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Parallel Computing Programming: more books (100)

Industrial Strength Parallel Computing
Parallel Computing by G. R. Joubert, Italy) Parco200 (2001 Naples, et all 2002-06-15
Parallel Computing Technologies: 9th International Conference, PaCT 2007, Pereslavl-Zalessky, Russia, September 3-7, 2007, Proceedings (Lecture Notes in ... Computer Science and General Issues)
Parallel Computing in Computational Chemistry (Acs Symposium Series)
Applied Parallel Computing. Computations in Physics, Chemistry and Engineering Science: Second International Workshop, PARA '95, Lyngby, Denmark, August ... (Lecture Notes in Computer Science)
Advances in Parallel Computing
Data-Parallel Computing: The Language Dimension by V. B. Muchnick, A. V. Shafarenko, 1996-06
Languages and Compilers for Parallel Computing: 6th International Workshop, Portland, Oregon, USA, August 12 - 14, 1993. Proceedings (Lecture Notes in Computer Science)
Network and Parallel Computing: IFIP International Conference, NPC 2007, Dalian, China, September 18-21, 2007, Proceedings (Lecture Notes in Computer Science ... Computer Science and General Issues)
Opportunities and Constraints of Parallel Computing
Languages and Compilers for Parallel Computing: 8th International Workshop, Columbus, Ohio, USA, August 10-12, 1995. Proceedings (Lecture Notes in Computer Science)
Parallel Computing on Distributed Memory Multiprocessors (NATO ASI Series / Computer and Systems Sciences)
Experimental Parallel Computing Architectures (Special Topics in Supercomputing, Vol 1)
Parallel Computing Technologies: 7th International Conference, PaCT 2003, Novosibirsk, Russia, September 15-19, 2003, Proceedings (Lecture Notes in Computer Science)

lists with details

CS 838 - Topics In Parallel Computing - Spring 1999
There is a couple of books on parallel algorithms and parallel computing youmight find useful as PVM and MPI2 are C/C++ parallel programming libraries.
http://www.cs.wisc.edu/~tvrdik/cs838.html

Extractions: Computer Sciences Department Instructor: Pavel Tvrdik email: tvrdik@cs.wisc.edu Office: CS 6376 Phone: Office hours: Tuesday/Thursday 9:30-11:00 a.m. or by appointment Lecture times: Tuesday/Thursday 08:00-09:15 a.m. Classroom: 1221 Computer Sciences Syllabus Schedule and materials Optional books Course requirements ... Grading policy The aim of the course is to introduce you into the art of designing efficient and analyzing parallel algorithms for both shared-memory and distributed memory machines. It is structured into four major parts. The first part of the course is a theoretical introduction into the field of design and analysis of parallel algorithms. We will explain the metrics for measuring the quality and performance of parallel algorithms with the emphasis on scalability and isoefficiency. To prepare the framework for parallel complexity theory, we will introduce a fundamental model, the PRAM model. Then we will introduce the basics of parallel complexity theory to provide a formal framework for explaining why some problems are easier to parallelize then some others. More specifically, we will study NC-algorithms and P-completeness. The second part of the course will deal with communication issues of distributed memory machines. Processors in a distributed memory machine need to communicate to overcome the fact that there is no global common shared storage and that all the information is scattered among processors' local memories. First we survey interconnection topologies and communication technologies, their structural and computational properties, embeddings and simulations among them. All this will form a framework for studying interprocessor communication algorithms, both point-to-point and collective communication operations. We will concentrate mainly on orthogonal topologies, such as hypercubes, meshes, and tori, and will study basic routing algorithms, permutation routing, and one-to-all as well as all-to-all communication operation algorithms. We conclude with some more realistic abstract models for distributed memory parallel computations.
LIACC --- Annual Plan For 1998 -- Declarative Programming And Parallel Computing
Go up to Top Go forward to parallel computing. Declarative programming and parallelcomputing. Research in this area is being sponsored by the following
http://www.liacc.up.pt/aplan98/englpl98_2.html
LIACC --- Annual Report 1997 -- Declarative Programming And Parallel Computing
Declarative programming and parallel computing. Projects. In this area during1997 there were 9 ongoing projects. The total effort at LIACC was 12.8
http://www.liacc.up.pt/arep97/englrep97_3.html

