ICL Technical Journal 4(4): CAFS-ISP

The special issue of the ICL Technical Journal on CAFS-ISP. This closely followed the award to ICL of the Queen's Award for Technology in April, 1985. The contents include the history of the hardware and software, its status and future, perspectives from leading developers and users, and a list of related patents

High efficiency, character-oriented, local area networks

Imperial Users onl

Database machines in support of very large databases

Software database management systems were developed in response to the needs of early data processing applications. Database machine research developed as a result of certain performance deficiencies of these software systems. This thesis discusses the history of database machines designed to improve the performance of database processing and focuses primarily on the Teradata DBC/1012, the only successfully marketed database machine that supports very large databases today. Also reviewed is the response of IBM to the performance needs of its database customers; this response has been in terms of improvements in both software and hardware support for database processing. In conclusion, an analysis is made of the future of database machines, in particular the DBC/1012, in light of recent IBM enhancements and its immense customer base

Extending functional databases for use in text-intensive applications

This thesis continues research exploring the benefits of using functional databases based around the functional data model for advanced database applications-particularly those supporting investigative systems. This is a growing generic application domain covering areas such as criminal and military intelligence, which are characterised by significant data complexity, large data sets and the need for high performance, interactive use. An experimental functional database language was developed to provide the requisite semantic richness. However, heavy use in a practical context has shown that language extensions and implementation improvements are required-especially in the crucial areas of string matching and graph traversal. In addition, an implementation on multiprocessor, parallel architectures is essential to meet the performance needs arising from existing and projected database sizes in the chosen application area. [Continues.

State of the art survey of network operating systems development

The results of the State-of-the-Art Survey of Network Operating Systems (NOS) performed for Goddard Space Flight Center are presented. NOS functional characteristics are presented in terms of user communication data migration, job migration, network control, and common functional categories. Products (current or future) as well as research and prototyping efforts are summarized. The NOS products which are revelant to the space station and its activities are evaluated

Parallel execution of horn claus programs

Imperial Users onl

Virtual files: a Framework for Experimental Design

The increasing power and decreasing cost of computers has resulted in them being applied in an ever widening area. In the world of Computer Aided Design it is now practicable to involve the machine in the earlier stages where a design is still speculative, as well as in the later stages where the computer's calculating ability becomes paramount. Research on database systems has not followed this trend, concentrating instead on commercial applications, with the result that there are very few systems targeted at the early stages of the design process. In this thesis we consider the design and implementation of the file manager for such a system, first of all from the point of view of a single designer working on an entire design, and then from the point of view of a team of designers, each working on a separate aspect of a design. We consider the functionality required of the type of system we are proposing, defining the terminology of experiments to describe it. Having ascertained our requirements we survey current database technology in order to determine to what extent it meets our requirements. We consider traditional concurrency control methods and conclude that they are incompatible with our requirements. We consider current data models and conclude that, with the exception of the persistent programming model, they are not appropriate in the context required, while the implementation of the persistent programming model provides transactions on data structures but not experiments. The implementation of experiments is considered. We examine a number of potential methods, deciding on differential files as the one most likely both to meet our requirements and to have the lowest overheads. Measurements conducted on both a preliminary and a full-scale implementation confirm that this is the case. There are, nevertheless, further gains in convenience and performance to be obtained by exploiting the capabilities of the hardware to the full; we discuss these in relation to virtual memory systems, with particular reference to the VAX/VMS environment. Turning to the case where several designers are each working on a (nearly) distinct part of a design, we consider how to detect conflicts between experiments. Basing our approach on optimistic concurrency control methods, we show how read and write sets may be used to determine those areas of the database where conflicts might arise. As an aside, we show how the methods we propose can be used in an alternative approach to optimistic concurrency control, giving a reduction in system overheads for certain applications. We consider implementation techniques, concluding that a differential files approach has significant advantages in maintaining write sets, while a two-level bitmap may be used to maintain read sets efficiently

Data-intensive Systems on Modern Hardware : Leveraging Near-Data Processing to Counter the Growth of Data

Over the last decades, a tremendous change toward using information technology in almost every daily routine of our lives can be perceived in our society, entailing an incredible growth of data collected day-by-day on Web, IoT, and AI applications. At the same time, magneto-mechanical HDDs are being replaced by semiconductor storage such as SSDs, equipped with modern Non-Volatile Memories, like Flash, which yield significantly faster access latencies and higher levels of parallelism. Likewise, the execution speed of processing units increased considerably as nowadays server architectures comprise up to multiple hundreds of independently working CPU cores along with a variety of specialized computing co-processors such as GPUs or FPGAs. However, the burden of moving the continuously growing data to the best fitting processing unit is inherently linked to today’s computer architecture that is based on the data-to-code paradigm. In the light of Amdahl's Law, this leads to the conclusion that even with today's powerful processing units, the speedup of systems is limited since the fraction of parallel work is largely I/O-bound. Therefore, throughout this cumulative dissertation, we investigate the paradigm shift toward code-to-data, formally known as Near-Data Processing (NDP), which relieves the contention on the I/O bus by offloading processing to intelligent computational storage devices, where the data is originally located. Firstly, we identified Native Storage Management as the essential foundation for NDP due to its direct control of physical storage management within the database. Upon this, the interface is extended to propagate address mapping information and to invoke NDP functionality on the storage device. As the former can become very large, we introduce Physical Page Pointers as one novel NDP abstraction for self-contained immutable database objects. Secondly, the on-device navigation and interpretation of data are elaborated. Therefore, we introduce cross-layer Parsers and Accessors as another NDP abstraction that can be executed on the heterogeneous processing capabilities of modern computational storage devices. Thereby, the compute placement and resource configuration per NDP request is identified as a major performance criteria. Our experimental evaluation shows an improvement in the execution durations of 1.4x to 2.7x compared to traditional systems. Moreover, we propose a framework for the automatic generation of Parsers and Accessors on FPGAs to ease their application in NDP. Thirdly, we investigate the interplay of NDP and modern workload characteristics like HTAP. Therefore, we present different offloading models and focus on an intervention-free execution. By propagating the Shared State with the latest modifications of the database to the computational storage device, it is able to process data with transactional guarantees. Thus, we achieve to extend the design space of HTAP with NDP by providing a solution that optimizes for performance isolation, data freshness, and the reduction of data transfers. In contrast to traditional systems, we experience no significant drop in performance when an OLAP query is invoked but a steady and 30% faster throughput. Lastly, in-situ result-set management and consumption as well as NDP pipelines are proposed to achieve flexibility in processing data on heterogeneous hardware. As those produce final and intermediary results, we continue investigating their management and identified that an on-device materialization comes at a low cost but enables novel consumption modes and reuse semantics. Thereby, we achieve significant performance improvements of up to 400x by reusing once materialized results multiple times