Abstract

As the complexity and variety of computer system hardware increases, its suitability as a pedagogical tool in computer organization/architecture courses diminishes. As a consequence, many instructors are turning to simulators as teaching aids, often using valuable teaching/research time to construct them. Many of these simulators have been made freely available on the Interact, providing a useful and time-saving resource for other instructors. However, finding the fight simulator for a particular course or topic can itself he a time-consuming process. The goal of this paper is to provide an easy-to-use survey of free and Internet-accessible computer system simulators as a resource for all instructors of computer organization and computer architecture courses.

ABSTRACT Testing Homotopy for Paths in the Plane ∗

In this paper we present an efficient algorithm to test if two given paths are homotopic; that is, whether they wind around obstacles in the plane in the same way. For simple paths specified by n line segments with obstacles described by n points, our algorithm runs in O(n log n) time, which we show is tight. For self-intersecting paths the problem is related to Hopcroft’s problem

Research Proposal: A Unified Approach to Scheduling in Grid Environments

Grid computing systems provide mechanisms to utilise a wide range of heterogeneous, distributed resources for compute- and data-intensive applications. In order to obtain good performance, it is necessary to select resources for use in such a manner that minimises the computation and communication time. The process of scheduling, or deciding which resources to use, has been explored for many different types of grids and applications. Three types of scheduling are used: computation scheduling, involving selecting hosts to execute a program, data scheduling, determining the placement of data for efficient access, and service scheduling, the selection of a remote host on which to access a particular service. Existing schedulers generally focus on only one of these types, and do not consider the interaction between them. We propose a model for scheduling grid applications based on the problem of assigning the schedulable entities of a grid application to resources. These entities represent the computation, data and service components of an application. Information about these entities and the relationships between them will be taken into account when making placement decisions. Examples of such relationships include the communication between tasks, and data dependencies between tasks and files. Our investigation will include the implementation of this model in several different grid middleware systems

Efficient Data Reduction with EASE

A variety of mining and analysis problems --- ranging from association-rule discovery to contingency table analysis to materialization of certain approximate datacubes --- involve the extraction of knowledge from a set of categorical count data. Such data can be viewed as a collection of "transactions, " where a transaction is a fixed-length vector of counts. Classical algorithms for solving count-data problems require one or more computationally intensive passes over the entire database and can be prohibitively slow. One e#ective method for dealing with this ever-worsening scalability problem is to run the algorithms on a small sample of the data. We present a new data-reduction algorithm, called ease, for producing such a sample. Like the fast algorithm introduced by Chen et al., ease is especially designed for count data applications. Both ease and fast take a relatively large initial random sample and then deterministically produce a subsample whose "distance" --- appropriately defined --- from the complete database is minimal. Unlike fast, which obtains the final subsample by quasi-greedy descent, ease uses epsilon-approximation methods to obtain the final subsample by a process of repeated halving. Experiments both in the context of association rule mining and classical contingency-table analysis show that ease outperforms both fast and simple random sampling, sometimes dramatically. Categories and Subject Descriptors H.2.8 [Database Management]: Database Applications - Data Mining NSF CAREER Grant CCR-0133599