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Articles 301 - 330 of 532
Full-Text Articles in Computer Sciences
Runtime And Language Support For Compiling Adaptive Irregular Programs On Distributed Memory Machines, Yuan-Shin Hwang, Bongki Moon, Shamik D. Sharma, Ravi Ponnusamy
Runtime And Language Support For Compiling Adaptive Irregular Programs On Distributed Memory Machines, Yuan-Shin Hwang, Bongki Moon, Shamik D. Sharma, Ravi Ponnusamy
Northeast Parallel Architecture Center
In many scientific applications, arrays containing data are indirectly indexed through indirection arrays. Such scientific applications are called irregular programs and are a distinct class of applications that require special techniques for parallelization. This paper presents a library called CHAOS, which helps users implement irregular programs on distributed-memory message-passing machines, such as the Paragon, Delta, CM-5 and SP-1. The CHAOS library provides efficient runtime primitives for distributing data and computation over processors; it supports efficient index translation mechanisms and provides users high-level mechanisms for optimizing communication. CHAOS subsumes the previous PARTI library and supports a larger class of applications. In …
Parallel Remapping Algorithms For Adaptive Problems, Chao Wei Ou, Sanjay Ranka
Parallel Remapping Algorithms For Adaptive Problems, Chao Wei Ou, Sanjay Ranka
Northeast Parallel Architecture Center
In this paper we present fast parallel algorithms for remapping a class of irregular and adaptive problems on coarse-grained distributed memory machines. We show that the remapping of these applications, using simple index-based mapping algorithm, can be reduced to sorting a nearly sorted list of integers or merging an unsorted list of integers with a sorted list of integers. By using the algorithms we have developed, the remapping of these problems can be achieved at a fraction of the cost of mapping from scratch. Experimental results are presented on the CM-5.
Communication Strategies For Out-Of-Core Programs On Distributed Memory Machines, Rajesh Bordawekar, Alok Choudhary
Communication Strategies For Out-Of-Core Programs On Distributed Memory Machines, Rajesh Bordawekar, Alok Choudhary
Northeast Parallel Architecture Center
In this paper, we show that communication in the out-of-core distributed memory problems requires both inter-processor communication and file I/O. Given that primary data structures reside in files, even communication requires I/O. Thus, it is important to optimize the I/O costs associated with a communication step. We present three methods for performing communication in out-of-core distributed memory problems. The first method, termed as the “out-of-core“communication method, follows a loosely synchronous model. Computation and Communication phases in this case are clearly separated, and communication requires permutation of data in files. The second method, termed as”demand-driven-in-core communication” considers only communication required of …
The Use Of The National Information Infrastructure And High Performance Computers In Industry, Geoffrey C. Fox, Wojtek Furmanski
The Use Of The National Information Infrastructure And High Performance Computers In Industry, Geoffrey C. Fox, Wojtek Furmanski
Northeast Parallel Architecture Center
We divide potential NII (National Information Infrastructure) services into five broad areas: Collaboration and televirtuality; InfoVISiON (Information, Video, Imagery, and Simulation on Demand), and digital libraries; commerce; metacomputing; WebTop productivity services. The latter denotes the broad suite of tools we expect to be offered on the Web in a general environment we term WebWindows. We review current and future World Wide Web technologies, which could underlie these services. In particular, we suggest an integration framework WebWork for High Performance (parallel and distributed) computing and the NII. We point out that pervasive WebWork and WebWindows technologies will enable, facilitate and substantially …
Cluster Computing Review, Mark Baker, Geoffrey C. Fox, Hon W. Yau
Cluster Computing Review, Mark Baker, Geoffrey C. Fox, Hon W. Yau
Northeast Parallel Architecture Center
In the past decade there has been a dramatic shift from mainframe or ‘host−centric’ computing to a distributed ‘client−server’ approach. In the next few years this trend is likely to continue with further shifts towards ‘network−centric’ computing becoming apparent. All these trends were set in motion by the invention of the mass−reproducible microprocessor by Ted Hoff of Intel some twenty−odd years ago. The present generation of RISC microprocessors are now more than a match for mainframes in terms of cost and performance. The long−foreseen day when collections of RISC microprocessors assembled together as a parallel computer could out perform the …
Exploiting High Performance Fortran For Computational Fluid Dynamics, Volume 919, Ken Hawick, Geoffrey C. Fox
Exploiting High Performance Fortran For Computational Fluid Dynamics, Volume 919, Ken Hawick, Geoffrey C. Fox
Northeast Parallel Architecture Center
