ppxscal/embedding_network huggingface dataset:
Implementation and Evaluation of Prefetching in the Intel Paragon Parallel File System
Authors: Meenakshi Arunachalam, Alok N. Choudhary, Brad Rullman
Venue: Proceedings of the 10th International Parallel Processing Symposium (1996)

The significant difference between the speeds of the I/O system (e.g. disks) and compute processors in parallel systems creates a bottleneck that lowers the performance of an application that does a considerable amount of disk accesses. A major portion of the compute processors' time is wasted on waiting for I/O to complete. This problem can be addressed to a certain extent, if the necessary data can be fetched from the disk before the I/O call to the disk is issued. Fetching data ahead of time, known as prefetching in a multiprocessor environment depends a great deal on the application's access pattern. The subject of this paper is implementation and performance evaluation of a prefetching prototype in a production parallel file system on the Intel Paragon. Specifically, this paper presents a) design and implementation of a prefetching strategy in the parallel file system and b) performance measurements and evaluation of the file system with and without prefetching. The prototype is designed at the operating system level for the PFS. It is implemented in the PFS subsystem of the Intel Paragon Operating System. It is observed that in many cases prefetching provides considerable performance improvements. In some other cases no improvements or some performance degradation is observed due to the overheads incurred in prefetching.
Real-Time Job Scheduling in Hypercube Systems
Authors: O-Hoon Kwon, Jong Kim, Sung Je Hong, Sunggu Lee
Venue: Proceedings of the international Conference on Parallel Processing (1997)

In this paper, we present the problem of scheduling real-time jobs in a hypercube system and propose a scheduling algorithm. The goals of the proposed scheduling algorithm are to determine whether all jobs can complete their processing before their fixed deadlines in a hypercube system and to find such a schedule. Each job is associated with a computation time, a deadline, and a dimensional requirement. Determining a schedule such that all jobs meet before their respective fixed deadlines in a hypercube system when preemption is not allowed is an NP-complete problem. Hence, we present a heuristic scheduling algorithm for scheduling non-preemptable real-time jobs in a hypercube system. Finally, we evaluate the proposed algorithm using simulation.
Sync-MS: Synchronized Messaging Service for Real-Time Multi-Player Distributed Games
Authors: Yow-Jian Lin, Katherine Guo, Sanjoy Paul
Venue: Proceedings of the 10th IEEE International Conference on Network Protocols (2002)

Real-time, online multi-player games are becoming increasingly popular due to advances in game design and the proliferation of broadband Internet access. However, fairness remains a major challenge when players over large geographic areas participate in a client-server based game together. This paper proposes a game-independent, network-based service, called Sync-MS, that balances the tradeoff between response time and fairness. Sync-MS uses twomechanisms, Sync-out and Sync-in, to address state update fairness and player action fairness, respectively. Two metrics, ahead and behind measured against the fair order, aredefined to evaluate Sync-MS's fairness performance. Simulation results show that Sync-MS dramatically improves player action fairness for all players while slightly increases average response time for players with shorter network delay to the game server.
Offline Handwritten Chinese Character Recognition viaRadical Extraction and Recognition
Authors: Wilson W. S. Ip, Korris F. L. Chung, Daniel S. Yeung
Venue: Proceedings of the 4th International Conference on Document Analysis and Recognition (1997)

Despite the facts that Chinese characters are composed of radicals and Chinese usually formulate their knowledge of Chinese characters as a combination of radicals, very few studies have focused on a character decomposition approach to recognition, i.e., recognizing a character by first extracting and recognizing its radicals. In this paper, such an approach is adopted and the problem of how to extract radical sub-images from character images is particularly addressed. A radical extraction algorithm based on deformable templates (DTs) has been developed. The application of DTs to Chinese character recognition is a novel one and concepts like goodness of character decomposition have been exploited to formulate appropriate energy terms and to devise cost effective minimization schemes for the problem. The advantage of the character decomposition approach is demonstrated by feeding the extracted radical images to an adopted structural based Chinese character recognizer whose outputs are then combined to produce the class label of the input character. Simulation results show that the performance of the adopted Chinese character recognition system can be improved significantly when character decomposition approach is used.
Applying Workflow Management to Support Massive Maintenance
Authors: Lerina Aversano, Sergio Betti, Eugenio Pompella, Silvio Stefanucci
Venue: Proceedings of the 26th International Computer Software and Applications Conference on Prolonging Software Life: Development and Redevelopment (2002)

Workflow Management Systems have proven useful for improving the management end execution of processes in several application domains, including software engineering. In this paper we discuss issues and preliminary results of a project aiming at introducing workflow technology in a software maintenance organization. We apply a four steps process to model the workflows, and the associated flows of documentations, of the massive maintenance process. The paper describes the models obtained and discusses how they have been implemented using market-widespread workflow technology.
Low Latency MPI for Meiko CS/2 and ATM Clusters
Authors: Chris R. Jones, Ambuj K. Singh, Divyakant Agrawal
Venue: Proceedings of the 11th International Symposium on Parallel Processing (1997)

