The most exciting development in parallel computer architecture is the convergence of traditionally disparate approaches on a common machine structure. This book explains the forces behind this convergence of shared-memory, message-passing, data parallel, and data-driven computing architectures. It then examines the design issues that are critical to all parallel architecture across the full range of modern design, covering data access, communication performance, coordination of cooperative work, and correct implementation of useful semantics. It not only describes the hardware and software techniques for addressing each of these issues but also explores how these techniques interact in the same system. Examining architecture from an application-driven perspective, it provides comprehensive discussions of parallel programming for high performance and of workload-driven evaluation, based on understanding hardware-software interactions.


* synthesizes a decade of research and development for practicing engineers, graduate students, and researchers in parallel computer architecture, system software, and applications development

* presents in-depth application case studies from computer graphics, computational science and engineering, and data mining to demonstrate sound quantitative evaluation of design trade-offs 

* describes the process of programming for performance, including both the architecture-independent and architecture-dependent aspects, with examples and case-studies

* illustrates bus-based and network-based parallel systems with case studies of more than a dozen important commercial designs

Table of Contents

1 Introduction 
2 Parallel Programs 
3 Programming for Performance 
4 Workload-Driven Evaluation 
5 Shared Memory Multiprocessors 
6 Snoop-based Multiprocessor Design 
7 Scalable Multiprocessors
8 Directory-based Cache Coherence
9 Hardware-Software Tradeoffs 
10 Interconnection Network Design 
11 Latency Tolerance 
12 Future Directions 
APPENDIX A Parallel Benchmark Suites

Parallel Computer Architecture: A Hardware/Software Approach

Several existing volume rendering algorithms operate by factoring the viewing transformation into a 3D shear parallel to the data slices, a projection to form an intermediate but distorted image, and a 2D warp to form an undistorted final image. We extend this class of algorithms in three ways. First, we describe a new object-order rendering algorithm based on the factorization that is significantly faster than published algorithms with minimal loss of image quality. Shear-warp factorizations have the property that rows of voxels in the volume are aligned with rows of pixels in the intermediate image. We use this fact to construct a scanline-based algorithm that traverses the volume and the intermediate image in synchrony, taking advantage of the spatial coherence present in both. We use spatial data structures based on run-length encoding for both the volume and the intermediate image. Our implementation running on an SGI Indigo workstation renders a 2563 voxel medical data set in one second. Our second extension is a shear-warp factorization for perspective viewing transformations, and we show how our rendering algorithm can support this extension. Third, we introduce a data structure for encoding spatial coherence in unclassified volumes (i.e. scalar fields with no precomputed opacity). When combined with our shear-warp rendering algorithm this data structure allows us to classify and render a 2563 voxel volume in three seconds. The method extends to support mixed volumes and geometry and is parallelizable.

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Fast volume rendering using a shear-warp factorization of the viewing transformation

Intelligent agents are employed as the central characters in this new introductory text. Beginning with elementary reactive agents, Nilsson gradually increases their cognitive horsepower to illustrate the most important and lasting ideas in AI. Neural networks, genetic programming, computer vision, heuristic search, knowledge representation and reasoning, Bayes networks, planning, and language understanding are each revealed through the growing capabilities of these agents. The book provides a refreshing and motivating new synthesis of the field by one of AI's master expositors and leading researchers. Artificial Intelligence: A New Synthesis takes the reader on a complete tour of this intriguing new world of AI.

* An evolutionary approach provides a unifying theme 
* Thorough coverage of important AI ideas, old and new
* Frequent use of examples and illustrative diagrams
* Extensive coverage of machine learning methods throughout the text
* Citations to over 500 references
* Comprehensive index

Table of Contents

1 Introduction
2 Stimulus-Response Agents
3 Neural Networks 
4 Machine Evolution 
5 State Machines 
6 Robot Vision 
7 Agents that Plan 
8 Uninformed Search 
9 Heuristic Search 
10 Planning, Acting, and Learning 
11 Alternative Search Formulations and Applications 
12 Adversarial Search 
13 The Propositional Calculus 
14 Resolution in The Propositional Calculus 
15 The Predicate Calculus 
16 Resolution in the Predicate Calculus 
17 Knowledge-Based Systems 
18 Representing Commonsense Knowledge 
19 Reasoning with Uncertain Information 
20 Learning and Acting with Bayes Nets 
21 The Situation Calculus 
22 Planning 
23 Multiple Agents 
24 Communication Among Agents 
25 Agent Architectures

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Artificial Intelligence: A New Synthesis

Artificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods for incorporating uncertainty into models. This book is devoted to providing a thorough and up-to-date survey of this field for researchers and students.

