Beowulf Cluster Computing with Linux by T. Sterling; Beowulf Cluster Computing withWindows by T. SterlingReview by: Sorin MitranSIAM Review, Vol. 44, No. 4 (Dec., 2002), pp. 734-736Published by: Society for Industrial and Applied MathematicsStable URL: http://www.jstor.org/stable/4148337 .

Accessed: 22/06/2014 22:47

Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at .http://www.jstor.org/page/info/about/policies/terms.jsp

.JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range ofcontent in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new formsof scholarship. For more information about JSTOR, please contact support@jstor.org.

.

Society for Industrial and Applied Mathematics is collaborating with JSTOR to digitize, preserve and extendaccess to SIAM Review.

http://www.jstor.org

This content downloaded from 62.122.73.250 on Sun, 22 Jun 2014 22:47:54 PMAll use subject to JSTOR Terms and Conditions

734 BOOK REVIEWS

wonderful, but no matter what the authors' original intent, researchers will want to use it-and will be frustrated by the lack of a bibliography.

The seminal book in the interior-point revolution was Nesterov and Nemirovski's monograph [1]. Learning modern convex optimization via that crucial but challeng- ing text is a daunting task. A recent, slim, and elegant introduction is Renegar's [2]. The current book also aims at a much gen- tler introduction, essentially by reversing the order of topics. Rather than starting with a general analysis of the tractability of Newton's method in convex optimization and the consequent fundamentals of barrier functions, and then moving on to specifics and applications, the current book begins with applications and specific models and ends with the general theory of tractability and the interior-point paradigm. The au- thors also favor this kind of inverse develop- ment within each lecture; for example, they move from the problem of uniform approx- imation, to linear programming duality, to theorems of the alternative, to the homo- geneous Farkas lemmna, to Helly's theorem, and finally to Radon's theorem, reversing a more typical formal development.

Occasionally, the order of topics becomes slightly problematic. A large portion of the book (Lectures 3 and 4) is devoted to a powerful calculus for conic quadratic and semidefinite representable sets-- -sets we can describe with the basic cones and linear constraints. The reader must take the com- putational significance of this development on trust, because ideas and descriptions of efficient algorithms only appear later. This ordering must also gloss over the fact that representability itself must be efficient: describing a set by too many inequalities is unhelpful. Given the strikingly parallel developments for the conic quadratic and semidefinite calculus, some discussion of the gap between the two notions of rep- resentability would have been natural.

But these are quibbles. This book is a delightful source of elegant and powerful ideas on modern optimization, packed with mathematical gems and far-reaching appli- cations. Like the best of teachers, the au- thors remain ever-hopeful for their flagging students: at one point, after a rapid sketch

of the machinery of the ellipsoid algorithm they estimate "implementation of the out- lined scheme takes from 10 to 30 minutes, depending on how many miscalculations are made." An optimistic complexity estimate, perhaps, but also a typically irresistible in- vitation from generous hosts.

REFERENCES

[1] Y. NESTEROV AND A. NEMIROVSKII, Interior-Point Polynomial Algorithms in Convex Programming, SIAM Stud. Appl. Math. 13, SIAM, Philadelphia, 1994.

[2] J. RENEGAR, A Mathematical View of Interior-Point Methods in Convex Op- timization, SIAM, Philadelphia, 2001.

ADRIAN LEWIS Simon Fraser University

Beowulf Cluster Computing with Linux. Edited by Ti Sterling. MIT Press, Cambridge, MA, 2001. $39.95. xxxiii+496 pp., softcover. ISBN 0-262-69274-0.

Beowulf Cluster Computing with Win- dows. Edited by TI Sterling. MIT Press, Cam- bridge, MA, 2001. $39.95. xxxiii+445 pp., soft- cover. ISBN 0-262-69275-9.