MPI (Message Passing Interface) is a proposed message passing standard for development of efficient and portable parallel programs. An implementation of MPI is presented and evaluated for the Meiko CS/2, a 64 node parallel computer, and a network of 8 SGI workstations connected by an ATM switch and Ethernet.
Experimental Evaluation of QSM, a Simple Shared-Memory Model
Authors: Brian Grayson, Michael Dahlin, Vijaya Ramachandran
Venue: Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing (1999)

Parallel programming models should attempt to satisfy two conflicting goals. On one hand, they should hide architectural details so that algorithm designers can write simple, portable programs. On the other hand, models must expose architectural details so that designers can evaluate and optimize the performance of their algorithms. In this paper, we experimentally examine the trade-offs made by a simple shared-memory model, QSM, to address this dilemma. The results indicate that analysis under the QSM model yields quite accurate results for reasonable input sizes and that algorithms developed under QSM achieve performance close to that obtainable through more complex models, such as BSP and LogP.
Hector: Automated Task Allocation for MPI
Authors: Samuel H. Russ, Brian K. Flachs, Jonathan Robinson, Bjørn Heckel
Venue: Proceedings of the 10th International Parallel Processing Symposium (1996)

Many institutions already have networks of workstations, which could potentially be harnessed as a powerful parallel processing resource. A new, automatic task allocation system has been built on top of MPI, an environment that permits parallel programming by using the message-passing paradigm and implemented in extensions to C and FORTRAN. This system, known as ``Hector'', supports dynamic migration of tasks and automatic run-time performance optimization. MPI programs can be run without modification under Hector, and can be run on existing networks of workstations. Thus Hector permits institutions to harness existing computational resources quickly and transparently.
MMPacking: A Load and Storage Balancing Algorithm for Distributed Multimedia Servers
Authors: Dimitrios N. Serpanos, Leonidas Georgiadis, T. Bouloutas
Venue: Proceedings of the 1996 International Conference on Computer Design, VLSI in Computers and Processors (1996)

In distributed multimedia servers where client requests for different video streams may have different probabilities, placement of video streams is an important parameter, because it may result in unbalanced requests to the system's stations, and thus to high blocking probabilities of requests. We present a method, MMPacking, to balance traffic load and storage use in a distributed server environment. Since different video streams are requested by clients with different rates, video stream replication is used to balance the traffic patterns of the stations; thus, the requests and I/O usage of the stations is balanced, since replication allows requests for the same video stream to be routed to different stations. MMPacking achieves load balancing by producing at most N-1 replicas of video streams in a system with N servers. These replicas are distributed among the stations, so that storage balancing is achieved as well, since no station stores more than 2 video streams than any other station in the system.
FARM: A Framework for Exploring Mining Spaces with Multiple Attributes
Authors: Chang-Shing Perng, Haixun Wang, Sheng Ma, Joseph L. Hellerstein
Venue: Proceedings of the 2001 IEEE International Conference on Data Mining (2001)

Mining for frequent itemsets typically involves a preprocessing step in which data with multiple attributes are grouped into transactions, and item are defined based on attribute values. We have observed that such fixed attribute mining can severely constrain the pattern that are discovered. Herein, we introduce mining paces, a new framework for mining multi-attribute data that include the discovery of transaction and item definition (with the exploitation of taxonomies and functional dependenciesif they are available).We prove that special downward closure properties (or anti-monotonic property) hold for mining paces, aresult that allows us to construct efficient algorithms for mining pattern without the constraint of fixed attribute mining. We apply our algorithm to real world data collected from a production computer network. The result how that by exploiting the special kind of downward closure in mining paces, execution times for mining can be reduced by a factor of three to four.
Re-Slicing Tomographic Volumes with Shell Rendering
Authors: Cesar Augusto de Carvalho
Venue: Proceedings of the 15th Brazilian Symposium on Computer Graphics and Image Processing (2002)

In this work we show a technique based on Shell Rendering to process a volume composed by a set of tomographic images in such a way that it can be rotated and re-sliced in a new volume in an appropriate angle. We also propose two different techniques for dealing with quality of rendered images. In the last case, the quality of the new images is comparable to the original ones.
Heuristic Optimization for Decentralized Frequent Itemset Counting
Authors: Viviane Crestana-Jensen, Nandit Soparkar
Venue: Proceedings of the 2001 IEEE International Conference on Data Mining (2001)