Extractions: There was continued work on developing the YAP system. The native code compiler was improved to support indexing. It was developed a generic mechanism for implementing extensions to the emulator. This mechanism provides a basis for extensions such as arrays and co-routining. Performance for X86 machines was substantially improved. Last, an high-level implementation scheme for tabulation was implemented. More information Study of semantic features of several type systems for declarative languages: an application of a characterization of type systems based on type constraints to the Curry type system, the Damas-Milner system and the Coppo-Dezani type system, and the comparison of two type languages for logic programming: regular types and regular deterministic types were made.
Programming Of Parallel Computers
Uppsala University Department of Information Technology Scientific computing,programming of parallel Computers 200409-14
http://www.it.uu.se/edu/course/homepage/algpar1/ht04/

Extractions: Computer simulations are used extensively both in industry and in academia. The demand for computing power is increasing faster and faster. To meet the demands parallel computers are becoming popular. Today, a powerful PC often contains two processors and it is easy to connect several PCs to a cluster, a powerful parallel computer. At the same time it is more difficult for the programmer to exploit the full capacity of the computer. The aims of the course are to give basic knowledge in parallel computers, algorithms and programming. To give knowledge in fundamental numerical algorithms and software for different parallel computers. To give skills in parallel programming. Classification of parallel computers. Different forms of memory organisation and program control. Different forms of parallelism. Programming models; programming in a local name space using MPI and in global name space using OpenMP. Data partitioning and load balancing algorithms. Measurements of performance; speedup, efficiency, flops. Parallelization of fundamental algorithms in numerical linear algebra; matrix-vector and matrix-matrix multiplication. Parallel sorting and searching. Software for parallel computers. GRID computing.
Parallel Programming Resources
IBM is offering parallel programming workshops for SP 2 users. parallel computing,an excelant introduction to parallel programming and the use of PVM.
http://www-math.cc.utexas.edu/math/parallel/bytopic.html

Extractions: Click on a topic to skip to that section. IBM POWERparallel Systems Products IBM's home page for its Scalable POWERparallel (SP) Systems Contains pointers to information on the SP-2 processors and high switch, the Parallel Environment, Load Leveler, and other software. IBM High-Performance Computing IBM High-Performance Computing page, some of this information is outdated by the above site. CERN SP2 Service page CERN has recently acquired an SP 2 machine to replace a VM system. This site contains some excellent documentation on getting started with the SP2 and an AIX for VM users guide. IBM AIX Parallel Environment This WWW page describes the software provided by IBM with the SP-2 system which supports parallel program development and execution. LoadLeveler IBM's load balancing and resource managment facility for parallel or distributed computing environments.
PCOMP
parallel and High Performance computing (HPC) are highly dynamic fields. is not an exhaustive compendium of all links related to parallel programming.
http://www.npaci.edu/PCOMP/

Extractions: About PCOMP Feedback Search My PCOMP ... User Groups Parallel and High Performance Computing (HPC) are highly dynamic fields. PCOMP provides parallel application developers a reliable, "one-stop" source of essential links to up-to-date, high-quality information in these fields. PCOMP is not an exhaustive compendium of all links related to parallel programming. PCOMP links are selected and classified by SDSC experts to be just those that are most relevant, helpful and of the highest quality. PCOMP links are checked on a regular basis to insure that the material and the links are current.
Distributed Parallel Computing Using Navigational Programming
This paper supports the claim that the NavP approach is better suited for generalpurpose parallel distributed programming than either MP or DSM.
http://citeseer.ist.psu.edu/pan04distributed.html
IBM Research | IBM Research | Putting The POWER In Parallel Computing
IBM to sponsor POWER processorbased parallel programming challenge in 2005 At IBM we are seeing that the parallel computing approach solves many of
http://domino.research.ibm.com/comm/research.nsf/pages/d.compsci.power.html

