class Speaker:1def __init__(self, name, employer=None, url=None, email=None, status=None, title=None, abstract=None):2self.name = name3self.employer = employer4self.email = email5self.url = url6self.title = title7self.abstract = abstract8self.status = status9if status != 'invited' and status != 'contributed':10raise ValueError, '%s: "%s"'%(name, status)1112def __repr__(self):13return self.name1415def last_name(self):16name = self.name17if ' and ' in self.name:18name = self.name.split(' and ')[0]19return ' '.join(name.split()[1:])2021def first_name(self):22return self.name.split()[0]2324def __cmp__(self, right):25return cmp(self.last_name(), right.last_name())2627def tag(self):28return self.name.replace(' ','')2930def html_full(self):31return """32<a name="%s">33<h2><font color="darkred"><b>%s</b></font>:34<font color="#333333"><i>%s</i></font><br></h2>35%s<br><br>36%s"""%(37self.tag(), self.last_name(), self.title, self.html_name(), self.html_abstract())3839def html_abstract(self):40s = self.abstract.replace('\n\n','<p>').replace('``','"').replace("''",'"')41if '*' in s:42i = s.find('*')43s = s.replace('*', '<li>')44s = s[:i] + '<ul>' + s[i:]45s += '</ul>'46return s4748def html_short(self):49return '%s<br><b><i>%s</i></b>'%(self.html_name(), self.html_title())5051def html_name(self):52if self.url:53url = self.url54else:55url = 'mailto:%s'%self.email56if self.employer:57emp = ' - %s'%self.employer58else:59emp = ''60return '<a href="%s">%s %s</a>'%(url, self.name, emp)6162def html_title(self):63return '<a href="#%s">%s</a>'%(self.tag(), self.title)646566############################################################################676869def wiki_full(self):70return """== %s: %s ==7172[%s %s %s]7374%s75"""%(self.last_name(), self.title, self.wiki_url(), self.name, self.wiki_employer(), self.wiki_abstract())7677def wiki_employer(self):78if self.employer == '':79return ''80else:81return '- %s'%self.employer8283def wiki_abstract(self):84ab = self.abstract.replace('``','"').replace("''",'"')85if '*' in ab:86return ab.strip()87return misc.word_wrap(ab).strip()8889def wiki_short(self):90return '%s<br>%s'%(self.wiki_name(), self.wiki_title())9192def wiki_url(self):93if self.url:94url = self.url95else:96url = 'mailto:%s'%self.email97return url9899100############################################################################101102def latex_full(self):103s = """104{\\large \\bf %s: {\\em\sf %s}}\\vspace{1ex}\\newline105{\em %s}\\vspace{1ex}\\newline106\url{%s}\\vspace{1ex}\\newline107{%s}108"""%(109self.last_name(), self.title, self.latex_name(), self.latex_url(), self.latex_abstract())110return s.strip()111112def latex_abstract(self):113s = self.abstract114if '*' in s:115i = s.find('*')116s = s.replace('*', '\\item')117s = s[:i] + '\\begin{itemize}' + s[i:]118s += '\\end{itemize}'119return s120121def latex_short(self):122return '%s - {\\em\\sf %s}'%(self.last_name(), self.title)123124def latex_name(self):125if self.employer:126emp = ' - %s'%self.employer127else:128emp = ''129return '%s %s'%(self.name, emp)130131def latex_url(self):132if self.url:133return self.url134return self.email135136137138speakers = [\139Speaker('David Bailey',140'Lawrence Berkeley Labs (LBL)',141'http://crd.lbl.gov/~dhbailey/',142'',143'invited',144'Experimental Mathematics and High-Performance Computing',145"""146Recent developments in ``experimental mathematics'' have underscored the value of high-performance computing in modern mathematical research. The most frequent computations that arise here are high-precision (typically several-hundred-digit accuracy) evaluations of integrals and series, together with integer relation detections using the ``PSLQ'' algorithm. Some recent highlights in this arena include: (2) the discovery of ``BBP'-type formulas for various mathematical constants, including pi and log(2); (3) the discovery of analytic evaluations for several classes of multivariate zeta sums; (4) the discovery of Apery-like formulas for the Riemann zeta function at integer arguments; and (5) the discovery of analytic evaluations and linear relations among certain classes of definite integrals that arise in mathematical physics. The talk will include a live demo of the ``experimental mathematician's toolkit''.147"""),148Speaker('Robert Bradshaw',149'University of Washington',150'',151'[email protected]',152'contributed',153'Loosely Dependent Parallel Processes',154"""155Many parallel computational algorithms involve dividing the problem into several smaller tasks and running each task in isolation in parallel. Often these tasks are the same procedure over a set of varying parameters. Inter-process communication might not be needed, but the results of one task may influence what subsequent tasks need to be performed. I will discuss the concept of job generators, or custom-written tasks that generate other tasks