A vast body of theoretical research has focused either on overly simplistic models of parallel computation, notably the PRAM, or overly specific models that have few representatives in the real world. Both kinds of models encourage exploitation of formal loopholes, rather than rewarding development of techniques that yield performance across a range of current and future parallel machines. This paper offers a new parallel machine model, called LogP, that reflects the critical technology trends underlying parallel computers. it is intended to serve as a basis for developing fast, portable parallel algorithms and to offer guidelines to machine designers. Such a model must strike a balance between detail and simplicity in order to reveal important bottlenecks without making analysis of interesting problems intractable. The model is based on four parameters that specify abstractly the computing bandwidth, the communication bandwidth, the communication delay, and the efficiency of coupling communication and computation. Portable parallel algorithms typically adapt to the machine configuration, in terms of these parameters. The utility of the model is demonstrated through examples that are implemented on the CM-5.

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LogP: towards a realistic model of parallel computation

American Bankruptcy Institute Law Review 17 Am. Bankr. Inst. L. Rev., No. 1, Spring, 2009. Boston College Law Review 50 B.C. L. Rev., No. 3, May, 2009. Boston University Public Interest Law Journal 18 B.U. Pub. Int. L.J., No. 2, Spring, 2009. Cardozo Journal of Conflict Resolution 10 Cardozo J. Conflict Resol., No. 2, Spring, 2009. Cardozo Public Law, Policy, & Ethics Journal 7 Cardozo Pub. L. Pol’y & Ethics J., No. 3, Summer, 2009. Chicago Journal of International Law 10 Chi. J. Int’l L., No. 1, Summer, 2009. Colorado Journal of International Environmental Law and Policy 20 Colo. J. Int’l Envtl. L. & Pol’y, No. 2, Winter, 2009. Columbia Journal of Law & the Arts 32 Colum. J.L. & Arts, No. 3, Spring, 2009. Connecticut Public Interest Law Journal 8 Conn. Pub. Int. L.J., No. 2, Spring-Summer, 2009. Cornell Journal of Law and Public Policy 18 Cornell J.L. & Pub. Pol’y, No. 1, Fall, 2008. Cornell Law Review 94 Cornell L. Rev., No. 5, July, 2009. Creighton Law Review 42 Creighton L. Rev., No. 3, April, 2009. Criminal Law Forum 20 Crim. L. Forum, Nos. 2-3, Pp. 173-394, 2009. Delaware Journal of Corporate Law 34 Del. J. Corp. L., No. 2, Pp. 433-754, 2009. Environmental Law Reporter News & Analysis 39 Envtl. L. Rep. News & Analysis, No. 7, July, 2009. European Journal of International Law 20 Eur. J. Int’l L., No. 2, April, 2009. Family Law Quarterly 43 Fam. L.Q., No. 1, Spring, 2009. Georgetown Journal of International Law 40 Geo. J. Int’l L., No. 3, Spring, 2009. Georgetown Journal of Legal Ethics 22 Geo. J. Legal Ethics, No. 2, Spring, 2009. Golden Gate University Law Review 39 Golden Gate U. L. Rev., No. 2, Winter, 2009. Harvard Environmental Law Review 33 Harv. Envtl. L. Rev., No. 2, Pp. 297-608, 2009. International Review of Law and Economics 29 Int’l Rev. L. & Econ., No. 1, March, 2009. Journal of Environmental Law and Litigation 24 J. Envtl. L. & Litig., No. 1, Pp. 1-201, 2009. Journal of Legislation 34 J. Legis., No. 1, Pp. 1-98, 2008. Journal of Technology Law & Policy 14 J. Tech. L. & Pol’y, No. 1, June, 2009. Labor Lawyer 24 Lab. Law., No. 3, Winter/Spring, 2009. Michigan Journal of International Law 30 Mich. J. Int’l L., No. 3, Spring, 2009. New Criminal Law Review 12 New Crim. L. Rev., No. 2, Spring, 2009. Northern Kentucky Law Review 36 N. Ky. L. Rev., No. 4, Pp. 445-654, 2009. Ohio Northern University Law Review 35 Ohio N.U. L. Rev., No. 2, Pp. 445-886, 2009. Pace Law Review 29 Pace L. Rev., No. 3, Spring, 2009. Quinnipiac Health Law Journal 12 Quinnipiac Health L.J., No. 2, Pp. 209-332, 2008-2009. Real Property, Trust and Estate Law Journal 44 Real Prop. Tr. & Est. L.J., No. 1, Spring, 2009. Rutgers Race and the Law Review 10 Rutgers Race & L. Rev., No. 2, Pp. 441-629, 2009. San Diego Law Review 46 San Diego L. Rev., No. 2, Spring, 2009. Seton Hall Law Review 39 Seton Hall L. Rev., No. 3, Pp. 725-1102, 2009. Southern California Interdisciplinary Law Journal 18 S. Cal. Interdisc. L.J., No. 3, Spring, 2009. Stanford Environmental Law Journal 28 Stan. Envtl. L.J., No. 3, July, 2009. Tulsa Law Review 44 Tulsa L. Rev., No. 2, Winter, 2008. UMKC Law Review 77 UMKC L. Rev., No. 4, Summer, 2009. Washburn Law Journal 48 Washburn L.J., No. 3, Spring, 2009. Washington University Global Studies Law Review 8 Wash. U. Global Stud. L. Rev., No. 3, Pp.451-617, 2009. Washington University Journal of Law & Policy 29 Wash. U. J.L. & Pol’y, Pp. 1-401, 2009. Washington University Law Review 86 Wash. U. L. Rev., No. 6, Pp. 1273-1521, 2009. William Mitchell Law Review 35 Wm. Mitchell L. Rev., No. 4, Pp. 1235-1609, 2009. Yale Journal of International Law 34 Yale J. Int’l L., No. 2, Summer, 2009. Yale Journal on Regulation 26 Yale J. on Reg., No. 2, Summer, 2009.

