7906272
Coordinating Parallel Processes on Networks of Workstations
The network of workstations (NOW) we consider for scheduling is heterogeneous and nondedicated, where computing power varies among the workstations and local and parallel jobs may interact with each other in execution. An effective NOW scheduling scheme needs sufficient information about system heterogeneity and job interactions. We use the measured power weight of each workstation to quantify the differences of computing capability in the system. Without a processing power usage agreement between parallel jobs and local user jobs in a workstation, job interactions are unpredictable, and performance of either type of jobs may not be guaranteed. Using the quantified and deterministic system information, we design a scheduling scheme calledself-coordinated local schedulingon a heterogeneous NOW. Based on a power usage agreement between local and parallel jobs, this scheme coordinates parallel processes independently in each workstation based on the coscheduling principle. We discuss its implementation on Unix System V Release 4 (SVR4). Our simulation results on a heterogeneous NOW show the effectiveness of the self-coordinated local scheduling scheme.
1520083
Token-ordered LRU: an effective page replacement policy and its implementation in Linux systems
Most computer systems use a global page replacement policy based on the LRU principle to approximately select a Least Recently Used page for a replacement in the entire user memory space. During execution interactions, a memory page can be marked as LRU even when its program is conducting page faults. We define the LRU pages under such a condition as false LRU pages because these LRU pages are not produced by program memory reference delays, which is inconsistent with the LRU principle. False LRU pages can significantly increase page faults, even cause system thrashing. This poses a more serious risk in a large parallel systems with distributed memories because of the existence of coordination among processes running on individual node. In the case, the process thrashing in a single node or a small number of nodes could severely affect other nodes running coordinating processes, even crash the whole system. In this paper, we focus on how to improve the page replacement algorithm running on one node. After a careful study on characterizing the memory usage and the thrashing behaviors in the multi-programming system using LRU replacement. we propose an LRU replacement alternative, called token-ordered LRU, to eliminate or reduce the unnecessary page faults by effectively ordering and scheduling memory space allocations. Compared with traditional thrashing protection mechanisms such as load control, our policy allows more processes to keep running to support synchronous distributed process computing. We have implemented the token-ordered LRU algorithm in a Linux kernel to show its effectiveness.
1459531
SmartSaver: Turning Flash Drive into a Disk Energy Saver for Mobile Computers
In a mobile computer the hard disk consumes a considerable amount of energy. Existing dynamic power management policies usually take conservative approaches to save disk energy, and disk energy consumption remains a serious issue. Meanwhile, the flash drive is becoming a must-have portable storage device for almost every laptop user on travel. In this paper, we propose to make another highly desired use of the flash drive - saving disk energy. This is achieved by using the flash drive as a standby buffer for caching and prefetching disk data. Our design significantly extends disk idle times with careful and deliberate consideration of the particular characteristics of the flash drive. Trace-driven simulations show that up to 41% of disk energy can be saved with a relatively small amount of data written to the flash drive
14511182
Does internet media traffic really follow Zipf-like distribution?
It is commonly agreed that Web traffic follows the Zipf-like distribution, which is an analytical foundation for improving Web access performance by client-server based proxy caching systems on the Internet. However, some recent studies have observed non-Zipf-like distributions of Internet media traffic in different content delivery systems. Due to the variety of media delivery systems and the diversity of media content, existing studies on media traffic are largely workload specific, and the observed access patterns are often different from or even conflict with each other. For Web media systems, study [3] reports that the access pattern of streaming media is Zipf-like in a university campus network, while study [2] finds that it is not Zipf-like in an enterprise media server. For VoD media systems, study [1] finds that it is not Zipf-like in a multicast-based Media-on-Demand server of a campus network, while study [9] reports it is Zipf-like in a large VoD streaming system of an ISP. For P2P media systems, study [4] reports that the access pattern of media workload in KaZaa system collected in a campus network is not Zipf-like, while study [5] reports that it is Zipf-like in another campus network. For live streaming media systems, study [8] reports it is Zipf-like while study [6] reports it is not Zipf-like. A number of models have been proposed to explain the observed media access patterns, such as the generalized Zipf-like model [7], “fetch-at-most-once” model [4], and two-mode Zipf model [6]. However, each of these models can only explain a very limited scope of measurement results. A general model of Internet media access patterns is highly desirable for traffic engineering on the Internet and is critical to design, benchmark, and evaluate Internet media delivery systems. In this study, we have analyzed a wide variety of media workloads on the Internet. The workloads were collected from both the client side and the server side in Web, VoD, P2P, and live streaming environments between 1998 and 2006, where the media content is delivered via Web/P2P downloading or unicast/multicast streaming. The duration of these workloads ranges from a few days to more than two years and the user population ranges from several thousands to more than one hundred thousand. The number of client requests
6763495
Memory Hierarchy Considerations for Cost-Effective Cluster Computing
Using off-the-shelf commodity workstations and PCs to build a cluster for parallel computing has become a common practice. The cost-effectiveness of a cluster computing platform for a given budget and for certain types of applications is mainly determined by its memory hierarchy and the interconnection network configurations of the cluster. Finding such a cost-effective solution from exhaustive simulations would be highly time-consuming and predictions from measurements on existing clusters would be impractical. We present an analytical model for evaluating the performance impact of memory hierarchies and networks on cluster computing. The model covers the memory hierarchy of a single SMP, a cluster of workstations/PCs, or a cluster of SMPs by changing various architectural parameters. Network variations covering both bus and switch networks are also included in the analysis. Different types of applications are characterized by parameterized workloads with different computation and communication requirements. The model has been validated by simulations and measurements. The workloads used for experiments are both scientific applications and commercial workloads. Our study shows that the depth of the memory hierarchy is the most sensitive factor affecting the execution time for many types of workloads. However, the interconnection network cost of a tightly coupled system with a short depth in memory hierarchy, such as an SMP, is significantly more expensive than a normal cluster network connecting independent computer nodes. Thus, the essential issue to be considered is the trade-off between the depth of the memory hierarchy and the system cost. Based on analyses and case studies, we present our quantitative recommendations for building cost-effective clusters for different workloads.
