2324494
Cost-Performance Evaluation of SMP Clusters
Clusters of Personal Computers have been proposed as potential replacements for expensive compute servers. One limitation in the overall performance is the interconnection network. A possible solution is to use multiple processors on each node of the PC cluster. Parallel programs can then use the fast shared memory to exchange data within a node, and access the interconnection network to communicate across multiple nodes. The performance of such a system is likely to be influenced by the runtime support system, whether one uses a standard message passing library or a distributed shared memory system to simulate a large shared memory machine. This paper presents a cost-performance evaluation of a cluster of eight dual processor PCs and a ten processor SMP workstation using two benchmark suites. We evaluate the effect of using gigabit ethernet against fast ethernet, single processor PCs versus SMP nodes, and compare the overall performance of the PC cluster to the SMP workstation. It is found that the SMP machine provides the best performance in only 50 % of the programs examined. The PC cluster with a Gigabit network is better in most of the other cases, but the improvement over FastEthernet is marginal.
17398921
Design issues for a high-performance distributed shared memory on symmetrical multiprocessor clusters
Clusters of Symmetrical Multiprocessors (SMPs) have recently become the norm for high-performance economical computing solutions. Multiple nodes in a cluster can be used for parallel programming using a message passing library. An alternate approach is to use a software Distributed Shared Memory (DSM) to provide a view of shared memory to the application programmer. This paper describes Strings, a high performance distributed shared memory system designed for such SMP clusters. The distinguishing feature of this system is the use of a fully multi-threaded runtime system, using kernel level threads. Strings allows multiple application threads to be run on each node in a cluster. Since most modern UNIX systems can multiplex these threads on kernel level light weight processes, applications written using Strings can exploit multiple processors on a SMP machine. This paper describes some of the architectural details of the system and illustrates the performance improvements with benchmark programs from the SPLASH-2 suite, some computational kernels as well as a full fledged application. It is found that using multiple processes on SMP nodes provides good speedups only for a few of the programs. Multiple application threads can improve the performance in some cases, but other programs show a slowdown. If kernel threads are used additionally, the overall performance improves significantly in all programs tested. Other design decisions also have a beneficial impact, though to a lesser degree.
10991562
Strings: a high-performance distributed shared memory for symmetrical multiprocessor clusters
Introduces Strings, a high-performance distributed shared memory system designed for clusters of symmetrical multiprocessors (SMPs). The distinguishing feature of this system is the use of a fully multithreaded runtime system, written using POSIX threads. Strings also allows multiple application threads to be run on each node in a cluster. Since most modern UNIX systems can multiplex these threads on kernel-level lightweight processes, applications written using Strings can use all the processors in a SMP machine. This paper describes some of the architectural details of the system and analyzes the performance improvements with two example programs and a few benchmark programs from the SPLASH-2 suite.
1480265
Evaluation of cluster interconnects for a distributed shared memory
Clusters of Symmetrical Multiprocessors (SMPs) have recently become popular as low-cost, high-performance computing solutions. The type of interconnection hardware used in these clusters can become a deciding factor in their overall performance. This paper evaluates the performance of three different communication systems, 10 Mbps Ethernet, 100 Mbps FastEthernet and 155 Mbps ATM, using a multithreaded Distributed Shared Memory system, Strings. The raw performance of each network is first measured using netperf. Ten different applications are then used for performance evaluation, including programs from the SPLASH-2 benchmarks, a medical computing application, and some computational kernels. It is found that half of the programs tested are not significantly affected by changes in the bandwidth. Though the ATM network provides the highest overall bandwidth, the remaining applications show that the increase in latency compared to FastEthernet prevents any performance improvement. On the other hand, applications that require only moderately high bandwidths perform substantially better with FastEthernet.
9572409
High-Throughput Multicast Routing Metrics in Wireless Mesh Networks
The stationary nature of nodes in a mesh network has shifted the main design goal of routing protocols from maintaining connectivity between source and destination nodes to finding high-throughput paths between them. In recent years, numerous link-quality-based routing metrics have been proposed for choosing high-throughput paths for unicast protocols. In this paper we study routing metrics for high-throughput tree or mesh construction in multicast protocols. We show that there is a fundamental difference between unicast and multicast routing in how data packets are transmitted at the link layer, and accordingly there is a difference in how the routing metrics for each of these primitives are designed. We adapt certain routing metrics for unicast for high-throughput multicast routing and propose news ones not previously used for high-throughput. We then study the performance improvement achieved by using different link-quality-based routing metrics via extensive simulation and experiments on a mesh network testbed, using ODMRP as a representative multicast protocol. Our testbed experiment results show that ODMRP enhanced with linkquality routing metrics can achieve up to 17.5% throughput improvement as compared to the original ODMRP.