We discuss the High Performance Fortran data parallel programming language as an aid to software engineering and as a tool for exploiting High Performance Computing systems for computational uid dynamics applications. We discuss the use of intrinsic functions, data distribution directives and explicitly parallel constructs to optimize performance by minimizing communications requirements in a portable manner. In particular we use an implicit method such as the ADI algorithm to illustrate the major issues. We focus on regular mesh problems, since these can be efficiently represented by the existing HPF definition, but also discuss issues arising from the use of irregular …
High Performance Distributed Computing, Geoffrey C. Fox
High Performance Distributed Computing, Geoffrey C. Fox
Northeast Parallel Architecture Center
High Performance Distributed Computing (HPDC) is driven by the rapid advance of two related technologies -- those underlying computing and communications, respectively. These technology pushes are linked to application pulls, which vary from the use of a cluster of some 20 workstations simulating fluid flow around an aircraft, to the complex linkage of several hundred million advanced PCs around the globe to deliver and receive multimedia information. The review of base technologies and exemplar applications is followed by a brief discussion of software models for HPDC, which are illustrated by two extremes -- PVM and the conjectured future World Wide …
Basic Issues And Current Status Of Parallel Computing -- 1995, Geoffrey C. Fox
Basic Issues And Current Status Of Parallel Computing -- 1995, Geoffrey C. Fox
Northeast Parallel Architecture Center
The best enterprises have both a compelling need pulling them forward and an innovative technological solution pushing them on. In high-performance computing, we have the need for increased computational power in many applications and the inevitable long-term solution is massive parallelism. In the short term, the relation between pull and push may seem unclear as novel algorithms and software are needed to support parallel computing. However, eventually parallelism will be present in all computers -- including those in your children's video game, your personal computer or workstation, and the central supercomputer.
Effects Of Technology Mapping On Fault Detection Coverage In Reprogrammable Fpgas, Kevin A. Kwiat, Warren Debany, Salim Hariri
Effects Of Technology Mapping On Fault Detection Coverage In Reprogrammable Fpgas, Kevin A. Kwiat, Warren Debany, Salim Hariri
Electrical Engineering and Computer Science - All Scholarship
Although Field-Programmable Gate Arrays (FPGAs) are tested by their manufacturers prior to shipment, they are still susceptible to failures in the field. In this paper, test vectors generated for the emulated (i.e., mission) circuit are fault simulated on two different models: the original view of the circuit, and the design as it is mapped to the FPGA's logic cells. Faults in the cells and in the programming logic are considered. Experiments show that this commonly-used approach fails to detect most of the faults in the FPGA.
Semantics Vs. Syntax Vs. Computations Machine Models For Type-2 Polynomial-Time Bounded Functionals (Preliminary Draft), James S. Royer
Semantics Vs. Syntax Vs. Computations Machine Models For Type-2 Polynomial-Time Bounded Functionals (Preliminary Draft), James S. Royer
Electrical Engineering and Computer Science - Technical Reports
This paper investigates analogs of the Kreisel-Lacombe-Shoenfield Theorem in the context of the type-2 basic feasible functionals, a.k.a. the Mehlhorn-Cook class of type-2 polynomial-time functionals. We develop a direct, polynomial-time analog of effective operation, where the time bound on computations is modeled after Kapron and Cook's scheme for their basic polynomial-time functionals. We show that (i) if P = NP, these polynomial-time effective operations are strictly more powerful on R (the class of recursive functions) than the basic feasible functions, and (ii) there is an oracle relative to which these polynomial-time effective operations and the basic feasible functionals have the …
Multiprocessor Document Allocation: A Neural Network Approach, Abdulaziz Sultan Al-Sehibani, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Multiprocessor Document Allocation: A Neural Network Approach, Abdulaziz Sultan Al-Sehibani, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Electrical Engineering and Computer Science - Technical Reports
We consider the problem of distributing the documents to a given set of processors so that the load on each processor is as equal as possible and the amount of communication is as small as possible. This is an NP-Complete problem. We apply continuous as well as discrete Hopfield neural networks to obtain suboptimal solutions for the problem. These networks perform better than a genetic algorithm for this task proposed by Frieder et al. [4]; in particular, the continuous Hopfield network performs extremely well.
Covering Radius 1985-1994, G. D. Cohen, S. N. Litsyn, Antoine C. Lobstein, H. F. Mattson Jr
Covering Radius 1985-1994, G. D. Cohen, S. N. Litsyn, Antoine C. Lobstein, H. F. Mattson Jr
Electrical Engineering and Computer Science - Technical Reports
We survey important developments in the theory of covering radius during the period 1985-1994. We present lower bounds, constructions and upper bounds, the linear and nonlinear cases, density and asymptotic results, normality, specific classes of codes, covering radius and dual distance, tables, and open problems.