The choices for mining of decentralized data are numerous, and we have developed techniques to enumerate andoptimize decentralized frequent itemset counting. In thispaper, we introduce our heuristic approach to improve theperformance of such techniques developed in ways similarto query processing in database systems. We also describeempirical results that validate our heuristic techniques.
Simulative inference about nonmonotonic reasoners
Authors: Aaron N. Kaplan
Venue: Proceedings of the 7th conference on Theoretical aspects of rationality and knowledge (1998)

If one has attributed certain initial beliefs to an agent, it is sometimes possible to reason about further beliefs the agent must hold by observing what conclusions one's own reasoning mechanism draws when given the initial beliefs as premises. This technique is called simulative inference. In an earlier paper, we described a logic of belief in which the reasoning that generates beliefs is modeled explicitly as a computational process. We used this logic to characterize a class of computational inference mechanisms for which simulative inference is sound, under the assumption that the observer and the observed have similar mechanisms. In this paper, we present a different form of simulative inference, and show that unlike the earlier form, it is sound even for some mechanisms that perform defeasible inference.
Optimizing Loop Performance for Clustered VLIW Architectures
Authors: Yi Qian, Steve Carr, Philip H. Sweany
Venue: Proceedings of the 2002 International Conference on Parallel Architectures and Compilation Techniques (2002)

Modern embedded systems often require high degrees of instruction-level parallelism (ILP) within strict constraints on power consumption and chip cost. Unfortunately, a high-performance embedded processor with high ILP generally puts large demands on register resources, making it difficult to maintain a single, multi-ported register bank. To address this problem, some architectures, e.g. the Texas Instruments TMS320C6x, partition the register bank into multiple banks that are each directly connected only to a sub-set of functional units. These functional unit/register bank groups are called clusters.Clustered architectures require that either copy operations or delay slots be inserted when an operation accesses data stored on a different cluster. In order to generate excellent code for such architectures, the compiler must not only spread the computation across clusters to achieve maximum parallelism, but also must limit the effects of intercluster data transfers.Loop unrolling and unroll-and-jam enhance the parallelism in loops to help limit the effects of intercluster data transfers. In this paper, we describe an accurate metric for predicting the intercluster communication cost of a loop and present an integer-optimization problem that can be used to guide the application of unroll-and-jam and loop unrolling considering the effects of both ILP and intercluster data transfers. Our method achieves a harmonic mean speedup of 1.4 ¿ 1.7 on software pipelined loops for both a simulated architecture and the TI TMS320C64x.
Initial Design of the "Plug-n-Analyze" Framework for Architecture Tradeoff Analysis
Authors: Hoh In, Ana Erendira Flores-Mendoza
Venue: 23rd International Computer Software and Applications Conference (1999)

This paper presents an initial design of the "Plug-n-Analyze" framework for the tradeoff analysis in determining architecture alternatives that have different strength and weakness on quality attributes. The framework provides: i) architecture alternative negotiation aids among multiple stakeholders, ii) visualization aids for understanding complicated interactions and tradeoff dependencies among quality attributes, and iii) a general environment by integrating independent analysis methods by simply "plugging" and generating architecture options for fully "analyzing".
Maintenance of Sequential Patterns for Record Deletion
Authors: Ching-Yao Wang, Tzung-Pei Hong, Shian-Shyong Tseng
Venue: Proceedings of the 2001 IEEE International Conference on Data Mining (2001)

In the past, we proposed an incremental mining algorithm for maintenance of sequential patterns based on the concept of pre-large sequences as new records were inserted. In this paper, we attempt to apply the concept of pre-large sequences to maintain sequentialpatterns as records are deleted. Pre-large sequences are defined by a lower support threshold and an upper support threshold. They act as buffers to avoid the movements of sequential patterns directly from large to small and vice-versa. Our proposed algorithm does notrequire rescanning original databases until the accumulative amount of deleted customer sequences exceeds a safety bound, which depends on database size. As databases grow larger, the numbers of deleted customer sequences allowed before database rescanningis required also grow. The proposed approach is thus efficient for a large database.
k -ary n -trees: High Performance Networks for Massively Parallel Architectures
Authors: Fabrizio Petrini, Marco Vanneschi
Venue: Proceedings of the 11th International Symposium on Parallel Processing (1997)

The past few years have seen a rise in popularity of massively parallel architectures that use fat-trees as their interconnection networks. In this paper we study the com-munication performance of a parametric family of fat-trees, the k-ary n-trees, built with constant arity switches inter-connected in a regular topology. Through simulation on a 4-ary 4-tree with 256 nodes, we analyze some variants of an adaptive algorithm that utilize wormhole routing with one, two and four virtual channels. The experimental results show that the uniform, bit reversal and transpose traffic pat-terns are very sensitive to the flow control strategy. In all these cases, the saturation points are between 35-40% of the network capacity with one virtual channel, 55-60% with two virtual channels and around 75% with four virtual channels. The complement traffic, a representative of the class of the congestion-free communication patterns, reaches an optimal performance with a saturation point at 97% of the capacity for all flow control strategies.
Mobile Query Optimization Based on Agent-Technology for Distributed Data Warehouse and OLAP Applications
Authors: Abdelkader Hameurlain, Franck Morvan, Philipp Tomsich, Robert M. Bruckner, Harald Kosch, Peter Brezany
Venue: Proceedings of the 13th International Workshop on Database and Expert Systems Applications (2002)