43134968
Some Methods for Privacy in RFID Communication
For RFID tags to gain general acceptance, they will have to offer powerful and flexible privacy mechanisms. After reviewing existing and upcoming privacy mechanisms for RFID privacy, we propose that a key aspect of RFID communication with passive tags, namely its required energy transference from an external antenna, may offer promise when developing privacy mechanisms. We present two proposals for such mechanisms. In the first mechanism, analysis of the received signal by the tags can be used to estimate reader distance (and hence trust). We show that a simple metric analogous to signal to noise ratio correlates well with rough distance. In the second, antenna energy is used to power a tiered authentication scheme, in which tags reveal more information about themselves to more trusted and/or “energetic” readers.
2052039
Overlay Node Placement: Analysis, Algorithms and Impact on Applications
Overlay routing has emerged as a promising approach to improving performance and reliability of Internet paths. To fully realize the potential of overlay routing under the constraints of deployment costs in terms of hardware, network connectivity and human effort, it is critical to carefully place infrastructure overlay nodes to balance the trade-off between performance and resource constraints. In this paper, we investigate approaches to perform intelligent placement of overlay nodes to facilitate (i) resilient routing and (ii) TCP performance improvement. We formulate objective functions to accurately capture application behavior: reliability and TCP performance, and develop several placement algorithms, which offer a wide range of trade-offs in complexity and required knowledge of the client- server location and traffic load. Using simulations on synthetic and real Internet topologies, and PlanetLab experiments, we demonstrate the effectiveness of the placement algorithms and objective functions developed, respectively. We conclude that an approach, hybrid of random and greedy approaches, provides the best tradeoff between computational efficiency and accuracy. We also uncover the fundamental challenge in simultaneously optimizing for reliability and TCP performance, and propose a simple unified algorithm to achieve the same.
13205673
Automatic Generation of Domain Models for Call-Centers from Noisy Transcriptions
Call centers handle customer queries from various domains such as computer sales and support, mobile phones, car rental, etc. Each such domain generally has a domain model which is essential to handle customer complaints. These models contain common problem categories, typical customer issues and their solutions, greeting styles. Currently these models are manually created over time. Towards this, we propose an unsupervised technique to generate domain models automatically from call transcriptions. We use a state of the art Automatic Speech Recognition system to transcribe the calls between agents and customers, which still results in high word error rates (40%) and show that even from these noisy transcriptions of calls we can automatically build a domain model. The domain model is comprised of primarily a topic taxonomy where every node is characterized by topic(s), typical Questions-Answers (Q&As), typical actions and call statistics. We show how such a domain model can be used for topic identification of unseen calls. We also propose applications for aiding agents while handling calls and for agent monitoring based on the domain model.
54110472
Fast and Accurate Text Classification via Multiple Linear Discriminant Projections
Publisher Summary 
Text classification is a standard problem in information retrieval (IR). A learner is presented with training documents, each labeled as containing or not containing material relevant to a given topic. Support vector machines (SVMs) have shown superb performance for text classification tasks. They are accurate, robust, and quick to apply to test instances. Their only potential drawback is their training time and memory requirement. SVMs have been trained on data sets with several thousand instances, but Web directories today contain millions of instances that are valuable for mapping billions of Web pages into Yahoo!-like directories. This chapter presents Simple Iterative Multiple Projection on Lines (SIMPL), a nearly linear-time classification algorithm that mimics the strengths of SVMs while avoiding the training bottleneck. It uses Fisher's linear discriminant, a classical tool from statistical pattern recognition, to project training instances to a carefully selected low-dimensional subspace before inducing a decision tree on the projected instances. SIMPL uses efficient sequential scans and sorts, and is comparable in speed and memory scalability to widely used naive Bayes (NB) classifiers, but it beats NB accuracy decisively.