Characterization Of A Class Of Sigmoid Functions With Applications To Neural Networks, Anil Ravindran Menon, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Characterization Of A Class Of Sigmoid Functions With Applications To Neural Networks, Anil Ravindran Menon, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Electrical Engineering and Computer Science - Technical Reports
Sigmoid functions, whose graphs are "S-shaped" curves, appear in a great variety of contexts, such as the transfer functions in many neural networks. Their ubiquity is no accident; these curves are the among the simplest non-linear curves, striking a graceful balance between linear and non-linear behavior.
Fluted Formulas And The Limits Of Decidability, William C. Purdy
Fluted Formulas And The Limits Of Decidability, William C. Purdy
Electrical Engineering and Computer Science - Technical Reports
In the predicate calculus, variables provide a flexible indexing service that selects the actual arguments to a predicate letter from among possible arguments that precede the predicate letter (in the parse of the formula). In the process of selection, the possible arguments can be permuted, repeated (used more than once), and skipped. If this service is withheld, so that arguments must be the immediately preceding ones, taken in the order in which they occur, the formula is said to be fluted. Quine showed that if a fluted formula contains only homogeneous conjunction (conjoins only subformulas of equal arity), then the …
A Domain-Specific Parallel Programming System I: Design And Application To Ecological Modelling, Elaine Wenderholm, Micah Beck
A Domain-Specific Parallel Programming System I: Design And Application To Ecological Modelling, Elaine Wenderholm, Micah Beck
Electrical Engineering and Computer Science - Technical Reports
The goal of the εm project is to make parallel programming easily accessible to a broad community of scientists. Previous approaches such as the use of general parallel programming languages and parallelizing compilers for sequential languages have fallen short in this respect. The approach is to design a special purpose programming language which is oriented towards a specific area of application. The result is a specialized and effective scientific tool. εm is a high-level programming system which puts parallelism into the hands of scientists who are not sophisticated programmers. By restricting and simplifying the programming interface, εm eases both the …
Analysis Of Myoelectrical Signals For Building A Dextrous Hand, Christopher T. Creel, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Analysis Of Myoelectrical Signals For Building A Dextrous Hand, Christopher T. Creel, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Electrical Engineering and Computer Science - Technical Reports
We analyze techniques for myoelectrical signals classification for the purpose of designing a multifunctional prosthetic device for human amputees. The main advantage of our system over existing models is that it is more robust, easier to work with, more general, and efficient enough to run in real time. We achieve this with the help of "Supervised Growing Cell Structures." an artificial neural network model designed by Fritzke [10]. The current paper focuses on the flexion of the index, middle and ring fingers, as these are the most difficult movements to tackle.
Knowledge-Based Nonuniform Crossover, Harpal Maini, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Knowledge-Based Nonuniform Crossover, Harpal Maini, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Electrical Engineering and Computer Science - Technical Reports
We present a new "knowledge-based non-uniform crossover" (KNUX) operator for genetic algorithms (GA's) that generalizes uniform crossover. We extend this to "Dynamic KNUX" (DKNUX), which constantly updates the knowledge extracted so far from the environment's feedback on previously generated chromosomes. KNUX can improve on good solutions previously obtained by using other algorithms. The modifications made by KNUX are orthogonal to other changes in parameters of GA's, and can be pursued together with any other proposed improvements. Whereas most genetic search methods focus on improving the move-selection procedures, after having chosen a fixed move-generation mechanism, KNUX and DKNUX make the move-generation …
Decoding Linear Block Codes Using A Priority-First Search: Performance Analysis And Suboptimal Version, Yunghsiang S. Han, Carlos R.P. Hartmann, Kishan Mehrotra
Decoding Linear Block Codes Using A Priority-First Search: Performance Analysis And Suboptimal Version, Yunghsiang S. Han, Carlos R.P. Hartmann, Kishan Mehrotra
Electrical Engineering and Computer Science - Technical Reports
An efficient maximum-likelihood soft-decision decoding algorithm for linear block codes using a generalized Dijkstra's Algorithm was proposed by Han, Hartmann, and Chen. In this report we prove that this algorithm is efficient for most practical communication systems where the probability of error is less than 10-3 by finding an upper bound of the computation performance of the algorithm. A suboptimal decoding algorithm is also proposed. The performance of this suboptimal decoding algorithm is within 0.25 dB and 0.5 dB of the performance of an optimal decoding algorithm for the (104, 52) binary extended quadratic residue code and the (128, 64) …
A Data Parallel Algorithm For Solving The Region Growing Problem On The Connection Machine, Nawal Copty, Sanjay Ranka, Geoffrey C. Fox, Ravi V. Shankar
A Data Parallel Algorithm For Solving The Region Growing Problem On The Connection Machine, Nawal Copty, Sanjay Ranka, Geoffrey C. Fox, Ravi V. Shankar
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
Region growing is a general technique for image segmentation, where image characteristics are used to group adjacent pixels together to form regions. This paper presents a parallel algorithm for solving the region growing problem based on the split and merge approach, and uses it to test and compare various parallel architectures and programming models. The implementations were done on the Connection Machine, models CM-2 and CM-5, in the data parallel and message passing programming models. Randomization was introduced in breaking ties during merging to increase the degree of parallelism, and only one and two-dimensional arrays of data were used in …
The Complexity Of Local Stratification, Peter Cholak, Howard A. Blair
The Complexity Of Local Stratification, Peter Cholak, Howard A. Blair
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
The class of locally stratified logic programs is shown to be Π 1 1-complete by the construction of a reducibility of the class of infinitely branching nondeterministic finite register machines.