10102756
Semi-Empirical Multiprocessor Performance Predictions
This paper presents a multiprocessor performance prediction methodology supported by experimental measurements, which predicts the execution time of large application programs on large parallel architectures based on a small set of sample data. We propose a graph model to describe application program behavior. In order to precisely abstract an architecture model for the prediction, important and implicit architecture parameters are obtained by experiments. We focus on performance predictions of application programs in shared-memory and data-parallel architectures. Real world applications are implemented using the shared-memory model on the KSR-1 and using the data-parallel model on the CM-5 for performance measurements and prediction validation. We show that experimental measurements provide strong support for performance predictions on multiprocessors with implicit communications and complex memory systems, such as shared-memory and data-parallel systems, while analytical techniques partially applied in the prediction significantly reduce computer simulation and measurement time.
6947307
Design of IIR orthogonal wavelet filter banks using lifting scheme
The lifting scheme is well known to be an efficient tool for constructing second generation wavelets and is often used to design a class of biorthogonal wavelet filter banks. For its efficiency, the lifting implementation has been adopted in the international standard JPEG2000. It is known that the orthogonality of wavelets is an important property for many applications. This paper presents how to implement a class of infinite-impulse-response (IIR) orthogonal wavelet filter banks by using the lifting scheme with two lifting steps. It is shown that a class of IIR orthogonal wavelet filter banks can be realized by using allpass filters in the lifting steps. Then, the design of the proposed IIR orthogonal wavelet filter banks is discussed. The designed IIR orthogonal wavelet filter banks have approximately linear phase responses. Finally, the proposed IIR orthogonal wavelet filter banks are applied to the image compression, and then the coding performance of the proposed IIR filter banks is evaluated and compared with the conventional wavelet transforms
8353152
An Efficient Algorithm for Mining Coherent Patterns from Heterogeneous Microarrays
DNA microarray techniques present a novel way for geneticists to monitor interactions among tens of thousands of genes simultaneously, and have become standard lab routines in gene discovery, disease diagnosis, and drug design. There has been extensive research on coherent subspace clustering of gene expressions measured under consistent experimental settings. This implies that all experiments are run using the same batch of microarray chips with similar characteristics of noise. Algorithms developed under this assumption may not be applicable for analyzing data collected from heterogeneous settings, where the set of genes being monitored may be different and expression levels may be not directly comparable even for the same gene. In this paper, we propose a model, F-cluster, for mining subspace coherent patterns from heterogeneous gene expression data, which is shown effective for revealing truthful patterns and reducing spurious ones. We also develop an efficient and scalable hybrid approach that combines gene-pair based and sample-pair based pruning to generate F-clusters from multiple gene expression matrices simultaneously. The experimental results demonstrate that our model can discover significant clusters that may not be identified by previous models.
1109125
An on-demand Bluetooth scatternet formation and routing protocol for wireless sensor networks
Bluetooth is a promising short-range wireless communication technology with the characteristics of interference resilience and power efficiency which are required by wireless sensor networks. As an enhanced sensor node platform, the Intel Mote uses Bluetoth as its radio scheme and MAC protocol. However, most of the existing scatternet formation protocols intend to connect all the nodes within the networks regardless of traffic pattern. For wireless sensor network applications with traffic of low duty cycle, on-demand scatternet formation and routing achieve significant power saving by avoiding to maintain the entire network connectivity. We propose in this paper an on-demand scatternet and route formation protocol for Bluetooth-based wireless sensor networks. It is able to cope with multiple sources initiating traffic simultaneously in densely deployed wireless sensor networks. We also introduce a modified inquiry scheme using extended ID packet for power efficient propagation of route request messages. Furthermore, we propose a mechanism employing POLL packets in Page processes to transfer scatternet formation and route reply information without extra overhead. Simulation results show that our on-demand scatternet formation and routing protocol can provide multihop channels with reasonable delay for Bluetooth-base wireless sensor networks.
17354053
Graphs with fourth Laplacian eigenvalue less than two
In this paper, all connected graphs with the fourth largest Laplacian eigenvalue less than two are determined, which are used to characterize all connected graphs with exactly three Laplacian eigenvalues no less than two. Moreover, we determine bipartite graphs such that the adjacency matrices of their line graphs have exactly three nonnegative eigenvalues.
3393161
BIG: An agent for resource-bounded information gathering and decision making
Abstract The World Wide Web has become an invaluable information resource but the explosion of available information has made Web search a time consuming and complex process. The large number of information sources and their different levels of accessibility, reliability and associated costs present a complex information gathering control problem. This paper describes the rationale, architecture, and implementation of a next generation information gathering system—a system that integrates several areas of Artificial Intelligence research under a single umbrella. Our solution to the information explosion is an information gathering agent, BIG, that plans to gather information to support a decision process, reasons about the resource trade-offs of different possible gathering approaches, extracts information from both unstructured and structured documents, and uses the extracted information to refine its search and processing activities.