ppxscal/embedding_network huggingface dataset:
Optimizing server placement for parallel I/O in switch-based clusters
Authors: Jan-Jan Wu, Yi-Fang Lin, Da-Wei Wang, Chien-Min Wang
Venue: Journal of Parallel and Distributed Computing (2009)

In this paper, we consider how to optimize I/O server placement in order to improve parallel I/O performance in switch-based clusters. The significant advances in cluster networks in recent years have made it practical to connect tens of thousands of hosts via networks that have enormous and scalable total capacity, and in which communications between a host and any other host incur the same cost. The same cost property frees users from consideration of network contention and allows them to concentrate on load-balancing issues. We formulate the server placement problem on a cluster that has the same cost property as a weighted bipartite matching with the goal of balancing the workload on the I/O nodes. To find an optimal solution to this problem, we propose an O(n^3^2m(logn+logm)) algorithm, called Load Balance Matching (LBM), where n is the number of compute nodes and m is the number of I/O servers. We also investigate server placement for general clusters in which multiple same-cost subclusters are interconnected to form a large cluster. This class of clusters typically adopt irregular topologies that allow the construction of scalable systems with an incremental expansion capability. Also, due to the limited bandwidth on network links between subclusters, network link contention is a major concern when distributing servers over the entire network. We show that finding an optimal placement strategy for general clusters with the goal of minimizing link contention is computationally intractable. To resolve this problem, we propose a hierarchical strategy that places servers in two steps. First, to minimize link contention, we decide which subcluster each server should be assigned to. We propose a tree-based heuristic algorithm, called Load Balance Traversing (LBT), to solve this problem. In the second step, the LBM algorithm decides the location of each server within a subcluster. Our simulation results demonstrate that LBT achieves a significant improvement in parallel I/O performance over four other algorithms, and is near-optimal in some cases.
Combining Invariant and Corner-Like Features to Optimize Image Matching
Authors: Jimmy Addison Lee, Kin-Choong Yow
Venue: Proceedings of the 3rd Pacific Rim Symposium on Advances in Image and Video Technology (2009)

Significance and usefulness of local invariant features and traditional corner-like features have been widely proven in the literature. In this paper, we novelly combine the two types of features to select salient keypoints with the invariant and corner-like properties, which are highly distinctive and improving match performance. We use moment-derived complex image patterns (e.g., corner, T-junction, sectional cut, and chess-cross) to find corner-like features. We further optimize the matching results by finding corner-like patterns in the invariant matched point correspondences; and rebuff point correspondences that have dissimilar pattern responses which are most likely false matches.
Dynamic load balancing in RCAN content addressable network
Authors: Djelloul Boukhelef, Hiroyuki Kitagawa
Venue: Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication (2009)

RCAN [1] is a novel multi-ring content addressable peer-to-peer system. RCAN was proposed in the aim of improving the routing performance of CAN [4] overlays while minimizing the maintenance overhead during nodes churn in large networks. The key idea of RCAN is to equip each node with a few long-links towards some distant nodes. Long-links are clockwise directed and wrap around to form small rings along each dimension. The number of rings and their sizes self-adjust as nodes join and leave the system. RCAN is a pure P2P design, where all nodes assume the same responsibility. Unlike some existing P2P overlays, RCAN is self-organizing and does not assume any a-priori fixed limits for the network size or the routing state per node. Each node auto-adapts its routing state to cope with network changes. In this work, we address the problem of load balancing in RCAN system. We propose fully decentralized mechanisms to cope with large scale data imbalance. Our methods extend the random join process [7,12] to enable a newly joining node to locate an existing node with a heavy load to share the load with. A new joining node selects one or more existing nodes at random, and then it chooses the heaviest node among them to share the load with. The heaviest node may also be located through a random walk starting from a randomly selected node. In opposition to [7], the proposed methods do not rely on any external index nor assume any global knowledge. All routing and load information is disseminated in the network through links established between immediate and distant neighbors, incurring thus no extra overhead. On another side, the number of probed nodes is logarithmic [1] which enables to achieve constant load imbalance less than or equal to 8 [12, 13, 16]. A combination of the two methods would achieve much smaller load imbalance that is less than or equal to 4 [12]. We also studied the impact of number of entry points to the systems on the load imbalance factor. To the best of our knowledge we are the first to address this problem. We have also conducted an extensive experimental study using uniform and non-uniform data distributions to demonstrate the effectiveness and the scalability of our proposals.
An analysis of WoW players' game hours
Authors: Pin-Yun Tarng, Kuan-Ta Chen, Polly Huang
Venue: Proceedings of the 7th ACM SIGCOMM Workshop on Network and System Support for Games (2008)