Genetic Algorithms For Graph Partitioning And Incremental Graph Partitioning, Harpal Maini, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Genetic Algorithms For Graph Partitioning And Incremental Graph Partitioning, Harpal Maini, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
Partitioning graphs into equally large groups of nodes, minimizing the number of edges between different groups, is an extremely important problem in parallel computing. This paper presents genetic algorithms for suboptimal graph partitioning, with new crossover operators (KNUX, DKNUX) that lead to orders of magnitude improvement over traditional genetic operators in solution quality and speed. Our method can improve on good solutions previously obtained by using other algorithms or graph theoretic heuristics in minimizing the total communication cost or the worst case cost of communication for a single processor. We also extend our algorithm to Incremental Graph Partitioning problems, in …
The Transportation Primitive, Ravi V. Shankar, Khaled A. Alsabti, Sanjay Ranka
The Transportation Primitive, Ravi V. Shankar, Khaled A. Alsabti, Sanjay Ranka
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
This paper presents algorithms for implementing the transportation primitive on a distributed memory parallel architecture. The transportation primitive performs many-to-many personalized communication with bounded incoming and outgoing traffic. We present a two-stage deterministic algorithm that decomposes the communication with possibly high variance in message size into two communication stages with low message size variance. If the maximum outgoing or incoming traffic at any processor is t, transportation can be done in 2t¯ time (+ lower order terms) when t O(p 2 + pø=¯) (¯ is the inverse of the data transfer rate, ø is the startup overhead). If the maximum …
Parallel Incremental Graph Partitioning Using Linear Programming, Chao Wei Ou, Sanjay Ranka
Parallel Incremental Graph Partitioning Using Linear Programming, Chao Wei Ou, Sanjay Ranka
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
Partitioning graphs into equally large groups of nodes while minimizing the number of edges between different groups is an extremely important problem in parallel computing. For instance, efficiently parallelizing several scientific and engineering applications requires the partitioning of data or tasks among processors such that the computational load on each node is roughly the same, while communication is minimized. Obtaining exact solutions is computationally intractable, since graph-partitioning is an NP-complete. For a large class of irregular and adaptive data parallel applications (such as adaptive meshes), the computational structure changes from one phase to another in an incremental fashion. In incremental …
Random Data Accesses On A Coarse-Grained Parallel Machine Ii. One-To-Many And Many-To-One Mappings, Ravi V. Shankar, Sanjay Ranka
Random Data Accesses On A Coarse-Grained Parallel Machine Ii. One-To-Many And Many-To-One Mappings, Ravi V. Shankar, Sanjay Ranka
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
This paper describes deterministic communication-efficient algorithms for performing random data accesses with hot spots on a coarse-grained parallel machine. The general random access read/write operations with hot spots can be completed in Clanip (+ lower order terms) time and is optimal and scalable provided n _> O(pa+p2r/l) (n is the number of elements distributed across p processors, r is the start-up overhead and 1/It is the data transfer rate). C is a small constant between 3 and 4 for the random access write operation, slightly higher for the random access read operation. Monotonic random access reads/writes can be completed with …
Optimal Processor Assignment For A Class Of Pipelined Computations, Alok N. Choudhary, Bhagirath Narahari, David Nicol, Rahul Simha
Optimal Processor Assignment For A Class Of Pipelined Computations, Alok N. Choudhary, Bhagirath Narahari, David Nicol, Rahul Simha
Electrical Engineering and Computer Science - All Scholarship
The availability of large scale multitasked parallel architectures introduces the following processor assignment problem: we are given a long sequence of data sets, each of which is to undergo processing by a collection of tasks whose inter-task data dependencies form a series-parallel partial order. Each individual task is potentially parallelizable, with a known experimentally determined execution signature. Recognizing that data sets can be pipelined through the task structure, the problem is to find a "good" assignment of processors to tasks. Two objectives interest us: minimal response time per data set given a throughput requirement, and maximal throughput given a response …
