The underutilization of disk parallelism and file cache buffers by traditional file systems induces I/O stall time that degrades the performance of modern microprocessor-based systems. In this paper, we present aggressive mechanisms that tailor file system resource management to the needs of I/O-intensive applications. In particular, we show how to use application-disclosed access patterns (hints) to expose and exploit I/O parallelism and to allocate dynamically file buffers among three competing demands: prefetching hinted blocks, caching hinted blocks for reuse, and caching recently used data for unhinted accesses. Our approach estimates the impact of alternative buffer allocations on application execution time and applies a cost-benefit analysis to allocate buffers where they will have the greatest impact. We implemented informed prefetching and caching in DEC’s OSF/1 operating system and measured its performance on a 150 MHz Alpha equipped with 15 disks running a range of applications including text search, 3D scientific visualization, relational database queries, speech recognition, and computational chemistry. Informed prefetching reduces the execution time of the first four of these applications by 20 % to 87%. Informed caching reduces the execution time of the fifth application by up to 30%.

Disk arrays were proposed in the 1980s as a way to use parallelism between multiple disks to improve aggregate I/O performance. Today they appear in the product lines of most major computer manufacturers. This paper gives a comprehensive overview of disk arrays and provides a framework in which to organize current and future work. The paper first introduces disk technology and reviews the driving forces that have popularized disk arrays: performance and reliability. It then discusses the two architectural techniques used in disk arrays: striping across multiple disks to improve performance and redundancy to improve reliability. Next, the paper describes seven disk array architectures, called RAID (Redundant Arrays of Inexpensive Disks) levels 0-6 and compares their performance, cost, and reliability. It goes on to discuss advanced research and implementation topics such as refining the basic RAID levels to improve performance and designing algorithms to maintain data consistency. Last, the paper describes six disk array prototypes or products and discusses future opportunities for research. The paper includes an annotated bibliography of disk array-related literature.

File prefetching is an effective technique for improving file access performance. In this paper, we present a file prefetching mechanism that is based on on-line analytic modeling of interesting system events and is transparent to higher levels. The mechanism, incorporated into a client's file cache manager, seeks to build semantic structures that capture the intrinsic correlations between file accesses. It then heuristically uses these structures to represent distinct file usage patterns and exploits them to prefetch files from a file server. We show results of a simulation study and of a working implementation. Measurements suggest that our method can predict future file accesses with an accuracy around 90%, that it can reduce cache miss rate by up to 47% and application latency by up to 40%. Our method imposes little overhead, even under antagonistic circumstances. 1 Introduction This paper reports the effectiveness of a predictive file prefetching technique that operates automat...

Modern high-end disk arrays often have several gigabytes of cache RAM. Unfortunately, most array caches use management policies which duplicate the same data blocks at both the client and array levels of the cache hierarchy: they are inclusive. Thus, the aggregate cache behaves as if it was only as big as the larger of the client and array caches, instead of as large as the sum of the two. Inclusiveness is wasteful: cache RAM is expensive. We explore the benefits of a simple scheme to achieve exclusive caching, in which a data block is cached at either a client or the disk array, but not both. Exclusiveness helps to create the effect of a single, large unified cache. We introduce a DEMOTE operation to transfer data ejected from the client to the array, and explore its effectiveness with simulation studies. We quantify the benefits and overheads of demotions across both synthetic and real-life workloads. The results show that we can obtain useful -- sometimes substantial -- speedups. During our investigations, we also developed some new cache-insertion algorithms that show promise for multi-client systems, and report on some of their properties.

DFSTrace is a system to collect and analyze long-term file reference data in a distributed UNIX workstation environment. The design of DFSTrace is unique in that it pays particular attention to efficiency, extensibility, and the logistics of long-term trace data collection in a distributed environment. The components of DFSTrace are a set of kernel hooks, a kernel buffer mechanism, a data extraction agent, a set of collection servers, and post-processing tools. Our experience with DFSTrace has been highly positive. Tracing has been virtually unnoticeable, degrading performance 3-7%, depending on the level of detail of tracing. We have collected file reference traces from approximately 30 workstations continuously for over two years. We have implemented a post-processing library to provide a convenient programmer interface to the traces, and have created an on-line database of results from a suite of analysis programs to aid trace selection. Our data has been used for a wide variety of purposes, including file system studies, performance measurement and tuning, and debugging. Extensions of DFSTrace have enabled its use in applications such as field reliability testing and determining disk geometry. This paper presents the design, implementation, and evaluation of DFSTrace and associated tools, and describes how they have been used.

The work habits of most individuals yield file access patterns that are quite pronounced and can be regarded as defining working sets of files used for particular applications. This paper describes a client-side cache management technique for detecting these patterns and then exploiting them to successfully prefetch files from servers. Trace-driven simulations show the technique substantially increases the hit rate of a client file cache in an environment in which a client workstation is dedicated to a single user. Successful file prefetching carries three major advantages: (1) applications run faster, (2) there is less "burst" load placed on the network, and (3) properly-loaded client caches can better survive network outages. Our technique requires little extra code, and --- because it is simply an augmentation of the standard LRU client cache management algorithm --- is easily incorporated into existing software. This work is supported by the New York State Science and Technology Fo...

Trace driven simulations are used to study the performance of several disk cache replacement policies for network fileservers. It is shown that locality based approaches, such as the common Least Recently Used (LRU) policy, which are known to work well on standalone disked workstations and at client workstations in distributed systems, are inappropriate at a fileserver. Quite simple frequency based approaches do better.

Informed prefetching and caching based on application disclosure of future I/O accesses (hints) can dramatically reduce the execution time of I/O-intensive applications. A recent study showed that, in the context of a single hinting application, prefetching and caching algorithms should adapt to the dynamic load on the disks to obtain the best performance. In this paper, we show how to incorporate adaptivity to disk load into the TIP2 system, which uses cost-benefit analysis to allocate global resources among multiple processes. We compare the resulting system, which we call TIPTOE (TIP with Temporal Overload Estimators) to Cao et al's LRU-SP allocation scheme, also modified to include adaptive prefetching. Using disk-accurate trace-driven simulation we show that, averaged over eleven experiments involving pairs of hinting applications, and with data striped over one to ten disks, TIPTOE delivers 7% lower execution time than LRU-SP. Where the computation and I/O demands of each experi...

Input/output performance on current parallel file systems is sensitive to a good match of application access pattern to file system capabilities. Automatic input/output access classification can determine application access patterns at execution time, guiding adaptive file system policies. In this paper we examine a new method for access pattern classification that uses hidden Markov models, trained on access patterns from previous executions, to create a probabilistic model of input/output accesses. We compare this approach to a neural network classification framework, presenting performance results from parallel and sequential benchmarks and applications. 1 Introduction Input/output is a critical bottleneck for many important scientific applications. One reason is that performance of extant parallel file systems is particularly sensitive to file access patterns. Often the application programmer must match application input/output requirements to the capabilities of the file system....

This paper focuses on extending the power of caching and prefetching to reduce file read latencies by exploiting application level hints about future I/O accesses. We argue that systems that disclose high-level knowledge can transfer optimization information across module boundaries in a manner consistent with sound software engineering principles. Such Transparent Informed Prefetching (TIP) systems provide a technique for converting the high throughput of new technologies such as disk arrays and log-structured file systems into low latency for applications. Our preliminary experiments show that even without a highthroughput I/O subsystem TIP yields reduced execution time of up to 30% for applications obtaining data from a remote file server and up to 13% for applications obtaining data from a single local disk. These experiments indicate that greater performance benefits will be available when TIP is integrated with low level resource management policies and highly parallel I/O subsys...