and process their feedback. I would discuss this specifically in the context of integer factorization.156"""),157158Speaker('Henry Cohn',159'Microsoft Research',160'http://research.microsoft.com/~cohn/',161'',162'invited',163'Parallel Computation Tools for Research: A Wishlist',164''),165166Speaker('Gene Cooperman',167'Northeastern University',168'http://www.ccs.neu.edu/home/gene/',169'',170'invited',171'Disk-Based Parallel Computing: A New Paradigm',172"""173One observes that 100 local commodity disks of an array have approximately the same streaming bandwidth as a single RAM subsystem. Hence, it is proposed to treat a cluster as if it were a single computer with tens of terabytes of data, and with RAM serving as cache for disk. This makes feasible the solution of truly large problems that are currently space-limited. We also briefly summarize other recent activities of our working group: lessons from supporting ParGAP and ParGCL; progress toward showing that 20 moves suffice to solve Rubik's cube; lessons about marshalling from support of ParGeant4 (parallelization of a million-line program at CERN); and experiences at the SCIEnce workshop (symbolic-computing.org), part of a 5-year, 3.2 million euro, European Union project. Our new distributed checkpointing package now provides a distributed analog of a SAVE-WORKSPACE command, for use in component-based symbolic software, such as SAGE."""),174175Speaker('Alan Edelman',176'MIT',177'http://www-math.mit.edu/~edelman/',178'',179'invited',180'Interactive Parallel Supercomputing: Today: MATLAB(r) and Python coming Cutting Edge: Symbolic Parallelism with Mathematica(r) and MAPLE(r)',181"""Star-P is a unique technology offered by Interactive Supercomputing after182nurturing at MIT. Star-P through its abstractions is solving the ease of use183problem that has plagued supercomputing. Some of the innovative features of184Star-P are the ability to program in MATLAB, hook in task parallel codes185written using a processor free abstraction, hook in existing parallel codes,186and obtain the performance that represents the HPC promise. All this is187through a client/server interface. Other clients such as Python or R could188be possible. The MATLAB, Python, or R becomes the "browser." Parallel189computing remains challenging, compared to serial coding but it is now that190much easier compared to solutions such as MPI. Users of MPI can plug in191their previously written codes and libraries and continue forward in Star-P.192193Numerical computing is challenging enough in a parallel environment,194symbolic computing will require even more research and more challenging195problems to be solved. In this talk we will demonstrate the possibilities196and the pitfalls.197"""),198199Speaker('Brian Granger',200'Tech X Corp.',201'http://txcorp.com',202'',203'invited',204'Interactive Parallel Computing using Python and IPython',205"""206Interactive computing environments, such as Matlab, IDL and207Mathematica are popular among researchers because their208interactive nature is well matched to the exploratory nature of209research. However, these systems have one critical weakness:210they are not designed to take advantage of parallel computing211hardware such as multi-core CPUs, clusters and supercomputers.212Thus, researchers usually turn to non-interactive compiled213languages, such as C/C++/Fortran when parallelism is needed.214215In this talk I will describe recent work on the IPython project216to implement a software architecture that allows parallel217applications to be developed, debugged, tested, executed and218monitored in a fully interactive manner using the Python219programming language. This system is fully functional and allows220many types of parallelism to be expressed, including message221passing (using MPI), task farming, shared memory, and custom user222defined approaches. I will describe the architecture, provide an223overview of its basic usage and then provide more sophisticated224examples of how it can be used in the development of new parallel225algorithms. Because IPython is one of the components of the SAGE226system, I will also discuss how IPython's parallel computing227capabilities can be used in that context.228"""),229230Speaker('Robert Harrison',231'Oak Ridge National Lab',232'http://www.csm.ornl.gov/ccsg/html/staff/harrison.html',233'',234'invited',235'Science at the petascale: tools in the tool box',236"""237Petascale computing will require coordinating the actions of 100,000+238processors, and directing the flow of data between up to six levels239of memory hierarchy and along channels that differ by over a factor of240100 in bandwidth. Amdahl's law requires that petascale applications241have less than 0.001% sequential or replicated work in order to242be at least 50% efficient. These are profound challenges for all but243the