A reimplementation of the UNIX file system is described. The reimplementation provides substantially higher throughput rates by using more flexible allocation policies that allow better locality of reference and can be adapted to a wide range of peripheral and processor characteristics. The new file system clusters data that is sequentially accessed and provides two block sizes to allow fast access to large files while not wasting large amounts of space for small files. File access rates of up to ten times faster than the traditional UNIX file system are experienced. Long needed enhancements to the programmers’ interface are discussed. These include a mechanism to place advisory locks on files, extensions of the name space across file systems, the ability to use long file names, and provisions for administrative control of resource usage.

Unix is a general-purpose, multi-user, interactive operating system for the larger Digital Equipment Corporation PDP-11 and the Interdata 8/32 computers. It offers a number of features seldom found even in larger operating systems, including i A hierarchical file system incorporating demountable volumes, ii Compatible file, device, and inter-process I/O, iii The ability to initiate asynchronous processes, iv System command language selectable on a per-user basis, v Over 100 subsystems including a dozen languages, vi High degree of portability. This paper discusses the nature and implementation of the file system and of the user command interface. I.

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%.

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...

Aggressive prefetching is an effective technique for reducing the execution times of disk-bound applications; that is, applications that manipulate data too large or too infrequently used to be found in file or disk caches. While automatic prefetching approaches based on static analysis or historical access patterns are effective for some workloads, they are not as effective as manually-driven (programmer-inserted) prefetching for applications with irregular or input-dependent access patterns. In this paper, we propose to exploit whatever processor cycles are left idle while an application is stalled on I/O by using these cycles to dynamically analyze the application and predict its future I/O accesses. Our approach is to speculatively pre-execute the application’s code in order to discover and issue hints for its future read accesses. Coupled with an

We seek to make robot programming more efficient by developing a standard abstract interface for robot hardware, based on familiar techniques from operating systems and network engineering. This paper describes the application of three well known abstractions, the character device model, the interface/driver model, and the client/server model to this purpose. These abstractions underlie Player/Stage, our Open Source project for rapid development of robot control systems. One product of this project is the Player Abstract Device Interface (PADI) specification, which denes a set of interfaces that capture the functionality of logically similar sensors and actuators. This specification is the central abstraction that enables Player-based controllers to run unchanged on a variety of real and simulated devices. We propose that PADI could be a starting point for development of a standard platform for robot interfacing, independent of Player, to enable code portability and re-use, while still providing access to the unique capabilities of individual devices.

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...

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...

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We present an in-kernel disk prefetcher which uses speculative execution to determine what data an application is likely to require in the near future. By placing our design within the operating system, we provide several bene ts compared to the previous application-level design. Not only is our system easier to implement and deploy, but by handling page faults as well as traditional le-access methods we are able to apply speculative execution to swapping applications, which often spend the majority of their execution time fetching non-resident pages. We also present two new OS features that further improve the performance of speculative execution for applications that have have large page tables and working sets. These are a fast method for synchronizing an errant speculative process with normal execution, and a modi ed form of copy-on-write which preserves application semantics without delaying normal execution. Finally, by leveraging OS knowledge about memory usage and contention, we design a mechanism for estimating and limiting the memory overhead of speculative executions.