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Topic: Parallel programming

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	Parallel computing - Wikipedia, the free encyclopedia
		Parallel computing is the simultaneous execution of the same task (split up and specially adapted) on multiple processors in order to obtain results faster.
		Parallel processor machines are also divided into symmetric and asymmetric multiprocessors, depending on whether all the processors are capable of running all the operating system code and, say, accessing I/O devices or if some processors are more or less privileged.
		Such mechanisms may provide either implicit parallelism -- the system (the compiler or some other program) partitions the problem and allocates tasks to processors automatically (also called automatic parallelizing compilers) -- or explicit parallelism where the programmer must annotate his program to show how it is to be partitioned.
	en.wikipedia.org /wiki/Parallel_computing (1086 words)

	Allen, Wilkinson, and Alley, "Parallel Programming" (Site not responding. Last check: 2007-10-06)
		Another new aspect for undergraduate parallel programming education is the use of guest speakers to expose students to the state of the art.
		The parallel programming objective of that first semester lab assignment is purely to familiarize the students with the parallel programming environment at UNCC by acquainting them with the process of editing, compiling, and running parallel programs.
		The objective is to familiarize them with the parallel programming environment available to them and simply orients them to the fact that under certain circumstances it is possible to reduce the computation time by throwing multiple processors at the solution of a problem.
	www.cs.dartmouth.edu /FPCC/papers/Wilkinson (2815 words)

	Parallel Programming Environments
		Programming environments correspond roughly to languages and libraries, as the examples below illustrate -- for example, HPF is a set of extensions to Fortran 90 (a "parallel language", so to speak), while MPI is a library of function calls.
		This is a complicated way to sort parallel programming environments, since a single programming environment can be classified under more than one programming model (for example, the Linda coordination language can be thought of in terms of a distributed-data-structure model or a coordination model).
		The philosophy behind Cilk is that programmers should concentrate on structuring their programs to expose parallelism and exploit locality, leaving the runtime system with the responsibility of scheduling the computation to run efficiently on a given platform.
	www.cise.ufl.edu /research/ParallelPatterns/PatternLanguage/Background/ProgEnvs.htm (4446 words)

	Introduction to Parallel Programming
		Programming with message passing is done by linking with and making calls to libraries which manage the data exchange between processors.
		Programming with data parallel model is accomplished by writing a program with data parallel constructs and compiling it with a data parallel compiler.
		All parallelism is explicit: the programmer is responsible for parallelism the program and implementing the MPI constructs.
	www.mhpcc.edu /training/workshop/parallel_intro/MAIN.html (4272 words)

	Parellel port output
		If the parallel port is integrated to the motherboard (like in many new computers) repairing damaged parallel port may be expensive (in many cases it it is cheaper to replace the whole motherborard than repair that port).
		Programming tip: Usually, it is most convenient to use #define statements to give pins logical names that have meaning in the context of your application.
		This parallel port type also implemented the same three registers as used by SPP for the control and monitoring of the data and handshaking lines; these are the data port, status port, and control port.
	www.epanorama.net /circuits/parallel_output.html (15337 words)

	Parallel Programming - Basic Theory For The Unwary
		A parallel system is a system (software and/or hardware) that allows one to write programs whose different parts are carried out in different threads of execution.
		In order to better understand what a parallel (or parallelic) system is, we should check what are the different components such a system is made of.
		Parallel systems implementation may be done in software, in hardware, or as a combination of both.
	users.actcom.co.il /~choo/lupg/tutorials/parallel-programming-theory/parallel-programming-theory.html (4652 words)

	Parallel Programming Pattern Language: Annotated Bibliography
		Using a program for modeling electromagnetic waves as an example, the power of the models is used to show how simple optimizations improve efficiency by a factor of 4-5 on a 64 processor CM-5 (using ghost nodes, split-phase communications and signaled stores.
		The chapters discussing architectures and programming languages are run-of-the-mill, but the bulk of the book describes and analyzes a wide variety of algorithms for mesh- and hypercube-based multicomputers (chosen as representative of sparsely-connected and densely-connected machines respectively).
		It is shown that any program written for the idealized shared-memory model of parallel computation can be simulated on a hypercube architecture with only constant factor inefficiency, provided that the original program has a certain amount of parallel slackness.
	www.cise.ufl.edu /research/ParallelPatterns/PatternLanguage/Background/Bibliography.htm (9486 words)

	Amazon.com: Parallel Programming Using C++ (Scientific and Engineering Computation): Books (Site not responding. Last check: 2007-10-06)
		One reason for this is that most parallel programming systems have failed to insulate their users from the architectures of the machines on which they have run.
		By hiding the architecture-specific constructs required for high performance inside platform-independent abstractions, parallel object-oriented programming systems may be able to combine the speed of massively-parallel computing with the comfort of sequential programming.
		For the parallel programming community, a common parallel application is discussed in each chapter, as part of the description of the system itself.
	www.amazon.com /exec/obidos/tg/detail/-/0262731185?v=glance (798 words)

