Sequential access

Abstract: A scalable access filter that is used together with others like it in a virtual private network to control access by users at clients in the network to information resources provided by servers in the network. Each access filter uses a local copy of an access control data base to determine whether an access request is made by a user. Changes made by administrators in the local copies are propagated to all of the other local copies. Each user belongs to one or more user groups and each information resource belongs to one or more information sets. Access is permitted or denied according to of access policies which define access in terms of the user groups and information sets. The rights of administrators are similarly determined by administrative policies. Access is further permitted only if the trust levels of a mode of identification of the user and of the path in the network by which the access is made are sufficient for the sensitivity level of the information resource. If necessary, the access filter automatically encrypts the request with an encryption method whose trust level is sufficient. The first access filter in the path performs the access check and encrypts and authenticates the request; the other access filters in the path do not repeat the access check.

Abstract: Set-associative caches achieve low miss rates for typical applications but result in significant energy dissipation. Set-associative caches minimize access time by probing all the data ways in parallel with the tag lookup, although the output of only the matching way is used. The energy spent accessing the other ways is wasted Eliminating the wasted energy by performing the data lookup sequentially following the tag lookup substantially increases cache access time, and is unacceptable for high-performance L1 caches. In this paper, we apply two previously-proposed techniques, way-prediction and selective direct-mapping, to reducing L1 cache dynamic energy while maintaining high performance. The techniques predict the matching way and probe only the predicted way and not all the ways, achieving energy savings. While these techniques were originally proposed to improve set-associative cache access times, this is the first paper to apply them to reducing cache energy. We evaluate the effectiveness of these techniques in reducing L1 d-cache, L1 i-cache, and overall processor energy. Using these techniques, our caches achieve the energy-delay of sequential access while maintaining the performance of parallel access. Relative to parallel access L1 i- and d-caches, the techniques achieve overall processor energy-delay reduction of 8%, while perfect way-prediction with no performance degradation achieves 10% reduction. The performance degradation of the techniques is less than 3%, compared to an aggressive,.1-cycle, 4-way, parallel access cache.

Abstract: Fast access to files of integers is crucial for the efficient resolution of queries to databases. Integers are the basis of indexes used to resolve queries, for example, in large internet search systems, and numeric data forms a large part of most databases, Disk access costs can be reduced by compression, if the cost of retrieving a compressed representation from disk and the CPU cost of decoding such a representation is less than that of retrieving uncompressed data. In this paper we show experimentally that, for large or small collections, storing integers in a compressed format reduces the time required for either sequential stream access or random access. We compare different approaches to compressing integers, including the Elias gamma and delta codes, Golomb coding, and a variable-byte integer scheme. As a conclusion, we recommend that, for fast access to integers, files be stored compressed.

Abstract: Accurately fetching data objects or pages in advance of their use is a powerful means of improving performance, but this capability has been difficult to realize. Current OODBs maintain object caches that employ fetch and replacement policies derived from those used for virtual-memory demand paging. These policies usually assume no knowledge of the future. Object cache managers often employ demand fetching combined with data clustering to effect prefetching, but cluster prefetching can be ineffective when the access patterns serviced are incompatible. This paper describes FIDO, an experimental {\em predictive cache} that predicts access for individuals during a session by employing an associative memory to assimilate regularities in the access pattern of an individual over time. By dint of continual training, the associative memory adapts to changes in the database and in the user''s access pattern, enabling on-line access predictions for prefetching. We discuss two salient components of Fido: \begin{enumerate} \item MLP, a replacement policy for managing pre-fetched objects. \item Estimating Prophet, an associative memory that recognizes patterns in access sequences adaptively over time and provides on-line predictions used for prefetching. \end{enumerate} We then present some early simulation thatts which suggest that predictive caching works well, especially for sequential access patterns, and conclude that predictive caching holds great promise.