Many scientific applications that run on today’s multiprocessors, such as weather forecasting and seismic analysis, are bottlenecked by their file-I/O needs. Even if the multiprocessor is configured with sufficient I/O hardware, the file-system software often fails to provide the available bandwidth to the application. Although libraries and enhanced file-system interfaces can make a significant improvement, we believe that fundamental changes are needed in the file-server software. We propose a new technique, disk-directed I/O, to allow the disk servers to determine the flow of data for maximum performance. Our simulations show that tremendous performance gains are possible. Indeed, disk-directed I/O provided consistent high performance that was largely independent of data distribution, obtained up to 93 % of peak disk bandwidth, and was as much as 16 times faster than traditional parallel file systems.

Most current multiprocessor le systems are designed to use multiple disks in parallel, using the high aggregate bandwidth to meet the growing I/O requirements of parallel scienti c applications. Many multiprocessor le systems provide applications with a conventional Unix-like interface, allowing the application to access multiple disks transparently. Thisinterface conceals the parallelism within the le system, increasing the ease of programmability, but making it di cult or impossible for sophisticated programmers and libraries to use knowledge about their I/O needs to exploit that parallelism. In addition to providing an insu cient interface, most current multiprocessor le systems are optimized for a di erent workload than they are being asked to support. We introduce Galley, a new parallel le system that is intended to e ciently support realistic scienti c multiprocessor workloads. We discuss Galley's le structure and application interface, as well as the performance advantages o ered by that interface. 1

Multiprocessors have permitted astounding increases in computational performance, but many cannot meet the intense I/O requirements of some scientific applications. An important component of any solution to this I/O bottleneck is a parallel file system that can provide high-bandwidth access to tremendous amounts of data in parallel to hundreds or thousands of processors. Most successful systems are based on a solid understanding of the expected workload, but thus far there have been no comprehensive workload characterizations of multiprocessor le systems. This paper presents the results of a three week tracing study in which all file-related activity on a massively parallel computer was recorded. Our instrumentation di ers from previous efforts in that it collects information about every I/O request and about the mix of jobs running in a production environment. We also present the results of a trace-driven caching simulation and recommendations for designers of multiprocessor file systems.

SOLAR is a portable high-performance library for out-of-core dense matrix computations. It combines portability with high performance by using existing high-performance in-core subroutine libraries and by using an optimized matrix input-output library. SOLAR works on parallel computers, workstations, and personal computers. It supports in-core computations on both shared-memory and distributed-memory machines, and its matrix input-output library supports both conventional I/O interfaces and parallel I/O interfaces. This paper discusses the overall design of SOLAR, its interfaces, and the design of several important subroutines. Experimental results show that SOLAR can factor on a single workstation an out-of-core positive-definite symmetric matrix at a rate exceeding 215 Mflops, and an out-of-core general matrix at a rate exceeding 195 Mflops. Less than 16 % of the running time is spent on I/O in these computations. These results indicate that SOLAR's portability does not compromise its performance. We expect that the combination of portability, modularity, and the use of a high-level I/O interface will make the library an important platform for research on out-of-core algorithms and on parallel I/O.

Rapid increases in the computational speeds of multiprocessors have not been matched by correspond-ing performance enhancements in the I/O subsystem. To satisfy the large and growing I/O requirements of some parallel scientific applications, we need parallel file systems that can provide high-bandwidth and high-v01ume data transfer between tth I/O subsystem and thousands of processors. Design of such high-performance parallel file systems depends on a thorough grasp of the expected " workload. So far there have been no-comprehensive usage studies of multiprocessor file systems. Our _. CHARISMA project intends to fill this void. The first results from our study involve an iPSC/860 at.. _i ",-' NASA Ames. This paper presents results from a different platform, the CM-5 at the National Center for Supercomputing Applications. The CHARISMA studies are unique because we collect information about every individual read and write request and about the entire mix of applications running on the machines. The results of our trace analysis lead to recommendations for parallel file system design. First, the file system should support efficient concurrent access to many files, and UO requests from many jobs