Extractions: Known for their enormous speed, memory, storage capacity and number crunching capabilities, IBM POWER-based parallel supercomputers have been used by universities, government agencies, research organizations and commercial enterprises to solve some of the most complex problems in physics, engineering, biology, geology and the environment. Scientists and engineers use IBM supercomputers based on the POWER processor to study the human genome, develop new vaccines, forecast the weather, study marine life, predict earthquakes, create simulations for building airplanes, develop new materials, look into the future of global warming, simulate auto crash tests, discover the origins of the universe and many other extraordinary, critical applications. The program will be judged on the correctness of results and how quickly it solves problems of increasing size. Contestants will be provided with training, MPI (Message-Passing Interface) educational material, and an example of functioning MPI applications, prior to the Challenge, at the 2005 Finals.
Qango : Science: Computer Science: Supercomputing And Parallel Computing: Progra
Home Science Computer Science Supercomputing and parallel computing programming, Suggest a Site. Science, etc. Categories
http://www.qango.com/dir/Science/Computer_Science/Supercomputing_and_Parallel_Co
Qango : Science: Computer Science: Supercomputing And Parallel Computing: Progra
Home Science Computer Science Supercomputing and parallel computing programming Message Passing Interface (MPI), Suggest a Site
http://www.qango.com/dir/Science/Computer_Science/Supercomputing_and_Parallel_Co
Parallel Programming Using C++ - Department Of Computing Science, University Of
Most programming systems for highperformance parallel computers widely used byscientists and engineers to solve complex problems are so-called universal
http://www.cs.ualberta.ca/research/library/0-262-73118-5.php

Extractions: Abstract from the Back Cover: Parallel Programming Using C++ presents a broad survey of current efforts to use C++, the most popular object-oriented programming language, on high-performance parallel computers and clusters of workstations. Sixteen different dialects and libraries are described by their developers and illustrated with many small example programs. Most programming systems for high-performance parallel computers widely used by scientists and engineers to solve complex problems are so-called universal languages that can run on a variety of computer platforms. Despite the benefits of this "platform independence", such a watered-down approach results in poor performance. A way to solve the problem, while preserving universality and efficiency, is to use an object-oriented programming language such as C++. Parallel object-oriented programming systems may be able to combine the speed of massively parallel computing with the ease of sequential programming. In each of the sixteen chapters a different system is described by its developers. The systems featured cover the entire spectrum of parallel programming paradigms from dataflow and distributed shared memory to message passing and control parallelism.
Pearson Education - Introduction To Parallel Computing
Introduction to parallel computing, Ananth Grama, George Karypis, Vipin Kumar, of parallel computing from introduction to architectures to programming
http://www.pearsoned.co.uk/Bookshop/detail.asp?item=100000000005961
Parallel Computing
parallel computing in scalable distributed shared memory multiprocessor system 4. Multiprocessor programming. 4.1. parallel Speedup. Amdahl s Law
http://www.informatik.tu-clausthal.de/~tchernykh/Scripts/Parallel_Computing.html

Extractions: P arallel Computing Instructor: Prof. Dr. Andrei Tchernykh Objective The objective of this course is to learn theoretical and practical problems of parallel computing, and to study the use of supercomputers for parallel algorithm implementation PART I. Foundation of Parallel Computing Background Computer and Computational Science 1_title.pdf 1-0_content.pdf, 1-1_computational.pdf Parallel computing paradigms; Motivation for Parallel Computing Fields of research Sequential and parallel paradigms Imperative and declarative parallel computation Functional programming Logic programming 1-2_paradigm.pdf Parallelism of program and computation Classification of parallelism; narrow and wide interpretation; Amdahls Law 1-3_background.pdf Data parallelism; 1-4_datapar.pdf Control parallelism, synchronization; 1-5_controlpar.pdf Data-Flow 1-6_dataflow.pdf 1-7_taxonomy.pdf PRAM computational models 1-8_pram.pdf Processor organization 1-9_topology.pdf
Upcoming Compiler And Parallel Computing Conferences
HIPS 2004 9th Int l Workshop on HighLevel parallel programming Models andSupportive The Internet parallel computing Archive s events list.
http://www.cs.rice.edu/~roth/conferences.html
IPCA : Parallel : Occam
PDF Introduction to parallel computing computing parallel programming
http://www.hensa.ac.uk/parallel/occam/
Programming For Parallel And High-Performance Computing
programming for parallel and HighPerformance computing Jonathan Wang sBookshelf on parallel computing, including Distributed Batch Processing,
http://www.kanadas.com/parallel/