Online gaming has become increasingly popular in recent years. Currently, the most common business model of online gaming is based on monthly subscription fees that game players pay to obtain credits, which allow them to start or continue a journey in the game's virtual world. Therefore, from the perspective of game operators, predicting how many players will join a game and how long they will stay in the game is important since these two factors dominate their revenue. This paper represents a pilot study of the predictability of online gamers' subscription time. Specifically, we study the gameplay hours of online gamers and investigate whether strong patterns are embedded in their game hours. Our ultimate goal is to provide a prediction model of online gamers, which takes a player's game hours as the input and predicts whether the player will leave in the near future. Our study is based on real-life traces collected from World of Warcraft, a famous MMORPG (Massively Multiplayer Online Role-Playing Game). The traces contain the gameplay histories of 34,524 players during a two-year period. We believe that our study would be useful for building a prediction model of players' future game hours and unsubscription decisions; i.e., decisions not to renew subscriptions.
Equivalence Criteria for Compositional IF Modal Logics
Authors: Tero Tulenheimo, Manuel Rebuschi
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

An IF modal logic L with a compositional semantics is formulated, generalizing the logic L"S"D introduced in [T. Tulenheimo, and M. Sevenster, On modal logic, IF logic and IF modal logic, in G. Governatori et al. (eds.): ''Advances in Modal Logic''6, 481-501, College Publications, 2006]. Syntactic fragments L"1, L"2, L"3, L"4 are discerned. For each fragment, we study the relation of L"i-equivalence: an equivalence relation between pointed models holding if and only if they satisfy precisely the same formulas of L"i. A criterion for L"i-equivalence is formulated in terms of model-comparison games, by imposing further conditions in addition to bisimilarity. Using the resulting methods for establishing indistinguishability w.r.t. L"i, the relative expressive powers of the four fragments are determined.
A High-Speed Pipelined Degree-Computationless Modified Euclidean Algorithm Architecture for Reed-Solomon Decoders
Authors: Seungbeom Lee, Hanho Lee
Venue: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (2008)

This paper presents a novel high-speed low-complexity pipelined degree-computationless modified Euclidean (pDCME) algorithm architecture for high-speed RS decoders. The pDCME algorithm allows elimination of the degree-computation so as to reduce hardware complexity and obtain high-speed processing. A high-speed RS decoder based on the pDCME algorithm has been designed and implemented with 0.13-μm CMOS standard cell technology in a supply voltage of 1.1 V. The proposed RS decoder operates at a clock frequency of 660 MHz and has a throughput of 5.3 Gb/s. The proposed architecture requires approximately 15% fewer gate counts and a simpler control logic than architectures based on the popular modified Euclidean algorithm.
A holistic framework for understanding government information access initiatives
Authors: Sharon S. Dawes, Theresa A. Pardo, Yuanfu Jiang
Venue: Proceedings of the 2nd International Conference on Theory and Practice of Electronic Governance (2008)

The quality, credibility, and legitimacy of government depends in part on transparency and access to government information. The character, quality, management, and use of information are crucial concerns for effective government. Many different kinds of organizations provide access to government information---libraries, government archives, and public agencies at all levels of government. This paper outlines the challenges facing government information access initiatives and introduces a framework for supporting the development of a holistic view of the specifics of users, uses, organizational capacity, data characteristics, and technology in the context of a complete program, system or process in which these components interact.
Design Computing and Cognition '08: Proceedings of the Third International Conference on Design Computing and Cognition, 1st edition
Authors: John S. Gero, Ashok K. Goel
Venue:  (2008)

This is the third volume of the new conference series Design Computing and Cognition (DCC) that takes over from and subsumes the successful series Artificial Intelligence in Design (AID) published by Kluwer since 1992. The AID volumes have become standard reference texts for the field. It is expected that the DCC volumes will perform the same role. Design Computing and Cognition04 and Design Computing and Cognition06 both edited by John S. Gero, were published by Springer. This new biennial conference series provides an international forum for the presentation and discussion of state-of-the-art and cutting-edge design research. The conference proceedings will form a continuing archive of design computing and cognition research. Design is a fundamentally important topic in disciplines ranging from the more commonly associated fields of architecture and engineering to emerging areas in the social sciences and life sciences. Design is the key to economic competitiveness and the fundamental precursor to objects - both physical and virtual - and services. The conference theme of design computing and cognition recognizes not only the essential relationship between human cognitive processes as models of computation but also how models of computation inspire conceptual realizations of human cognition.
Stream processing in data-driven computational science
Authors: Ying Liu, Nithya Vijayakumar, Beth Plale
Venue: Proceedings of the 7th IEEE/ACM International Conference on Grid Computing (2006)