most regular or embarrassingly parallel applications, yet we also244demand that not just bigger and better, but fundamentally new science.245In this presentation I will discuss how we are attempting to confront246simultaneously the complexities of petascale computation while247increasing our scientific productivity. I hope that I can convince you248that our development of MADNESS (multiresolution adaptive numerical249scientific simulation) is not as crazy as it sounds.250251This work is funded by the U.S. Department of Energy, the division of252Basic Energy Science, Office of Science, and was performed in part253using resources of the National Center for Computational Sciences, both254under contract DE-AC05-00OR22725 with Oak Ridge National Laboratory.255"""),256257Speaker('Bill Hart',258'Warwick',259'http://www.maths.warwick.ac.uk/~masfaw/',260'',261'invited',262'Parallel Computation in Number Theory',263"""264This talk will have two sections. The first will265introduce a new library for number theory which is266under development, called FLINT. I will discuss the267various algorithms already available in FLINT, compare268them with similar implementations available elsewhere,269and speak about what the future holds for FLINT, with270the focus on parallel processing and integration into271Pari and the SAGE package.272273The second part of the talk will focus on low level274implementation details of parallel algorithms in275number theory. In particular I will discuss the design276decisions that we have made so far in the FLINT277library to facilitate multicore and multiprocessor278platforms.279280If time permits, there will be a live demonstration.281"""282),283284Speaker('Yozo Hida',285'UC Berkeley',286'http://www.cs.berkeley.edu/~yozo/',287'',288'invited',289'Moving Lapack and ScaLapack to Higher Precision without Too Much Work',290"""I will be discussing recent developments in Lapack and ScaLapack291libraries, along with some recent work on incorporating higher292precision into Lapack and ScaLapack."""),293294Speaker('Samee Khan',295'University of Texas, Arlington',296'',297'[email protected]',298'contributed',299'Game Theoretical Solutions for Data Replication in Distributed Computing Systems',300"""301Data replication is an essential technique employed to reduce the user302perceived access time in distributed computing systems. One can find numerous303algorithms that address the data replication problem (DRP) each contributing in304its own way. These range from the traditional mathematical optimization305techniques, such as, linear programming, dynamic programming, etc. to the306biologically inspired meta-heuristics. We aim to introduce game theory as a new307oracle to tackle the data replication problem. The beauty of the game theory308lies in its flexibility and distributed architecture, which is well-suited to309address the DRP. We will specifically use action theory (a special branch of310game theory) to identify techniques that will effectively and efficiently solve311the DRP. Game theory and its necessary properties are briefly introduced,312followed by a through and detailed mapping of the possible game theoretical313techniques and DRP. As an example, we derive a game theoretical algorithm for314the DRP, and propose several extensions of it. An elaborate experimental setup315is also detailed, where the derived algorithm is comprehensively evaluated316against three conventional techniques, branch and bound, greedy and genetic317algorithms.318"""),319320Speaker('Ilias Kotsireas',321'Laurier University, Canada',322'',323'[email protected]',324'contributed',325'Combinatorial Designs: constructions, algorithms and new results',326"""327We plan to describe recent progress in the search for combinatorial designs of328high order. This progress has been achieved via some algorithmic concepts, such329as the periodic autocorrelation function, the discrete Fourier transform and330the power spectral density criterion, in conjunction with heuristic331observations on plausible patterns for the locations of zero elements. The332discovery of such patterns is done using meta-programming and automatic code333generation (and perhaps very soon data mining algorithms) and reveals the334remarkable phenomenon of crystalization, which does not yet possess a335satisfactory explanation. The resulting algorithms are amenable to parallelism336and we have implemented them on supercomputers, typically as implicit parallel337algorithms.338"""),339340Speaker('Anton Leykin',341'IMA (Minessota)',342'',343'[email protected]',344'contributed',345'Parallel computation of Grobner bases in the Weyl algebra',346"""347The usual machinery of Grobner bases can be applied to non-commutative algebras348of the so-called solvable type. One of them, the Weyl algebra, plays the349central role in the computations