Extractions: Created: 12/9/94, Modified: 11/22/95. See also [Parent page] [Kanada's home page in English] [Kanada's home page in Japanese] Language List: Parallel (search) by Jonathan Hardwick Software Engineering Topics ( Nearly empty on 12/8/94 David A. Bader's Home Page , which contains Reading List on Parallel Programming Languages by Guy E. Blelloch, including Data parallelism, Explicit communication models, Functional languages, Non-determinism, Automatic parallelization, The real world, and so on. Jonathan Wang's Bookshelf on Parallel Computing , including Distributed Batch Processing, Parallel Computing (Message Passing, Shared Object, Misc), Super Computers/labs, Compiler/Parallelizer, Benchmarks, Fault Tolerance and Load Balance, Parallel Software, Comprehensive Links at Other Institutes, and so on. Research Area "Parallel Computing" An Introduction Documentation for Parallelists HPCC Blue Book - TOC HP Fortran Draft, Archives, Papers, ...
Parallel Computing Research
parallel computing Research Caltech s Summer Research Program for Women inFinal Year. Education / Outreach. EDUCATION / OUTREACH
http://www.crpc.rice.edu/newsletters/sum99/
UC Berkeley CS267 Home Page: Spring 1999
Applications of parallel Computers. Spring 1999. TuTh 12302, 310 Soda Resources for parallel machines, programming, tools, applications,
http://www.cs.berkeley.edu/~demmel/cs267_Spr99/

Extractions: (send email) Handout 1: Class Introduction for Spring 1999 Handout 2: Class Survey for Spring 1999 The Sharks and Fish problem. Assignment 1: Warm-up exercise Results of assignment 1 Assignment 2: Memory Benchmark and Matrix-multiply race Results of assignment 2 ... The notes from the Spring 96 CS 267 will be updated and installed here, along with daily notes. Lecture 1, 1/19/99: Introduction to Parallel Computing Lecture 2, 1/21/99: Memory Hierarchies and Optimizing Matrix Multiplication Lecture 3, 1/26/99: Introduction to Parallel Architectures and Programming Models Lecture 4, 1/28/99: More about Shared Memory Processors and Programming ... Lecture 15, 3/9/99: Graph Partitioning - II Lecture 16, 3/11/99: MetaComputing
WANG'S BOOKSHELF (Parallel Computing)
Welcome to Jonathan Wang s Bookshelf on parallel computing parallel ProgrammingSystems For Workstation Clusters Craig Douglas
http://www.umcs.maine.edu/~shamis/wang.html

Extractions: How fast can it be? (The top 500 super computers, in postscript, size 10M) Contents: Distributed Batch Processing Parallel Computing Message Passing Shared Object Misc (yet to be sorted) Super Computers/labs Compiler/Parallelizer Benchmarks Fault Tolerance and Load Balance Parallel Software Comprehensive Links at Other Institutes Personal Stuff Mail Drop 1. Distributed Batch Processing dqs Distributed Queueing System, Tom Green (green@scri.fsu.edu), Florida State University nqs Network Queueing System, Brent A. Kingsbury, Sterling Software Inc. Another version from CERN. CONDOR Mike Litzkom (mike@cs.wisc.edu), Univeristy of Wisconsin DJM , Distributed Job Manager, University of Minnesota. LSBATCH, Utopia LSF Commercial product, documents only. University of Toronto network batch processing summery by Norbert Juffa (norbert@iit.com) A Comparison of Queueing, Cluster and Distributed Computing Systems
Parallel Computing Toolkit: Product Information
Programs written using parallel computing Toolkit are platform independent andcan run on any computer for which Mathematica is available.
http://www.wolfram.com/products/applications/parallel/

Extractions: PreloadImages('/common/images2003/btn_products_over.gif','/common/images2003/btn_purchasing_over.gif','/common/images2003/btn_services_over.gif','/common/images2003/btn_new_over.gif','/common/images2003/btn_company_over.gif','/common/images2003/btn_webresource_over.gif'); Products Parallel Computing Toolkit Features New in Version 2 ... Give us feedback Sign up for our newsletter: Tackle large-scale problems with the power of parallel computing. Engineers, scientists, and analysts will find Parallel Computing Toolkit ideal for product design and problem solving. Educators can use this package in classrooms and labs to quickly convey and explore the concepts of parallel computing. Parallel Computing Toolkit brings parallel computation to anyone with access to more than one processor, regardless of whether the processors are multiprocessor machines, networked PCs, or a Top 500 supercomputer. This package implements many programming primitives for writing and controlling parallel Mathematica programs as well as high-level commands for common parallel operations. Programs written using

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