Prefetching in File Systems for Mimd Multiprocessors

The problem of providing file I/O to parallel programs has been largely neglected in the development of multiprocessor systems. There are two essential elements of any file system design intended for a highly parallel environment: parallel I/O and effective caching schemes. This paper concentrates on the second aspect of file system design and specifically, on the question of whether prefetching blocks of the file into the block cache can effectively reduce overall execution time of a parallel computation, even under favorable assumptions. \par Experiments have been conducted with an interleaved file system testbed on the Butterfly Plus multiprocessor. Results of these experiments suggest that 1) the hit ratio, the accepted measure in traditional caching studies, may not be an adequate measure of performance when the workload consists of parallel computations and parallel file access patterns, 2) caching with prefetching can significantly improve the hit ratio and the average time to perform an I/O operation, and 3) an improvement in overall execution time has been observed in most cases. In spite of these gains, prefetching sometimes results in increased execution times (a negative result, given the optimistic nature of the study). \par We explore why is it not trivial to translate savings on individual I/O requests into consistently better overall performance and identify the key problems that need to be addressed in order to improve the potential of prefetching techniques in this environment

Prefetching in File Systems for Mimd Multiprocessors

The problem of providing file I/O to parallel programs has been largely neglected in the development of multiprocessor systems. There are two essential elements of any file system design intended for a highly parallel environment: parallel I/O and effective caching schemes. This paper concentrates on the second aspect of file system design and specifically, on the question of whether prefetching blocks of the file into the block cache can effectively reduce overall execution time of a parallel computation, even under favorable assumptions. \par Experiments have been conducted with an interleaved file system testbed on the Butterfly Plus multiprocessor. Results of these experiments suggest that 1) the hit ratio, the accepted measure in traditional caching studies, may not be an adequate measure of performance when the workload consists of parallel computations and parallel file access patterns, 2) caching with prefetching can significantly improve the hit ratio and the average time to perform an I/O operation, and 3) an improvement in overall execution time has been observed in most cases. In spite of these gains, prefetching sometimes results in increased execution times (a negative result, given the optimistic nature of the study). \par We explore why is it not trivial to translate savings on individual I/O requests into consistently better overall performance and identify the key problems that need to be addressed in order to improve the potential of prefetching techniques in this environment

Traffic Characteristics of a Distributed Memory System

We believe that many distributed computing systems of the future will use distributed shared memory as a technique for interprocess communication. Thus, traffic generated by memory requests will be a major component of the traffic for any networks which connect nodes in such a system. In this paper, we study memory reference strings gathered with a tracing program we devised. We study several models. First, we look at raw reference data, as would be seen if the network were a backplane. Second, we examine references in units of blocks , first using a one-block cache model and then with an infinite cache. Finally, we study the effect of predictive prepaging of these blocks on the traffic. We provide a novel representation of memory reference data which can be used to calculate interarrival distributions directly. Integrating communication with computation can be used to control both traffic and performance

Practical Prefetching Techniques for Multiprocessor File Systems

Improvements in the processing speed of multiprocessors are outpacing improvements in the speed of disk hardware. Parallel disk I/O subsystems have been proposed as one way to close the gap between processor and disk speeds. In a previous paper we showed that prefetching and caching have the potential to deliver the performance benefits of parallel file systems to parallel applications. In this paper we describe experiments with practical prefetching policies that base decisions only on on-line reference history, and that can be implemented efficiently. We also test the ability of these policies across a range of architectural parameters

Practical Prefetching Techniques for Multiprocessor File Systems

Improvements in the processing speed of multiprocessors are outpacing improvements in the speed of disk hardware. Parallel disk I/O subsystems have been proposed as one way to close the gap between processor and disk speeds. In a previous paper we showed that prefetching and caching have the potential to deliver the performance benefits of parallel file systems to parallel applications. In this paper we describe experiments with practical prefetching policies that base decisions only on on-line reference history, and that can be implemented efficiently. We also test the ability of these policies across a range of architectural parameters

Optimal Prediction for Prefetching in the Worst Case

This is the published version. Copyright © 1998 Society for Industrial and Applied MathematicsResponse time delays caused by I/O are a major problem in many systems and database applications. Prefetching and cache replacement methods are attracting renewed attention because of their success in avoiding costly I/Os. Prefetching can be looked upon as a type of online sequential prediction, where the predictions must be accurate as well as made in a computationally efficient way. Unlike other online problems, prefetching cannot admit a competitive analysis, since the optimal offline prefetcher incurs no cost when it knows the future page requests. Previous analytical work on prefetching [. Vitter Krishnan 1991.] [J. Assoc. Comput. Mach., 143 (1996), pp. 771--793] consisted of modeling the user as a probabilistic Markov source. In this paper, we look at the much stronger form of worst-case analysis and derive a randomized algorithm for pure prefetching. We compare our algorithm for every page request sequence with the important class of finite state prefetchers, making no assumptions as to how the sequence of page requests is generated. We prove analytically that the fault rate of our online prefetching algorithm converges almost surely for every page request sequence to the fault rate of the optimal finite state prefetcher for the sequence. This analysis model can be looked upon as a generalization of the competitive framework, in that it compares an online algorithm in a worst-case manner over all sequences with a powerful yet nonclairvoyant opponent. We simultaneously achieve the computational goal of implementing our prefetcher in optimal constant expected time per prefetched page using the optimal dynamic discrete random variate generator of [. Matias Matias, Vitter, and Ni [Proc. 4th Annual SIAM/ACM Symposium on Discrete Algorithms, Austin, TX, January 1993]