These two companion volumes are an evo- lution of How to Build a Beowulf [4] and chronicle the remarkable developments in cluster computing achieved in the past three years. Books on the subject are bound to lag behind developments in the real world, yet it is convenient to periodically gather knowledge about the state-of-the-art in a single volume or two. The two books pro- vide an introduction to cluster computing that would be time-consuming to collect from disparate sources. Most of the mate- rial is shared among the two books. Fea- tures specific to either Linux or Windows account for around a quarter of each book.

That the Beowulf idea should have pro- gressed from humble origins to a signifi- cant presence in the list of fastest com- puters in operation [1] is a testimony to the economies of scale driving mainstream commercial computing. Where specialized, proprietary architectures once ruled, open

This content downloaded from 62.122.73.250 on Sun, 22 Jun 2014 22:47:54 PMAll use subject to JSTOR Terms and Conditions

BOOK REVIEWS 735

source ideas now provide a competitive so- lution. The very fastest computers will al- ways be the result of significant expendi- tures by government laboratories, but it is heartening to see do-it-yourself opera- tions making an appearance in the Top 500 list [2]. The democratization of access to high-performance computing is bound to lead to significant algorithmic developments in the future. These books provide an in- sider's view to this development. Chapters are written by different authors who have all made significant contributions to dis- tributed computing.

The first two parts of both books, I. Enabling Technologies and II. Parallel Pro- gramming, are essentially updates of the corresponding How to Build a Beowulf ma- terial. One first learns about current hard- ware capabilities, overall features of the op- erating system, networks, and cluster setup. The material serves as a useful compendium from which to extract a bit more informa- tion on the myriad acronyms that popu- late the computer technology marketplace, if one is so inclined. Yet it is doubtful that finding out that SRAM is implemented as "multitransistor flipflop circuits" is suf- ficiently illuminating. For the electronics engineer it is probably obvious, while for the parallel application programmer it is superfluous. Such enumerations of current technologies only superficially aid someone contemplating construction of a cluster. It would be much more useful to present design case studies on how a desired computational capacity may be achieved. Even if tech- nologies age, as they most certainly do, the rationale of making specific choices will re- main valid. A few carefully chosen problems could serve to illuminate tradeoffs and bot- tlenecks much more readily than the simple listing of transient hardware solutions.

Similar remarks pertain to the presenta- tion of the operating system, network hard- ware, and software. The books provide con- cise overviews of the state-of-the-art, but one should have some initial knowledge of each subject to appreciate the information provided. Someone familiar with comput- ers could follow the prescriptions set forth on how to set up and manage a cluster, but that initial familiarity should be gained elsewhere.

The material on parallel programming is a reasonable balance between conciseness and information. Someone familiar with the C programming language can quickly ascer- tain the salient points of the message pass- ing approach to parallel programming from the two chapters presenting MPI (Message Passing Interface). The chapters on PVM (Parallel Virtual Machine) are in the same vein, but also include a Fortran example. Some advanced material on fault-tolerance and parallel input/output is also included. For a more in-depth presentation one can turn to the books on MPI and PVM in the series in which these two books are pub- lished.

The third part, Managing Clusters, is a new addition to the material in How to Build a Beowulf. After a quick presentation of what cluster management entails, there follow chapters on a number of management solutions. The Condor system developed at the University of Wisconsin goes beyond job scheduling on a single cluster to a full imple- mentation of dedicated and opportunistic scheduling to use idle computer cycles on all networked machines. With ever-faster Internet connection speeds, systems such as Condor hold the promise of coherently harnessing the power of thousands of under- utilized computers. The chapter describing Condor provides a fairly detailed overview, sufficient for someone to decide whether to try out the system and also to guide first steps. Subsequent chapters present two other job schedule systems named Maui and PBS (Portable Batch System). The Windows book also describes Cluster CoN- Troller suitable for that particular operating system (one wonders how the product name changes with successive Windows incarna- tions). Besides job management there is also a practical need for cluster file manage- ment. A chapter on PVFS (Parallel Virtual File System) presents one such system.