The use of real-time data streams in data-driven computational science is driving the need for stream processing tools that work within the architectural framework of the larger application. Data stream processing systems are beginning to emerge in the commercial space, but these systems fail to address the needs of large-scale scientific applications. In this paper we illustrate the unique needs of large-scale data driven computational science through an example taken from weather prediction and forecasting. We apply a realistic workload from this application against our Calder stream processing system to determine effective throughput, event processing latency, data access scalability, and deployment latency.1
A tabu search heuristic for a sequence-dependent and time-dependent scheduling problem on a single machine
Authors: Gabriella Stecco, Jean-François Cordeau, Elena Moretti
Venue: Journal of Scheduling (2009)

This paper introduces a tabu search heuristic for a production scheduling problem with sequence-dependent and time-dependent setup times on a single machine. The problem consists in scheduling a set of dependent jobs, where the transition between two jobs comprises an unrestricted setup that can be performed at any time, and a restricted setup that must be performed outside of a given time interval which repeats daily in the same position. The setup time between two jobs is thus a function of the completion time of the first job. The tabu search heuristic relies on shift and swap moves, and a surrogate objective function is used to speed-up the neighborhood evaluation. Computational experiments show that the proposed heuristic consistently finds better solutions in less computation time than a recent branch-and-cut algorithm. Furthermore, on instances where the branch-and-cut algorithm cannot find the optimal solution, the heuristic always identifies a better solution.
An historical look at the SIGCSE conference
Authors: Curt M. White
Venue: ACM SIGCSE Bulletin (2009)

This special session will present an historical look at all past SIGCSE conferences, beginning with 2008. If possible, the conference chair, from each conference will present a brief synopsis of his/her conference. This synopsis may include a photo of the conference site, the number of attendees, the paper acceptance ratio, any special awards and the awardees, the "theme" of the conference, any special issues relevant at that conference, and one or two "interesting" events that occurred during that conference.
High throughput VLSI architecture for soft-output mimo detection based on a greedy graph algorithm
Authors: Yang Sun, Joseph R. Cavallaro
Venue: Proceedings of the 19th ACM Great Lakes symposium on VLSI (2009)

Maximum-likelihood (ML) decoding is a very computational-intensive task for multiple-input multiple-output (MIMO) wireless channel detection. This paper presents a new graph based algorithm to achieve near ML performance for soft MIMO detection. Instead of using the traditional tree search based structure, we represent the search space of the MIMO signals with a directed graph and a greedy algorithm is applied to compute the a posteriori probability (APP) for each transmitted bit. The proposed detector has two advantages: 1) it keeps a fixed throughput and has a regular and parallel datapath structure which makes it amenable to high speed VLSI implementation, and 2) it attempts to maximize the a posteriori probability by making the locally optimum choice at each stage with the hope of finding the global minimum Euclidean distance for every transmitted bit. Compared to the soft K-best detector, the proposed solution significantly reduces the complexity because sorting is not required, while still maintaining good bit error rate (BER) performance. The proposed greedy detection algorithm has been designed and synthesized for a 4 by 4 16-QAM MIMO system in a TSMC 65 nm CMOS technology. The detector achieves a maximum throughput of 600 Mbps with a 0.79 square mm core area.
Semantic Grouping of Shots in a Video Using Modified K-Means Clustering
Authors: Partha Pratim Mohanta, Sanjoy Kumar Saha
Venue: Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition (2009)

Semantic grouping of the shots in a video can bethought of as first step towards scene detection. It also facilitates the easy identification of visually similar scenes. Such grouping also help in the creation of semantic content table and efficient content browsing. In this work, we present an effective scheme to form such groupings. We address the important issue of representing a shot with the help of keyframes and other sampled frames from the shot. Finally, the content of the shot is denoted by the low-level feature vectors corresponding to the representative frames. Similar shots are grouped following a modified k-means clustering algorithm. Modifications have been incorporated to accommodate the differing roles played by the keyframes and sampled frames. We have carried out the experiment with different type of video data and result obtained is satisfactory.
A discrete action principle for electrodynamics and the construction of explicit symplectic integrators for linear, non-dispersive media
Authors: Jeffrey M. McMahon, Stephen K. Gray, George C. Schatz
Venue: Journal of Computational Physics (2009)

