during garbage collection. Experimental results show that performance SLO can be achieved through OPS isolation.

We present the design, implementation, and evaluation of a file system mechanism that protects the integrity of application data from failures such as process crashes, kernel panics, and power outages. A simple interface offers applications a guarantee that the application data in a file always reflects the most recent successful fsync or msync operation on the file. Our file system furthermore offers a new syncv mechanism that failure-atomically commits changes to multiple files. Failure-injection tests verify that our file system protects the integrity of application data from crashes and performance measurements confirm that our implementation is efficient. Our file system runs on conventional hardware and unmodified Linux kernels and will be released commercially. We believe that our mechanism is implementable in any file system that supports per-file writable snapshots.

Although data compression can benefit flash memory lifetime, little work has been done to rigorously study the full potential of exploiting data compressibility to improve memory lifetime. This work attempts to fill this missing link. Motivated by the fact that memory cell damage strongly depends on the data content being stored, we first propose an implicit data compression approach (i.e., compress each data sector but do not increase the number of sectors per flash memory page) as a complement to conventional explicit data compression that aims to increase the number of sectors per flash memory page. Due to the runtime variation of data compressibility, each flash memory page almost always contains some unused storage space left by compressed data sectors. We develop a set of design strategies for exploiting such unused storage space to reduce the overall memory physical damage. We derive a set of mathematical formulations that can quantitatively estimate flash memory physical damage reduction gained by the proposed design strategies for both explicit and implicit data compression. Using 20nm MLC NAND flash memory chips, we carry out extensive experiments to quantify the content dependency of memory cell damage, based upon which we empirically evaluate and compare the effectiveness of the proposed design strategies under a wide spectrum of data compressibility characteristics.

NAND flash, used in modern SSDs, is a write-once medium, where each memory cell must be erased prior to writing. The lifetime of an SSD is limited by the number of erasures allowed on each cell. Thus, minimizing erasures is a key objective in SSD design.

A promising approach to eliminate erasures and extend SSD lifetime is to use write-once memory (WOM) codes, designed to accommodate additional writes on write-once media. However, these codes inflate the physically stored data by at least 29%, and require an extra read operation before each additional write. This reduces the available capacity and I/O performance of the storage device, so far preventing the adoption of these codes in SSD design.

Host-side flash storage opens up an exciting avenue for accelerating Virtual Machine (VM) writes in virtualized datacenters. The key challenge with implementing such an acceleration layer is to do so without breaking live VM migration which is essential for providing distributed resource management and high availability. High availability also powers-on VMs on new host when the previous host crashes. We introduce FVP, a fault tolerant host-side flash write acceleration layer that seamlessly integrates with the virtualized environment while preserving dynamic resource management and high availability, the holy tenets of a virtualized environment. FVP integrates with the VMware ESX hypervisor kernel to intercept VM I/O and redirects the I/O to host-side flash devices. VMs experience flash latencies instead of SAN latencies and write intensive applications such as databases and email servers benefit from predictable write throughput. No changes are required to the VM guest operating systems so VM applications can continue to function seamlessly without any modifications. FVP pools together all the host-side flash devices in the cluster so every host can access another host’s flash device preserving VM mobility. By replicating VM writes onto peer host-side flash devices, FVP is able to tolerate multiple cascading host and flash failures. Failure recovery is distributed, requiring no central co-ordination. We describe the workings of the FVP key components and demonstrate how FVP reduces VM latencies to accelerate VM writes, improves performance predictability, and increases virtualized datacenter efficiency.

Storage system benchmarks either use samples of proprietary data or synthesize artificial data in simple ways (such as using zeros or random data). However, many storage systems behave completely differently on such artificial data than they do on real-world data. This is the case with systems that include data reduction techniques, such as compression and/or deduplication.

To address this problem, we propose a benchmarking methodology called mimicking and apply it in the domain of data compression. Our methodology is based on characterizing the properties of real data that influence the performance of compressors. Then, we use these characterizations to generate new synthetic data that mimics the real one in many aspects of compression. Unlike current solutions that only address the compression ratio of data, mimicking is flexible enough to also emulate compression times and data heterogeneity. We show that these properties matter to the system’s performance.

In our implementation, called SDGen, characterizations take at most 2:5KB per data chunk (e.g., 64KB) and can be used to efficiently share benchmarking data in a highly anonymized fashion; sharing it carries few or no privacy concerns. We evaluated our data generator’s accuracy on compressibility and compression times using real-world datasets and multiple compressors (lz4, zlib, bzip2 and lzma). As a proof-of-concept, we integrated SDGen as a content generation layer in two popular benchmarks (LinkBench and Impressions).

Insights from workloads have been instrumental in hardware and software design, problem diagnosis, and performance optimization. The recent emergence of software-defined data centers and application-centric computing has further increased the interest in studying workloads. Despite the ever-increasing interest, the lack of general frameworks for trace capture and workload analysis at line rate has impeded characterizing many storage workloads and systems. This is in part due to complexities associated with engineering a solution that is tailored enough to use computational resources efficiently yet is general enough to handle different types of analyses or workloads.

This paper presents Chronicle, a high-throughput framework for capturing and analyzing Network File System (NFS) workloads at line rate. More specifically, we designed Chronicle to characterize NFS network traffic at rates above 10Gb/s for days to weeks. By leveraging the actor programming model and a pluggable, pipelined architecture, Chronicle facilitates a highly portable and scalable framework that imposes little burden on application programmers. In this paper, we demonstrate that Chronicle can reconstruct, process, and record storage-level semantics at the rate of 14Gb/s using general-purpose CPUs, disks, and NICs.

Mobile apps need to manage data, often across devices, to provide users with a variety of features such as seamless access, collaboration, and offline editing. To do so reliably, an app must anticipate and handle a host of local and network failures while preserving data consistency. For mobile environments, frugal usage of cellular bandwidth and device battery are also essential. The above requirements place an enormous burden on the app developer. We built Simba, a data-sync service that provides mobile app developers with a high-level local-programming abstraction unifying tabular and object data—a need common to mobile apps—and transparently handles data storage and sync in a reliable, consistent, and efficient manner. In this paper we present a detailed description of Simba’s client software which acts as the gateway to the data sync infrastructure. Our evaluation shows Simba’s effectiveness in rapid development of robust mobile apps that are consistent under all failure scenarios, unlike apps developed with Dropbox. Simba apps are also demonstrably frugal with cellular resources.