Expert Systems and Probabilistic Network Models

From the Publisher:
The Message Passing Interface (MPI) specification is widely used for solving significant scientific and engineering problems on parallel computers There exist more than a dozen implementations on computer platforms ranging from IBM SP-2 supercomputers to clusters of PCs running Windows NT or Linux ("Beowulf" machines) The initial MPI Standard document, MPI-1, was recently updated by the MPI Forum The new version, MPI-2, contains both significant enhancements to the existing MPI core and new features
Using MPI is a completely up-to-date version of the authors' 1994 introduction to the core functions of MPI It adds material on the new C++ and Fortran 90 bindings for MPI throughout the book It contains greater discussion of datatype extents, the most frequently misunderstood feature of MPI-1, as well as material on the new extensions to basic MPI functionality added by the MPI-2 Forum in the area of MPI datatypes and collective operations
Using MPI-2 covers the new extensions to basic MPI These include parallel I/O, remote memory access operations, and dynamic process management The volume also includes material on tuning MPI applications for high performance on modern MPI implementations

Using MPI-2: Advanced Features of the Message Passing Interface

This book explains what automated reasoning is and what it can do and then demonstrates how to use it to solve complex problems with applications in logic circuit design, circuit validation, real-time system design and expert systems. A diskette containing the automated reasoning program "Otter" is included. It is available for the first time to PCs and workstations. The book has input files, commentary, examples in "Otter" notation and a user's manual that enables readers to experiment with the material presented as well as with ideas of their own. Other features include: various challenge problems that allow readers to test, compare and evaluate new ideas and techniques; techniques for answering open questions and finding shorter proofs; methods for finding such proofs; examples and puzzles to aid in the understanding of parallel versions of an automated reasoning program; and problems.

Automated reasoning: Introduction and applications

Portable Programs for Parallel Processors

How can a program written in pure applicative LISP be reused in a Fortran environment? One answer is by automatically transforming it from LISP into Fortran. In this paper we discuss a practical application of this technique-one that yields an efficient Fortran program. We view this process as an example of abstract programming, in which the LISP program constitutes an abstract specification for the Fortran version. The idea of strategy-a strategy for getting from LISP to Fortran-is basic to designing and applying the transformations. One strategic insight is that the task is easier if the LISP program is converted to ``recursive'' Fortran, and then the recursive Fortran program is converted to nonrecursive standard Fortran. Another strategic insight is that much of the task can be accomplished by converting the program from one canonical form to another. Developing a strategy also involves making various implementation decisions. One advantage of program transformation methodology is that it exposes such decisions for examination and review. Another is that it enables optimizations to be detected and implemented easily. Once a strategy has been discovered, it can be implemented by means of rewrite-rule transformations using the TAMPR program transformation system. The transformational approach to program reuse based on this strategy has a measure of elegance. It is also practical-the resulting Fortran program is 25 percent faster than its compiled LISP counterpart, even without extensive optimization.

Program Reusability through Program Transformation

Automated reasoning (2nd ed.): introduction and applications

Writing correct numerical software is a complex, demanding, and, at times, even a boring, task. In this chapter, we describe an approach to constructing software—program specification and transformation—and allied tools that can help not only to ensure the correctness of numerical computations but also automate much of the drudge-work involved in preparing such software. This approach to software construction holds out the exciting prospect of enabling the numerical analyst or specialist in scientific computing to concentrate on correctly capturing the problem to be solved, while delegating the details of programming the software and adapting it to specialized computing environments to automated tools.

James M. Boyle

Papers

Automated reasoning: Introduction and applications

Portable Programs for Parallel Processors

Program Reusability through Program Transformation

Automated reasoning (2nd ed.): introduction and applications

The TAMPR program transformation system: simplifying the development of numerical software