10542450
Capturing dynamic memory reference behavior with adaptive cache topology
Memory references exhibit locality and are therefore not uniformly distributed across the sets of a cache. This skew reduces the effectiveness of a cache because it results in the caching of a considerable number of less-recently-used lines which are less likely to be re-referenced before they are replaced. In this paper, we describe a technique that dynamically identifies these less-recently-used lines and effectively utilizes the cache frames they occupy to more accurately approximate the global least-recently-used replacement policy while maintaining the fast access time of a direct-mapped cache. We also explore the idea of using these underutilized cache frames to reduce cache misses through data prefetching. In the proposed design, the possible locations that a line can reside in is not predetermined. Instead, the cache is dynamically partitioned into groups of cache lines. Because both the total number of groups and the individual group associativity adapt to the dynamic reference pattern, we call this design the adaptive group-associative cache. Performance evaluation using trace-driven simulations of the TPC-C benchmark and selected programs from the SPEC95 benchmark suite shows that the group-associative cache is able to achieve a hit ratio that is consistently better than that of a 4-way set-associative cache. For some of the workloads, the hit ratio approaches that of a fully-associative cache.
6036700
Functional Implementation Techniques for CPU Cache Memories
As the performance gap between processors and main memory continues to widen, increasingly aggressive implementations of cache memories are needed to bridge the gap. In this paper, we consider some of the issues that are involved in the implementation of highly optimized cache memories and survey the techniques that can be used to help achieve the increasingly stringent design targets and constraints of modern processors. In particular, we consider techniques that enable the cache to be accessed quickly and still achieve a good hit ratio. We also consider issues such as area cost and bandwidth requirements. Trace-driven simulations of a TPC-C-like workload and selected applications from the SPEC95 benchmark suite are used in the paper to compare the performance of some of the techniques.
14423694
Characteristics of I/O traffic in personal computer and server workloads
Understanding the characteristics of I/O traffic is increasingly important as the performance gap between the processor and disk-based storage continues to widen. Moreover, recent advances in technology, coupled with market demands, have led to new and exciting developments in storage systems, particularly network storage, storage utilities, and intelligent self-optimizing storage. In this paper, we empirically examine the physical I/O traffic of a wide range of server and personal computer (PC) workloads, focusing on how these workloads will be affected by the recent developments in storage systems. As part of our analysis, we compare our results with historical data and re-examine some rules of thumb (e.g., one bit of I/O per second for each instruction per second of processing power) that have been widely used for designing computer systems. We find that the I/O traffic is bursty and appears to exhibit self-similar characteristics. Our analysis also indicates that there is little cross-correlation between traffic volumes of server workloads, which suggests that aggregating these workloads will likely help to smooth out the traffic and enable more efficient utilization of resources. We discover that there is significant potential for harnessing "free" system resources to perform background tasks such as optimization of disk block layout. In general, we observe that the characteristics of the I/O traffic are relatively insensitive to the extent of upstream caching, and thus our results still apply, on a qualitative level, when the upstream cache is increased in size.
308038
Projecting the performance of decision support workloads on systems with smart storage (SmartSTOR)
Recent developments in both hardware and software have made it worthwhile to consider embedding intelligence in storage to handle general-purpose processing that can be off-loaded from the hosts. In particular, low-cost processing power is now widely available and software can be made robust, secure and mobile. In this paper, we propose a general smart storage (SmartSTOR) architecture in which a processing unit that is coupled to one or more disks can be used to perform such off-loaded processing. A major part of the paper is devoted to understanding the performance potential of the SmartSTOR architecture for decision support workloads. Our analysis suggests that there is a definite performance advantage in using fewer but more powerful processors, a result that bolsters the case for sharing a powerful processor among multiple disks. As for software architecture, we find that the off-loading of database operations that involve only a single relation is not very promising. In order to achieve significant speed-up, we have to consider the off-loading of multiple-relation operations. In general, if embedding intelligence in storage is an inevitable architectural trend, we have to focus on developing parallel software systems that can effectively take advantage of the large number of processing units that will be in the system.
7063986
Fossilized index: the linchpin of trustworthy non-alterable electronic records
As critical records are increasingly stored in electronic form, which tends to make for easy destruction and clandestine modification, it is imperative that they be properly managed to preserve their trustworthiness, i.e., their ability to provide irrefutable proof and accurate details of events that have occurred. The need for proper record keeping is further underscored by the recent corporate misconduct and ensuing attempts to destroy incriminating records. Currently, the industry practice and regulatory requirements (e.g., SEC Rule 17a-4) rely on storing records in WORM storage to immutably preserve the records. In this paper, we contend that simply storing records in WORM storage is increasingly inadequate to ensure that they are trustworthy. Specifically, with the large volume of records that are typical today, meeting the ever more stringent query response time requires the use of direct access mechanisms such as indexes. Relying on indexes for accessing records could, however, provide a means for effectively altering or deleting records, even those stored in WORM storage.In this paper, we establish the key requirements for a fossilized index that protects the records from such logical modification. We also analyze current indexing methods to determine how they fall short of these requirements. Based on our insights, we propose the Generalized Hash Tree (GHT). Using both theoretical analysis and simulations with real system data, we demonstrate that the GHT can satisfy the requirements of a fossilized index with performance and cost that are comparable to regular indexing techniques such as the B-tree. We further note that as records are indexed on multiple fields to facilitate search and retrieval, the records can be reconstructed from the corresponding index entries even after the records expire and are disposed of, Therefore, we also present a novel method to eliminate this disclosure risk by allowing an index entry to be effectively disposed of when its record expires.