With the rapid collection of data in wide variety of fields ¿ ranging from business transactions through medical investigations to scientific research ¿ the demands in data analysis tools are ever growing. Today's challenges are less related to data storage and information retrieval, but can rather be found in the analysis of data on a global scale in a heterogenous information system: technologies such as On-Line Analytical Processing, Data Mining and Knowledge Discovery in Databases all require the integration of information and efficient query processing. In distributed and heterogenous datasets this can only be achieved by the efficient distribution and scheduling of subtasks in a distributed computing resource. We propose the use of mobile query optimizations based on agent-technology for distributeddata warehouse and OLAP applications to adapt the concurrent query execution dynamically to the computing resource it executes on. This is of particular importance in cluster and grid computing.
Fully-Scalable Fault-Tolerant Simulations for BSP and CGM
Authors: Sung-Ryul Kim, Kunsoo Park
Venue: Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing (1999)

In this paper we consider general simulations of algorithms designed for fully operational BSP and CGM machines on machines with faulty processors. The faults are deterministic (i.e., worst-case distributions of faults are considered) and static (i.e., they do not change in the course of computation). We assume that a constant fraction of processors are faulty. We present a deterministic simulation (resp. a randomized simulation) that achieves constant slowdown per local computations and O((logh p)2 ) (resp. O(logh p)) slowdown per communication round, provided that a deterministic preprocessing is done that requires O((logh p)2 ) communication rounds and linear (in h)computation per processor in each communication round. Our results are fully-scalable over all values of p from 0(1) to (n). Furthermore, our results imply that for p = n (0
General word recognition using approximate segment-string matching
Authors: John T. Favata
Venue: Proceedings of the 4th International Conference on Document Analysis and Recognition (1997)

Focuses on the problem of isolated off-line general word recognition using an approximate stroke-segment/string matching algorithm. Several recently proposed word recognition algorithms use the strategy of directly matching the stroke segments (with OCR estimates) to the sequence of characters in each lexicon word. This idea works very well under ideal conditions; however, many applications require the recognition of text in the presence of document noise, poor handwriting and lexicon errors. These factors require careful design of the matching strategy such that a moderate amount of any form of degradation does not cause a recognition failure. A segment-to-string matching algorithm is proposed which robustly recovers from moderate levels of noise and system errors. This algorithm is developed in the context of a complete word recognition system and serves as its final post-processing module.
Connection-oriented net model and fuzzy clustering techniques for K-way circuit partitioning
Authors: Jin-Tai Yan
Venue: Proceedings of the 1995 International Conference on Computer Design: VLSI in Computers and Processors (1995)

In this paper, we firstly propose a k-way connection-oriented net model, chain net model, to generalize the cut analysis for k-way circuit partitioning and to reduce the complexity of edges for the representation of a multiple-pin net between the transformation of a hypergraph and an edge-weighted graph. Furthermore, based on the techniques of fuzzy c-means clustering, we develop and propose fuzzy c-means graph clustering to obtain k groups of fuzzy memberships for the vertices in the mapped graph according to the global information of all the net connections. Finally, by the area information of any cell in the circuit netlist, these k groups of fuzzy memberships will lead to a cut-driven or balance-driven k-way circuit partitioning. As a result, k-way circuit partitioning has been implemented for testing MCNC circuit benchmarks and the experimental results show that the proposed partitioning approach generates effective results on the partitioning cut and the partitioning balance for these benchmarks.
Region Encoding Diagram for Fully Symbolic Verification of Real-Time Systems
Authors: Farn Wang
Venue: 24th International Computer Software and Applications Conference (2000)

RED (Region Encoding Diagram), first reported in [15], is a BDD-like data-structure for fully symbolic verification of symmetric real-time systems with single clock per process. We propose to extend RED for asymmetric real-time systems with unrestricted number of global or local clocks. Unlike in DBM which records differences between pairs of clock readings, we records the ordering among fractional parts of clock readings into integer sequences encoded in RED's. Like BDD, the new RED is also a minimal canonical form for its target system state-space representations. The number of variables used in RED is O(jXj log jXj) when X is the clock set in the input system description. Experiment has been carried out to compare performance with tools UPPAAL2k and Kronos. Accordingly, we find out that our RED is the most efficient real-time system safety analyzer as long as concurrency complexity is considered.