Finally, each of the two books has a pre- sentation of a particular installation. The Linux book describes the Chiba City clus- ter built at Argonne National Laboratory; the Windows book recounts the experience of the Cornell Theory Center with clusters using Microsoft operating systems. These real-world accounts of managing a large cluster are quite useful to other institutions

This content downloaded from 62.122.73.250 on Sun, 22 Jun 2014 22:47:54 PMAll use subject to JSTOR Terms and Conditions

736 BOOK REVIEWS

contemplating such a facility. Both books close with thoughts on future hardware and software developments.

Overall the books are a nice addition to a library that individuals interested in learn- ing more about Beowulfs can peruse and from which they can rapidly get some in- formation. One would hope for a synthesis of distributed processing, but perhaps it is too early and more field developments are needed.

The books come with a forward by Gor- don Bell, who now works at Microsoft Re- search. He provides a unique view of the increase in computational capacity brought about by multiprocessing. The success of the "Beowulf way" of open source develop- ment and the use of commodity hardware is contrasted against the many high-cost so- lutions preceding it. Bell advocates the use of Windows Beowulf as a standard so as to avoid fragmentation of Linux Beowulf into multiple dialects. This raises the question of whether such a freeze of the free-for-all atmosphere of current contributions in fa- vor of controlled development is desirable. That is a choice best left to the wisdom of each multiprocessing practitioner. The ballots are out but we have to wait a few more years for the election results.

REFERENCES

[1] http://www.top500.org. [2] http://kepler.sfb382-zdv.uni-tuebingen.de/

kepler/index.shtrnl. [3] http://clusters.top500.org. [4] T. STERLING, J. SALMON, D. .J. BECKER,

AND D. F. SAVARESE, How to Build a Beowulf, MIT Press, Cambridge, MA, 1999 (reviewed in SIAM Rev., 42 (2000), pp. 341-342).

SORIN MITRAN University of Washington

Applied Interval Analysis. By L.Jaulin, M. Kief- fer, 0. Didrit, and E. Walter. Springer-Verlag, New York, 2001. $79.95. xvi+379 pp., hardcover. ISBN 1-85233-219-0.

This book, with the subtitle With Exam- ples in Parameter and State Estimation,

Robust Control and Robotics," presents in- terval analysis in the context of its appli- cations. While there are a number of good recent books [1, 9, 11, 12, 20] featuring in- tervals in the context of numerical compu- tations and optimization, they all remain strictly within the limits of mathematics; the only exception is a book by Kolev [12] on interval methods in circuit analysis. Thus the new book is a welcome addition, helping bridge the gaps among theory, tools, and applications.

Interval analysis was originally invented by Moore [16, 17] for controlling round- ing errors in numerical computations; it serves in this role today by providing math- ematical rigor in computer-assisted proofs in mathematics and mathematical physics. The most conspicuous of these is Hales's proof [8] of Kepler's over-300-year-old con- jecture that the face-centered cubic lattice is the densest packing of equal spheres in 3-space. Tucker's recent proof [22, 23] that the Lorenz attractor exists also needs inter- val analysis in a nontrivial way. For other computer-assisted proofs see the recent re- views by Frommner [6] and Fefferiann and Seco [5].

A second, initially unexpected, use of interval analysis is based on its ability to provide tools for attacking global questions about nonlinear problems, by allowing a rig- orous control of the deviation from nonlin- earity. This turns interval techniques into powerful and in some cases indispensable tools in those applications outside mathe- matics which require the solution of global problems.

The book under review is virtually silent about applications to computer-assisted proofs. It is in the second role-solving global nonlinear problems-that interval analysis is promoted in the book under re- view, and numerous examples and illustra- tions show its use in engineering applica- tions.

The book is organized into four parts. Part I gives a short motivation for the book. Part II introduces in chapters 2-4 operations on intervals, interval vectors (= boxes) and interval matrices, basic proper- ties of various range enclosure forms, two basic workhorses, the branch-and-bound principle ("subpavings") and the contrac-

This content downloaded from 62.122.73.250 on Sun, 22 Jun 2014 22:47:54 PMAll use subject to JSTOR Terms and Conditions