Design Issues For The Parallelization Of An Optimal Interpolation Algorithm, Gregor Von Laszewski, Mike Seablom, Miloje Makivic, Peter Lyster
Design Issues For The Parallelization Of An Optimal Interpolation Algorithm, Gregor Von Laszewski, Mike Seablom, Miloje Makivic, Peter Lyster
Northeast Parallel Architecture Center
A regionalized optimal interpolation algorithm is currently used at the NASA Goddard Data Assimilation Office (DAO) for four dimensional data assimilation. Instead of using all observations regions are defined to approximate the solution. The sequential code for the regionalized optimal interpolation is very complex and in its current form unusable for MIMD machines. This paper describes the efforts at the DAO to parallelize the existing sequential algorithm. We outline three strategies transforming the sequential algorithm gradually to MIMD machines. A major requirement for the new parallel algorithm is the portability to as many MIMD machines as possible. Therefore, the parallel …
A Generalized Expression Optimization Hook For C++ On High-Performance Architectures, David J. Edelsohn
A Generalized Expression Optimization Hook For C++ On High-Performance Architectures, David J. Edelsohn
Northeast Parallel Architecture Center
C++ has gained broad acceptance as an object-oriented evolutionary extension to the C language, but it severely constrains methods for operating on class objects by forcing all data manipulation through an interface which assumes that all basic operations can be implemented as they are written: as unary or binary operators. C++ allows great flexibility in the creation of complex data structures which can perform the same functionality as built-in types of many other languages, but unfortunately it does not allow an equivalent level of flexibility so that operators acting on those data types can achieve the same level of efficiency …
Performance Modeling Of Load Balancing Algorithms Using Neural Networks, Ishfaq Ahmad, Arif Ghafoor, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Performance Modeling Of Load Balancing Algorithms Using Neural Networks, Ishfaq Ahmad, Arif Ghafoor, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
This paper presents a new approach that uses neural networks to predict the performance of a number of dynamic decentralized load balancing strategies. A distributed multicomputer system using any distributed load balancing strategy is represented by a unified analytical queuing model. A large simulation data set is used to train a neural network using the back–propagation learning algorithm based on gradient descent. The performance model using the predicted data from the neural network produces the average response time of various load balancing algorithms under various system parameters. The validation and comparison with simulation data show that the neural network is …
Scheduling Of Unstructured Communication On The Intel Ipsc/860, Jhy-Chun Wang, Sanjay Ranka
Scheduling Of Unstructured Communication On The Intel Ipsc/860, Jhy-Chun Wang, Sanjay Ranka
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
In this paper we present several algorithms for decomposing all-to-many personalized communication into a set of disjoint partial permutations. These partial permutations avoid node contention as well as link contention. We discuss the theoretical complexity of these algorithms and study their effectiveness both from the view of static scheduling and from runtime scheduling. Experimental results for our algorithms are presented on the iPSC/860.
Genetic Algorithms For Soft Decision Decoding Of Linear Block Codes, Harpal Maini, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
Genetic Algorithms For Soft Decision Decoding Of Linear Block Codes, Harpal Maini, Kishan Mehrotra, Chilukuri K. Mohan, Sanjay Ranka
College of Engineering and Computer Science - Former Departments, Centers, Institutes and Projects
Soft-decision decoding is an NP-hard problem of great interest to developers of communication systems. We show that this problem is equivalent to the problem of optimizing Walsh polynomials. We present genetic algorithms for soft-decision decoding of binary linear block codes and compare the performance with various other decoding algorithms including the currently developed A* algorithm. Simulation results show that our algorithms achieve bit-error-probabilities as low as 0:00183 for a [104; 52] code with a low signal-to-noise ratio of 2:5 dB, exploring only 22; 400 code words, whereas the search space contains 4:5 \Theta 10 15 codewords. We define a new …