In this work, we derive a discrete action principle for electrodynamics that can be used to construct explicit symplectic integrators for Maxwell's equations. Different integrators are constructed depending on the choice of discrete Lagrangian used to approximate the action. By combining discrete Lagrangians in an explicit symplectic partitioned Runge-Kutta method, an integrator capable of achieving any order of accuracy is obtained. Using the von Neumann stability analysis, we show that the integrators greatly increase the numerical stability and reduce the numerical dispersion compared to other methods. For practical purposes, we demonstrate how to implement the integrators using many features of the finite-difference time-domain method. However, our approach is also applicable to other spatial discretizations, such as those used in finite element methods. Using this implementation, numerical examples are presented that demonstrate the ability of the integrators to efficiently reduce and maintain a minimal amount of numerical dispersion, particularly when the time-step is less than the stability limit. The integrators are therefore advantageous for modeling large, inhomogeneous computational domains.
General Game Playing with Ants
Authors: Shiven Sharma, Ziad Kobti, Scott Goodwin
Venue: Proceedings of the 7th International Conference on Simulated Evolution and Learning (2008)

General Game Playing (GGP) aims at developing game playing agents that are able to play a variety of games and, in the absence of pre-programmed game specific knowledge, become proficient players. The challenge of making such a player has led to various techniques being used to tackle the problem of game specific knowledge absence. Most GGP players have used standard tree-search techniques enhanced by automatic heuristic learning, neuroevolution and UCT (Upper Confidence bounds applied to Trees) search, which is a simulation-based tree search. In this paper, we explore a new approach to GGP. We use an Ant Colony System (ACS) to explore the game space and evolve strategies for game playing. Each ant in the ACS is a player with an assigned role, and forages through the game's state space, searching for promising paths to victory. Preliminary results show this approach to be promising. In order to test the architecture, we create matches between players using the knowledge learnt by the ACS and random players.
Taking the measure of program complexity
Authors: Jean Cochrane Zolnowski, Dick B. Simmons
Venue: Proceedings of the May 4-7, 1981, national computer conference (1981)

Program complexity is a topic often discussed in the literature. Research is ongoing in verifying existing complexity measures. There is also a continuing effort to produce and validate new approaches to a complexity measure which incorporate ideas from a variety of areas. Too often, however, approaches to complexity measurement center on a particular aspect of a program, e.g., structures, without incorporating other relevant program characteristics. The question to be answered, then, is, What aspects of a program contribute to its complexity? This paper presents a first step in answering this question. Preliminary results are presented from a Delphi Survey on program complexity. The survey was sent to a cross-section of programmers, managers and software experts. Respondents rated a large number of characteristics as to their effect on program complexity. The paper summarizes the results and includes preliminary analyses.
Parallel simulation of the global epidemiology of Avian influenza
Authors: Dhananjai M. Rao, Alexander Chernyakhovsky
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

SEARUMS is an Eco-modeling, bio-simulation, and analysis environment to study the global epidemiology of Avian Influenza. Originally developed in Java, SEARUMS enables comprehensive epidemiological analysis, forecast epicenters, and time lines of epidemics for prophylaxis; thereby mitigating disease outbreaks. However, SEARUMS-based simulations were time consuming due to the size and complexity of the models. In an endeavor to reduce time for simulation, we have redesigned the infrastructure of SEARUMS to operate as a Time Warp synchronized, parallel and distributed simulation. This paper presents our parallelization efforts along with empirical evaluation of various design alternatives that were explored to identify the ideal parallel simulation configuration. Our experiments indicate that the redesigned environment called SEARUMS++ achieves good scalability and performance, thus meeting a mission-critical objective.
Memory MISER: Improving Main Memory Energy Efficiency in Servers
Authors: Matthew E. Tolentino, Joseph Turner, Kirk W. Cameron
Venue: IEEE Transactions on Computers (2009)

Main memory power in volume and mid-range servers is growing as a fraction of total system power. The resulting energy consumption increases system cost and the heat produced reduces reliability. Emergent memory technology will provide systems with the ability to dynamically turn-on (online) and turn-off (offline) memory devices at runtime. This technology, coupled with slack in memory demand, offers the potential for significant energy savings in servers. However, to gain general acceptance in the server community, power-aware techniques must maintain performance and scale to thousands of memory devices. We propose a Memory Management Infra-Structure for Energy Reduction (Memory MISER) that is transparent, performance-neutral, and scalable. Memory MISER provides: 1) a prototype Linux kernel that manages memory at device granularity, and 2) a userspace daemon that tracks systemic memory demand and implements energy- and performance-constrained device controller policies. Experiments on an 8-node cluster of servers show our Memory MISER conserves memory energy up to 56.8% with no performance degradation for scientific codes that utilized the entire cluster. For multi-user workloads, we achieved memory energy savings of up to 67.94% with no performance degradation. Normalizing to total system energy consumption, our power-aware memory approach reduced energy between 18.81% and 39.02%.