Disk-Directed I/O for MIMD Multiprocessors

Many scientific applications that run on today\u27s multiprocessors 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 improved 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, \em disk-directed I/O, that flips the usual relationship between server and client to allow the disks (actually, 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, and close to the maximum disk bandwidth

Disk-directed I/O for MIMD Multiprocessors

Many scientific applications that run on today\u27s multiprocessors 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 improved 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, that flips the usual relationship between server and client to allow the disks (actually, 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, and close to the maximum disk bandwidth

Interfaces for Disk-Directed I/O

In other papers I propose the idea of disk-directed I/O for multiprocessor file systems. Those papers focus on the performance advantages and capabilities of disk-directed I/O, but say little about the application-programmer\u27s interface or about the interface between the compute processors and I/O processors. In this short note I discuss the requirements for these interfaces, and look at many existing interfaces for parallel file systems. I conclude that many of the existing interfaces could be adapted for use in a disk-directed I/O system

Hyperswitch communication network

The Hyperswitch Communication Network (HCN) is a large scale parallel computer prototype being developed at JPL. Commercial versions of the HCN computer are planned. The HCN computer being designed is a message passing multiple instruction multiple data (MIMD) computer, and offers many advantages in price-performance ratio, reliability and availability, and manufacturing over traditional uniprocessors and bus based multiprocessors. The design of the HCN operating system is a uniquely flexible environment that combines both parallel processing and distributed processing. This programming paradigm can achieve a balance among the following competing factors: performance in processing and communications, user friendliness, and fault tolerance. The prototype is being designed to accommodate a maximum of 64 state of the art microprocessors. The HCN is classified as a distributed supercomputer. The HCN system is described, and the performance/cost analysis and other competing factors within the system design are reviewed

Dynamic File-Access Characteristics of a Production Parallel Scientific Workload

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 characteristics of the expected workload, but until now there have been no comprehensive workload characterizations of multiprocessor file systems. We began the CHARISMA project in an attempt to fill that gap. We instrumented the common node library on the iPSC/860 at NASA Ames to record all file-related activity over a two-week period. Our instrumentation is different from previous efforts in that it collects information about every read and write request and about the mix of jobs running in the machine (rather than from selected applications). The trace analysis in this paper leads to many recommendations for designers of multiprocessor file systems. First, the file system should support simultaneous access to many different files by many jobs. Second, it should expect to see many small requests, predominantly sequential and regular access patterns (although of a different form than in uniprocessors), little or no concurrent file-sharing between jobs, significant byte- and block-sharing between processes within jobs, and strong interprocess locality. Third, our trace-driven simulations showed that these characteristics led to great success in caching, both at the compute nodes and at the I/O nodes. Finally, we recommend supporting strided I/O requests in the file-system interface, to reduce overhead and allow more performance optimization by the file system

Computational methods and software systems for dynamics and control of large space structures

Two key areas of crucial importance to the computer-based simulation of large space structures are discussed. The first area involves multibody dynamics (MBD) of flexible space structures, with applications directed to deployment, construction, and maneuvering. The second area deals with advanced software systems, with emphasis on parallel processing. The latest research thrust in the second area involves massively parallel computers

Three Highly Parallel Computer Architectures and Their Suitability for Three Representative Artificial Intelligence Problems

Virtually all current Artificial Intelligence (AI) applications are designed to run on sequential (von Neumann) computer architectures. As a result, current systems do not scale up. As knowledge is added to these systems, a point is reached where their performance quickly degrades. The performance of a von Neumann machine is limited by the bandwidth between memory and processor (the von Neumann bottleneck). The bottleneck is avoided by distributing the processing power across the memory of the computer. In this scheme the memory becomes the processor (a smart memory ). This paper highlights the relationship between three representative AI application domains, namely knowledge representation, rule-based expert systems, and vision, and their parallel hardware realizations. Three machines, covering a wide range of fundamental properties of parallel processors, namely module granularity, concurrency control, and communication geometry, are reviewed: the Connection Machine (a fine-grained SIMD hypercube), DADO (a medium-grained MIMD/SIMD/MSIMD tree-machine), and the Butterfly (a coarse-grained MIMD Butterflyswitch machine)

Mapping of portable parallel programs

An efficient parallel program designed for a parallel architecture includes a detailed outline of accurate assignments of concurrent computations onto processors, and data transfers onto communication links, such that the overall execution time is minimized. This process may be complex depending on the application task and the target multiprocessor architecture. Furthermore, this process is to be repeated for every different architecture even though the application task may be the same. Consequently, this has a major impact on the ever increasing cost of software development for multiprocessor systems. A remedy for this problem would be to design portable parallel programs which can be mapped efficiently onto any computer system. In this dissertation, we present a portable programming tool called Cluster-M. The three components of Cluster-M are the Specification Module, the Representation Module, and the Mapping Module. In the Specification Module, for a given problem, a machine-independent program is generated and represented in the form of a clustered task graph called Spec graph. Similarly, in the Representation Module, for a given architecture or heterogeneous suite of computers, a clustered system graph called Rep graph is generated. The Mapping Module is responsible for efficient mapping of Spec graphs onto Rep graphs. As part of this module, we present the first algorithm which produces a near-optimal mapping of an arbitrary non-uniform machine-independent task graph with M modules, onto an arbitrary non-uniform task-independent system graph having N processors, in 0(M P) time, where P = max(M, N). Our experimental results indicate that Cluster-M produces better or similar mapping results compared to other leading techniques which work only for restricted task or system graphs

System software for the finite element machine

The Finite Element Machine is an experimental parallel computer developed at Langley Research Center to investigate the application of concurrent processing to structural engineering analysis. This report describes system-level software which has been developed to facilitate use of the machine by applications researchers. The overall software design is outlined, and several important parallel processing issues are discussed in detail, including processor management, communication, synchronization, and input/output. Based on experience using the system, the hardware architecture and software design are critiqued, and areas for further work are suggested

Disk-directed I/O for an Out-of-Core Computation

New file systems are critical to obtain good I/O performance on large multiprocessors. Several researchers have suggested the use of collective file-system operations, in which all processes in an application cooperate in each I/O request. Others have suggested that the traditional low-level interface (read, write, seek) be augmented with various higher-level requests (e.g., read matrix), allowing the programmer to express a complex transfer in a single (perhaps collective) request. Collective, high-level requests permit techniques like two-phase I/O and disk-directed I/O to significantly improve performance over traditional file systems and interfaces. Neither of these techniques have been tested on anything other than simple benchmarks that read or write matrices. Many applications, however, intersperse computation and I/O to work with data sets that cannot fit in main memory. In this paper, we present the results of experiments with an ``out-of-core\u27\u27 LU-decomposition program, comparing a traditional interface and file system with a system that has a high-level, collective interface and disk-directed I/O. We found that a collective interface was awkward in some places, and forced additional synchronization. Nonetheless, disk-directed I/O was able to obtain much better performance than the traditional system