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Current index to legal periodicals

Networks of workstations are poised to become the primary computing infrastructure for science and engineering. NOWs may dramatically improve virtual memory and file system performance; achieve cheap, highly available, and scalable file storage: and provide multiple CPUs for parallel computing. Hurdles that remain include efficient communication hardware and software, global coordination of multiple workstation operating systems, and enterprise-scale network file systems. Our 100-node NOW prototype aims to demonstrate practical solutions to these challenges. >

A case for NOW (Networks of Workstations)

Models and Methods in Social Network Analysis presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust’s Social Network Analysis: Methods and Applications, it is a collection of original articles by leading methodologists reviewing recent advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodeling, the analysis of diffusion through networks, the analysis of affiliation or “two-mode” networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphic techniques for exploring network data, and software for the analysis of social networks.

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Models and methods in social network analysis

We describe our work on improving the performance of collective communication operations in MPICH for clusters connected by switched networks. For each collective operation, we use multiple algorithms depending on the message size, with the goal of minimizing latency for short messages and minimizing bandwidth use for long messages. Although we have implemented new algorithms for all MPI Message Passing Interface collective operations, because of limited space we describe only the algorithms for allgather, broadcast, all-to-all, reduce-scatter, reduce, and allreduce. Performance results on a Myrinet-connected Linux cluster and an IBM SP indicate that, in all cases, the new algorithms significantly outperform the old algorithms used in MPICH on the Myrinet cluster, and, in many cases, they outperform the algorithms used in IBM's MPI on the SP. We also explore in further detail the optimization of two of the most commonly used collective operations, allreduce and reduce, particularly for long messages and nonpower-of-two numbers of processes. The optimized algorithms for these operations perform several times better than the native algorithms on a Myrinet cluster, IBM SP, and Cray T3E. Our results indicate that to achieve the best performance for a collective communication operation, one needs to use a number of different algorithms and select the right algorithm for a particular message size and number of processes.

/pdf/optimization-of-collective-communication-operations-in-mpich-2v96fa8yt4.pdf

Optimization of Collective Communication Operations in MPICH

enough to be generally useful and to keep the algorithm analysis tractable. Ideally, producing a better algorithm under the model should yield a better program in practice. The Parallel Random Access Machine (PRAM) [8] is the most popular model for representing and analyzing the complexity of parallel algorithms. A LogP A Practic

LogP: a practical model of parallel computation

We consider several natural broadcasting problems for the LogP model of distributed memory machines recently proposed by Culler et al. For each of these problems, we present algorithms that yield an optimal communication schedule. Our algorithms are absolutely best possible in that not even the constant factors can be improved upon. We also devise an (absolutely) optimal algorithm for summing a list of elements (using a non- commutative operation) using one of the optimal broadcast algorithms.

/pdf/optimal-broadcast-and-summation-in-the-logp-model-54kvwnsms0.pdf

Optimal broadcast and summation in the LogP model

Inaugural issue editorial

http://di2ag.thayer.dartmouth.edu/wiki/images/3/32/IJAR_Fusion_2011_(print_version).pdf

Eunice E. Santos

Papers

LogP: towards a realistic model of parallel computation

LogP: a practical model of parallel computation

Optimal broadcast and summation in the LogP model

Inaugural issue editorial

Fusing multiple Bayesian knowledge sources