	High-Level Parallel Programming Models and Supportive Environments (HIPS 2004)
		While this year's workshop focuses on component-based programming, contributions on other high-level programming models and supportive environments for parallel and distributed systems are equally welcome.
		One of the keys for the advancement of parallel processing are the existence of high-level programming models and abstractions that allow one to more easily produce truly efficient applications across a range of parallel architectures.
		This situation requires strong research efforts in the design of parallel programming models and languages supporting component-based systems that are both at a high conceptual level and implemented efficiently, in the development of supportive tools, and in the integration of languages and tools into convenient programming environments.
	www.cca-forum.org /ipdps-workshop (434 words)

	PARALLEL PROGRAMMING TOOLS (Site not responding. Last check: 2007-10-06)
		Indeed, developing a parallel programming environment is a priority for all the NSF supercomputer centers.
		Parallel computers have a building-block-like architecture--that is, they can be scaled up in size as more computing power is needed.
		Programs written with these tools can be easily ported to parallel machines with other architectures such as a shared memory machine or a network of workstations.
	www.sdsc.edu /GatherScatter/gsmar92/ParallelProgTools.html (1372 words)

	Parallel Programming (Site not responding. Last check: 2007-10-06)
		Parallel processing has matured to the point where it has begun to make a considerable impact on the computer marketplace.
		This course serves as an introduction to the area of parallel systems with a special focus on programming for parallel architectures.
		This course is accompanied by a laboratory course whose focus is on practical programming of parallel architectures.
	dps.uibk.ac.at /~tf/lehre/ws0405/ps (509 words)

	Parallel Programming (Site not responding. Last check: 2007-10-06)
		Emergent programming styles for solving problems with a variety of parallel models.
		Paradigms basic to the design of efficient parallel algorithms, methods of problem decomposition, models for evaluating program performance, and techniques for optimizing parallel compilers.
		A wide variety of problems with programming exercises on Linda TS/Net, illustrating a general approach to programming parallel machines.
	www.cs.yale.edu /homes/gelernter/424a.html (394 words)

	SAL- Parallel Computing - Programming Languages & Systems
		Most parallel programming languages are conventional or sequential programming languages with some parallel extensions.
		A compiler is a program that converts the source code written in a specific language into another format, eventually in assembly or machine code that a computer understands.
		NESL -- a parallel programming language which is easy and portable.
	ceu.fi.udc.es /SAL/C/1/index.shtml (402 words)

	The PC's Parallel Port
		Jan's Parallel Port FAQ has answers to frequently asked questions about using, interfacing, and programming the parallel port in all of its modes.
		NFPT (No-Frills Parallel Transfer) includes a DOS program with source code and instructions for building an ECP test cable for transferring files between two PCs using ECP mode.
		There are various ways for applications to access the parallel port and other I/O ports in PCs, including directly accessing port addresses, communicating with a driver that accessing port addresses and using Windows' built-in drivers.
	www.lvr.com /parport.htm (2333 words)

	Amazon.com: Practical Parallel Programming (Scientific and Engineering Computation): Books (Site not responding. Last check: 2007-10-06)
		Practical Parallel Programming provides scientists and engineers with a detailed, informative, and often critical introduction to parallel programming techniques.
		Following a review of the fundamentals of parallel computer theory and architecture, it describes four of the most popular parallel programming models in use today -- data parallelism, shared variables, message passing, and Linda -- and shows how each can be used to solve various scientific and numerical problems.
		Practical Parallel Programming will be particularly helpful for scientists and engineers who use high-performance computers to solve numerical problems and do physical simulations but who have little experience of networking or concurrency.
	www.amazon.com /exec/obidos/tg/detail/-/0262231867?v=glance (555 words)

	High-Level Parallel Programming Models and Supportive Environments (HIPS'02) (Site not responding. Last check: 2007-10-06)
		High-level programming environments are the key to success of the next generation of software systems.
		HIPS'02 focuses on high-level programming issues of parallel architectures, ranging from SMPs and DSM systems to workstation clusters to massively-parallel grids.
		Its goal is to bring together researchers working in the areas of applications, computational models, language design, compilers, system architecture, and programming tools to discuss new ideas and developments.
	www.ecn.purdue.edu /hips02 (362 words)

	Parallel Programming Laboratory
		We aim to reach a point where, with our freely distributed software base, complex irregular and dynamic applications can be (a) developed quickly, and (b) perform scalably on machines with thousands of processors.
		Tools: Charm++, a parallel C++ library, and AMPI, an adaptive MPI implementation, provide processor virtualization.
		To further enhance programmer productivity, we are developing frameworks that automate domain-specific parallelization techniques, and producing reusable libraries for parallel algorithms.
	charm.cs.uiuc.edu (261 words)

