Combining object-oriented techniques with data-driven parallel execution on message passing, MIMD computers

1989 ◽  
Vol 24 (4) ◽  
pp. 129-131
Author(s):  
E. J. Segall
Keyword(s):  
Message Passing ◽  
Object Oriented ◽  
Parallel Execution ◽  
Data Driven

Parallel Nonnegative Matrix Factorization via Newton Iteration

2016 ◽  
Vol 26 (03) ◽  
pp. 1650014 ◽  
Author(s):  
Markus Flatz ◽  
Marián Vajteršic
Keyword(s):  
Shared Memory ◽  
Matrix Factorization ◽  
Message Passing ◽  
Nonnegative Matrix Factorization ◽  
Nonnegative Matrix ◽  
Newton Iteration ◽  
Parallel Execution ◽  
Kkt Conditions ◽  
Nonnegative Matrices ◽  
First Order

The goal of Nonnegative Matrix Factorization (NMF) is to represent a large nonnegative matrix in an approximate way as a product of two significantly smaller nonnegative matrices. This paper shows in detail how an NMF algorithm based on Newton iteration can be derived using the general Karush-Kuhn-Tucker (KKT) conditions for first-order optimality. This algorithm is suited for parallel execution on systems with shared memory and also with message passing. Both versions were implemented and tested, delivering satisfactory speedup results.

Simple type-theoretic foundations for object-oriented programming

1994 ◽  
Vol 4 (2) ◽  
pp. 207-247 ◽  
Author(s):  
Benjamin C. Pierce ◽  
David N. Turner
Keyword(s):  
Message Passing ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Simple Type ◽  
Theoretic Foundations

AbstractWe develop a formal, type-theoretic account of the basic mechanisms of object-oriented programming: encapsulation, message passing, subtyping and inheritance. By modelling object encapsulation in terms of existential types instead of the recursive records used in other recent studies, we obtain a substantial simplification both in the model of objects and in the underlying typed λ-calculus.

scholarly journals Parallel Object-Oriented Computation Applied to a Finite Element Problem

1993 ◽  
Vol 2 (4) ◽  
pp. 133-144 ◽  
Author(s):  
Jon B. Weissman ◽  
Andrew S. Grimshaw ◽  
R.D. Ferraro
Keyword(s):  
Finite Element ◽  
Message Passing ◽  
Large Scale ◽  
Processing System ◽  
Object Oriented ◽  
Data Parallel ◽  
Programming Tools ◽  
Comparable Performance ◽  
Oriented Parallel ◽  
Performance Results

The conventional wisdom in the scientific computing community is that the best way to solve large-scale numerically intensive scientific problems on today's parallel MIMD computers is to use Fortran or C programmed in a data-parallel style using low-level message-passing primitives. This approach inevitably leads to nonportable codes and extensive development time, and restricts parallel programming to the domain of the expert programmer. We believe that these problems are not inherent to parallel computing but are the result of the programming tools used. We will show that comparable performance can be achieved with little effort if better tools that present higher level abstractions are used. The vehicle for our demonstration is a 2D electromagnetic finite element scattering code we have implemented in Mentat, an object-oriented parallel processing system. We briefly describe the application. Mentat, the implementation, and present performance results for both a Mentat and a hand-coded parallel Fortran version.

DKRL — AN OBJECT-ORIENTED LANGUAGE TO SUPPORT PROBLEM SOLVING IN DISTRIBUTED BLACKBOARD SYSTEMS

1993 ◽  
Vol 07 (02) ◽  
pp. 221-242 ◽  
Author(s):  
MANOJ K. SAXENA ◽  
K.K. BISWAS ◽  
P.C.P. BHATT
Keyword(s):  
Problem Solving ◽  
Knowledge Base ◽  
Message Passing ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Current Status ◽  
External Knowledge ◽  
Blackboard Systems ◽  
Problem Solving Process ◽  
Internal Knowledge

For distributed problem solving systems, there is a need to define knowledge at two levels, one external to the agents and the other internal to the agents. External knowledge is required to achieve cooperation among agents and global convergence of the problem solving process, whereas internal knowledge is required to solve the sub-problems assigned to the agents. External knowledge specifies the role of each agent and its relationship with other agents in the system. Internal knowledge specifies knowledge structure and the problem solving process within each agent. DKRL is an object-oriented language for describing distributed blackboard systems. In DKRL a problem solving system is described as a collection of distributed intelligent, autonomous agents (modelled as objects), cooperating to solve the problem. An agent consists of a knowledge base, a behaviour part, a local controller, a monitor, and a communication controller. DKRL has characteristics of a dynamic nature, i.e. the agents can be created dynamically and the relationship among them also changes dynamically. An agent in DKRL’s computational model cannot be activated by more than one message at the same time and uses a virtual synchrony environment for message transmission among agents. This model combines the advantages of remote procedure calls with those of asynchronous message passing. DKRL allows object-oriented programming techniques to be used for system development and facilitates the development by allowing one-to-one mapping between the objects in the knowledge model and the knowledge base of the agent. In this paper, we give an overview of the distributed blackboard paradigm for which DKRL was developed as well as the design considerations. We also propose and formally describe the underlying models of DKRL and explain how concurrency is exploited by DKRL. We conclude with the current status of and preliminary experience with DKRL in using it for the development of a gate assignment problem.

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