2578042
Trustworthy keyword search for regulatory-compliant records retention
Recent litigation and intense regulatory focus on secure retention of electronic records have spurred a rush to introduce Write-Once-Read-Many (WORM) storage devices for retaining business records such as electronic mail. However, simply storing records in WORM storage is insuffcient to ensure that the records are trustworthy, i.e., able to provide irrefutable proof and accurate details of past events. Specifically, some form of index is needed for timely access to the records, but unless the index is maintained securely, the records can in effect be hidden or altered, even if stored in WORM storage. In this paper, we systematically analyze the requirements for establishing a trustworthy inverted index to enable keyword-based search queries. We propose a novel scheme for effcient creation of such an index and demonstrate, through extensive simulations and experiments with an enterprise keyword search engine, that the scheme can achieve online update speeds while maintaining good query performance. In addition, we present a secure index structure for multi-keyword queries that supports insert, lookup and range queries in time logarithmic in the number of documents.
1251407
Reference metadata extraction using a hierarchical knowledge representation framework
The integration of bibliographical information on scholarly publications available on the Internet is an important task in the academic community. Accurate reference metadata extraction from such publications is essential for the integration of metadata from heterogeneous reference sources. In this paper, we propose a hierarchical template-based reference metadata extraction method for scholarly publications. We adopt a hierarchical knowledge representation framework called INFOMAP, which automatically extracts metadata. The experimental results show that, by using INFOMAP, we can extract author, title, journal, volume, number (issue), year, and page information from different kinds of reference styles with a high degree of precision. The overall average accuracy is 92.39% for the six major reference styles compared in this study.
16227528
Fast image retrieval using color-spatial information
Abstract. In this paper, we present an image retrieval system that employs both the color and spatial information of images to facilitate the retrieval process. The basic unit used in our technique is a single-colored cluster, which bounds a homogeneous region of that color in an image. Two clusters from two images are similar if they are of the same color and overlap in the image space. The number of clusters that can be extracted from an image can be very large, and it affects the accuracy of retrieval. We study the effect of the number of clusters on retrieval effectiveness to determine an appropriate value for “optimal'' performance. To facilitate efficient retrieval, we also propose a multi-tier indexing mechanism called the Sequenced Multi-Attribute Tree (SMAT). We implemented a two-tier SMAT, where the first layer is used to prune away clusters that are of different colors, while the second layer discriminates clusters of different spatial locality. We conducted an experimental study on an image database consisting of 12,000 images. Our results show the effectiveness of the proposed color-spatial approach, and the efficiency of the proposed indexing mechanism.
341424
Domain Event Extraction and Representation with Domain Ontology
With domain ontology, a meaningful index of document indexing, such as the domain events structure in this paper, can be defined. Since the construction of domain ontology is costly, an automatic domain ontology acquisition is preferred. We find that named entity can be a clue of domain event acquisition from the training corpus. Therefore , we add the named entity recognition module into the automatic domain ontology acquisition process. Thus, a subject-verb-object-modifier (SVOM) indexing can be constructed. Our experimental results demonstrate that the automatic event extraction and ontology acquisition can be good resources for text categorization and further information processing.
1049682
An Empirical Comparison of Runtime Systems for Conservative Parallel Simulation
A main consideration when implementing a parallel simulation application is the choice of the parallel simulation protocol (conservative vs. optimistic). Given a particular protocol, the application programmer then has to determine a suitable parallel runtime system to implement the application. If the choice is an optimistic protocol, there are several parallel simulation libraries intended for application programmers (e.g. GTW, Warped). For a conservative protocol, the most effective approach is for the programmer to use a general parallel runtime library, and implement optimizations specific to the simulation application and/or model. In this paper, we selected four general parallel runtime libraries potentially relevant to parallel simulations, and implemented a conservative protocol on each of them. We study the four libraries on three main aspects: (a) programmability; (b) performance, and (c) mechanisms for performance tuning. Our target platforms are machines supporting shared address spaces (e.g. SGI Origin200, Sun Enterprise 3000), and we obtained performance figures from a 4-CPU Ultra2 Sun Enterprise 3000. From our experiments, we find that POSIX, though an industry standard, still has relatively high overheads, and cannot efficiently support a protocol with fine-grain LPs. The research libraries all show speedups on 4 processors, but to different extents. Cilk speedup curves improves with larger thread granularity, while Active threads show relatively good speedup even for small thread granularity. BSP processes are naturally coarse-grained, and thus good speedup is achieved in our simulation application.
9763838
Generative, discriminative, and ensemble learning on multi-modal perceptual fusion toward news video story segmentation
News video story segmentation is a critical task for automatic video indexing and summarization. Our prior work has demonstrated promising performance by using a generative model, called maximum entropy (ME), which models the posterior probability given the multi-modal perceptual features near the candidate points. In this paper, we investigate alternative statistical approaches based on discriminative models, i.e. support vector machine (SVM), and ensemble learning, i.e. boosting. In addition, we develop a novel approach, called BoostME, which uses the ME classifiers and the associated confidence scores in each boosting iteration. We evaluated these different methods using the TRECVID 2003 broadcast news data set. We found that SVM-based and ME-based techniques both outperformed the pure boosting techniques, with the SVM-based solutions achieving even slightly higher accuracy. Moreover, we summarize extensive analysis results of error sources over distinctive news story types to identify future research opportunities