	Cilk Home Page (Site not responding. Last check: 2007-10-06)
		Cilk is a language for multithreaded parallel programming based on ANSI C. Cilk is designed for general-purpose parallel programming, but it is especially effective for exploiting dynamic, highly asynchronous parallelism, which can be difficult to write in data-parallel or message-passing style.
		Unlike many other multithreaded programming systems, Cilk is algorithmic, in that the runtime system employs a scheduler that allows the performance of programs to be estimated accurately based on abstract complexity measures.
		Porch is a source-to-source compiler that translates C programs into semantically equivalent C programs which are capable of saving and recovering from portable checkpoints.
	supertech.lcs.mit.edu /cilk (777 words)

	CODE Visual Parallel Programming System
		is a visual parallel programming system, allowing users to compose sequential programs into a parallel one.
		The parallel program is a directed graph, where data flows on arcs connecting the nodes representing the sequential programs.
		The sequential programs may be written in any language, and CODE will produce parallel programs for a variety of architectures, as its model is architecture-independent.
	www.cs.utexas.edu /users/code (153 words)

	Parallel Port Programming
		Parallel port programming is easier than it sounds.
		Now usually when sending data to the parallel port you need a slight delay to ensure that the data has been sent, and not lost.
		Programming the parallel port can be a lot fun.
	www.gmonline.demon.co.uk /cscene/CS4/CS4-02.html (975 words)

	UC Berkeley CS267 Home Page: Spring 1996
		Lecture 7, 2/6/96: Parallel Programming with Split-C. Lecture 8, 2/8/96: Floating Point Arithmetic.
		Lectures 11 and 12, 2/{20,22}/96: Sources of Parallelism and Locality in Simulation I. Lecture 13, 2/27/96: Sources of Parallelism and Locality in Simulation II.
		Lectures 27, 4/23/96: Parallel Sparse Cholesky (under construction).
	www.cs.berkeley.edu /~demmel/cs267 (415 words)

	NESL: A Parallel Programming Language
		It integrates various ideas from the theory community (parallel algorithms), the languages community (functional languages) and the system's community (many of the implementation techniques).
		Nested data parallelism: this feature offers the benefits of data parallelism, concise code that is easy to understand and debug, while being well suited for irregular algorithms, such as algorithms on trees, graphs or sparse matrices (see the examples above or in our library of algorithms).
		Algorithms are typically significantly more concise in NESL than in most other parallel programming languages.
	www-2.cs.cmu.edu /~scandal/nesl.html (756 words)

	Parallel Computing Links
		Parallel Numerical Algorithms, Michael Heath, University of Illinois
		Introduction to parallel programming with C++, John Steel, Queen Mary and Westfield College
		Sandia National Laboratory's Trilinos Project is an effort to develop parallel solver algorithms and libraries within an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific applications.
	www.indiana.edu /~rac/hpc/links.html (495 words)

	Concurrent Programming with J2SE 5.0
		Java is a multithreaded programming language that makes programming with threads easier, by providing built-in language support for threads.
		This leads developers to implement their own high-level synchronization facilities, but given the difficulty of concurrency issues, their implementations may not be correct, efficient, or high quality.
		This package does for concurrent programming what the collection framework has done to data structures -- essentially freeing the developer from re-inventing the wheel with possibly incorrect and inefficient implementations.
	java.sun.com /developer/technicalArticles/J2SE/concurrency (2038 words)

	Parallel Programming with MPI
		Parallel Programming with MPI is an elementary introduction to programming parallel systems that use the MPI 1.1 library of extensions to C and Fortran.
		It is intended for use by students and professionals with some knowledge of programming conventional, single-processor systems, but who have little or no experience programming multiprocessor systems.
		The CHIMP implementation developed by researchers at the Edinburgh Parallel Computing Centre also runs on networks of workstations.
	fawlty.cs.usfca.edu /mpi (550 words)

	Parallel Programming Resources (Site not responding. Last check: 2007-10-06)
		PVM is a subroutine library which allows you to distribute you program across many machines in a heterogeneous network (i.e.
		A good description of many aspects of parallel programming, set in the context of the PVM package.
		Split-C, a parallel extension of the C programming language
	www.utexas.edu /math/parallel/bytopic.html (496 words)

	HLRS - Organization - Parallel Computing - Parallel Programming Workshop ONLINE
		Here, you can find the full workshop program with links to all data on this CD combined with links to the other content that you can find on the web, i.e., via the Online Parallel Programming Workshop.
		Heat conduction program, a parallelization example with MPI (talk)
		Each document is reduced by a factor of 0.707, i.e., two pages of the original standard document is printed on one paper page.
	www.hlrs.de /organization/par/par_prog_ws (1556 words)

	Open Directory - Computers: Parallel Computing: Programming (Site not responding. Last check: 2007-10-06)
		AppleSeed - Information for clustering and writing programs for Macintoshes using MPI.
		Jaguar - Java Access to Generic Underlying Architectural Resources - Jaguar is an extension of the Java runtime environment which enables direct Java access to operating system and hardware resources, such as fast network interfaces, memory-mapped and programmed I/O, and specialized machine instruction sets.
		OpenMP - An API for multi-platform shared-memory parallel programming in C/C++ and Fortran.
	dmoz.org /Computers/Parallel_Computing/Programming (130 words)

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