Optimal Prediction for Prefetching in the Worst Case

AMS subject classi cations. 68Q25, 68T05, 68P20, 68N25, 60J20 PII. S0097539794261817Response time delays caused by I/O are a major problem in many systems and database applications. Prefetching and cache replacement methods are attracting renewed attention because of their success in avoiding costly I/Os. Prefetching can be looked upon as a type of online sequential prediction, where the predictions must be accurate as well as made in a computationally e cient way. Unlike other online problems, prefetching cannot admit a competitive analysis, since the optimal o ine prefetcher incurs no cost when it knows the future page requests. Previous analytical work on prefetching [J. Assoc. Comput. Mach., 143 (1996), pp. 771{793] consisted of modeling the user as a probabilistic Markov source. In this paper, we look at the much stronger form of worst-case analysis and derive a randomized algorithm for pure prefetching. We compare our algorithm for every page request sequence with the important class of nite state prefetchers, making no assumptions as to how the sequence of page requests is generated. We prove analytically that the fault rate of our online prefetching algorithm converges almost surely for every page request sequence to the fault rate of the optimal nite state prefetcher for the sequence. This analysis model can be looked upon as a generalization of the com- petitive framework, in that it compares an online algorithm in a worst-case manner over all sequences with a powerful yet nonclairvoyant opponent. We simultaneously achieve the computational goal of implementing our prefetcher in optimal constant expected time per prefetched page using the optimal dynamic discrete random variate generator of Matias, Vitter, and Ni [Proc. 4th Annual SIAM/ACM Symposium on Discrete Algorithms, Austin, TX, January 1993]

PASSION: Parallel And Scalable Software for Input-Output

We are developing a software system called PASSION: Parallel And Scalable Software for Input-Output which provides software support for high performance parallel I/O. PASSION provides support at the language, compiler, runtime as well as file system level. PASSION provides runtime procedures for parallel access to files (read/write), as well as for out-of-core computations. These routines can either be used together with a compiler to translate out-of-core data parallel programs written in a language like HPF, or used directly by application programmers. A number of optimizations such as Two-Phase Access, Data Sieving, Data Prefetching and Data Reuse have been incorporated in the PASSION Runtime Library for improved performance. PASSION also provides an initial framework for runtime support for out-of-core irregular problems. The goal of the PASSION compiler is to automatically translate out- of-core data parallel programs to node programs for distributed memory machines, with calls to the PASSION Runtime Library. At the language level, PASSION suggests extensions to HPF for out-of-core programs. At the file system level, PASSION provides support for buffering and prefetching data from disks. A portable parallel file system is also being developed as part of this project, which can be used across homogeneous or heterogeneous networks of workstations. PASSION also provides support for integrating data and task parallelism using parallel I/O techniques. We have used PASSION to implement a number of out-of-core applications such as a Laplace\u27s equation solver, 2D FFT, Matrix Multiplication, LU Decomposition, image processing applications as well as unstructured mesh kernels in molecular dynamics and computational fluid dynamics. We are currently in the process of using PASSION in applications in CFD (3D turbulent flows), molecular structure calculations, seismic computations, and earth and space science applications such as Four-Dimensional Data Assimilation. PASSION is currently available on the Intel Paragon, Touchstone Delta and iPSC/860. Efforts are underway to port it to the IBM SP-1 and SP-2 using the Vesta Parallel File System

Cooperative caching and prefetching in parallel/distributed file systems

If we examine the structure of the applications that run on parallel machines, we observe that their I/O needs increase tremendously every day. These applications work with very large data sets which, in most cases, do not fit in memory and have to be kept in the disk. The input and output data files are also very large and have to be accessed very fast. These large applications also want to be able to checkpoint themselves without wasting too much time. These facts constantly increase the expectations placed on parallel and distributed file systems. Thus, these file systems have to improve their performance to avoid becoming the bottleneck in parallel/distributed environments. On the other hand, while the performance of the new processors, interconnection networks and memory increases very rapidly, no such thing happens with the disk performance. This lack of improvement is due to the mechanical parts used to build the disks. These components are slow and limit both the latency and t..