The functionality and performance innovations in file systems and storage systems have proceeded largely independently from each other over the past years. The result is an information gap: neither has information about how the other is designed or implemented, which can result in a high cost of maintenance, poor performance, duplication of features, and limitations on functionality. To bridge this gap, we introduce and evaluate a new division of labor between the storage system and the file system. We develop an enhanced storage layer known as Exposed RAID (ERAID), which reveals information to file systems built above; specifically, ERAID exports the parallelism and failure-isolation boundaries of the storage layer, and tracks performance and failure characteristics on a fine-grained basis. To take advantage of the information made available by ERAID, we develop an Informed Log-Structured File System (ILFS). ILFS is an extension of the standard logstructured file system (LFS) that has been altered to take advantage of the performance and failure information exposed by ERAID. Experiments reveal that our prototype implementation yields benefits in the management, flexibility, reliability, and performance of the storage system, with only a small increase in file system complexity. For example, ILFS/ERAID can incorporate new disks into the system on-the-fly, dynamically balance workloads across the disks of the system, allow for user control of file replication, and delay replication of files for increased performance. Much of this functionality would be difficult or impossible to implement with the traditional division of labor between file systems and storage.

We describe TPIE, a Transparent Parallel I/O Environment. TPIE is a system designed to bridge the gap between current theoretical knowledge about the construction of I/O-optimal algorithms on parallel disk systems and the design and implementation of parallel I/O systems. We discuss the design of TPIE and its interface, the structure of a typical implementation, applications of the system, our prototype, and future research directions. The initial goal of our work is a prototype system to demonstrate: 1) that optimal algorithms can be made to run efficiently on parallel I/O devices; and 2) that high level hardware independent interfaces to the I/O paradigms required to implement such algorithms can be provided to application programmers. The TPIE interface is designed to be portable across a variety of parallel hardware platforms; thus code that runs efficiently on one machine will run efficiently on others. Longer term goals for TPIE include extending the prototype in ways t...

In the past couple of years, significant progress has been made in the development of message-passing libraries for parallel and distributed computing, and in the area of high-speed networking. These advances in computing technology have also led to a tremendous increase in the amount of data being manipulated and produced by scientific and commercial application programs. Despite their popularity, message-passing libraries only provide part of the support necessary for most high performance distributed computing applications -- support for high speed parallel I/O is still lacking. In this paper, we provide an overview of the conceptual design of a parallel and distributed I/O file system, the Virtual Parallel File System (VIP-FS), and describe its implementation. VIP-FS makes use of message-passing libraries to provide a parallel and distributed file system which can execute over multiprocessor machines or heterogeneous network environments.

As parallel computers are increasingly used to run scienti c applications with large data sets, and as processor speeds continue to increase, it becomes more important to provide fast, e ective parallel le systems for data storage and for temporary les. In an earlier work we demonstrated that a technique we call disk-directed I/O has the potential to provide consistent high performance for large, collective, structured I/O requests. In this paper we expand on this potential by demonstrating the ability of a disk-directed I/O system to read irregular subsets of data from a le, and to lter and distribute incoming data according to data-dependent functions. 1

The HURRICANE File System (HFS) is designed for large-scale, shared-memory multiprocessors. Its architecture is based on the principle that a file system must support a wide variety of file structures, file system policies and I/O interfaces to maximize performance for a wide variety of applications. HFS uses a novel, object-oriented building-block approach to provide the flexibility needed to support this variety of file structures, policies, and I/O interfaces. File structures can be defined in HFS that optimize for sequential or random access, read-only, write-only or read/write access, sparse or dense data, large or small file sizes, and different degrees of application concurrency. Policies that can be defined on a per-file or per-open instance basis include locking policies, prefetching policies, compression/decompression policies and file cache management policies. In contrast, most existing file systems have been designed to support a single file structure and a small set of po...