with $D$-modules. The practical complexity of350the Grobner bases computation in the Weyl algebra is much higher than in the351(commutative) polynomial rings, therefore, calling naturally for parallel352computation. We have developed an algorithm to perform such computation353employing the master-slave paradigm. Our implementation, which has been carried354out in C++ using MPI, draws ideas from both Buchberger algorithm and355Faugere's $F_4$. It exhibits better speedups for the Weyl algebra in356comparison to polynomial problems of the similar size.357"""),358359Speaker('Jason Martin',360'James Madison University',361'http://www.math.jmu.edu/~martin/',362'',363'invited',364'MPMPLAPACK: The Massively Parallel Multi-Precision Linear Algebra Package',365"""366For several decades, researchers in the applied fields have had access367to powerful linear algebra packages designed to run on massively368parallel systems. Libraries such as ScaLAPACK and PLAPACK provide a369rich set of functions (usually based on BLAS) for performing linear370algebra over single or double precision real or complex data.371However, such libraries are of limited use to researchers in discrete372mathematics who often need to compute with multi-precision data types.373374This talk will cover a massively parallel multi-precision linear375algebra package that I am attempting to write. The goal of this C/MPI376library is to provide drop-in parallel functionality to existing377number theory and algebraic geometry programs (such as Pari, Sage, and378Macaulay2) while preserving enough flexibility to eventually become a379full multi-precision version of PLAPACK. I will describe some380architectural assumptions, design descisions, and benchmarks made so381far and actively solicit input from the audience (I'll buy coffee for382the person who suggests the best alternative to the current name).383"""),384385Speaker('Marc Moreno Maza',386'Western Ontario',387'http://www.csd.uwo.ca/~moreno/',388'',389'invited',390'Component-level Parallelization of Triangular Decompositions',391"""392We discuss the parallelization of algorithms for solving polynomial systems symbolically by way of triangular decompositions. We introduce a component-level parallelism for which the number of processors in use depends on the geometry of the solution set of the input system. Our long term goal is to achieve an efficient multi-level parallelism: coarse grained (component) level for tasks computing geometric objects in the solution sets, and medium/fine grained level for polynomial arithmetic such as GCD/resultant computation within each task.393394Component-level parallelism belongs to the class of dynamic irregular parallel applications, which leads us to address the following questions: How to discover and use geometrical information, at an early stage of the solving process, that would be favorable to component-level parallel execution and load balancing? How to use this level of parallel execution to effectively eliminate unnecessary computations? What implementation mechanisms are feasible?395396We report on the effectiveness of the approaches that we have applied, including ``modular methods'', ``solving by decreasing order of dimension'', ``task cost estimation for guided scheduling''. We have realized a preliminary implementation on a SMP using multiprocessed parallelism in Aldor and shared memory segments for data communication. Our experimentation shows promising speedups for some well-know problems. We expect that this speedup would add a multiple factor to the speedup of medium/fine grained level parallelization as parallel GCD/resultant computations.397"""),398399Speaker('Alfred Noel',400'UMass Boston / MIT',401'http://www.math.umb.edu/~anoel/',402'',403'invited',404'Structure and Representations of Real Reductive Lie Groups: A Computational Approach',405"""406I work with David Vogan (MIT) on the Atlas of Lie Groups and Representations. This is a project to make available information about representations of semi-simple Lie groups over real and p-adic fields. Of particular importance is the problem of the unitary dual: classifying all of the irreducible unitary representations of a given Lie group.407408I will present some of the main ideas behind the current and very preliminary version of the software. I will provide some examples also. Currently, we are developing sequential algorithms that are implemented in C++. However, because of time and space complexity we are slowly moving in the direction of parallel computation. For example, David Vogan is experimenting with multi-threads in the K-L polynomials computation module.409410This talk is in memory of Fokko du Cloux, the French mathematician who, until a few months ago, was the lead developer. He died this past November.411"""),412413Speaker('Clement Pernet',414'University of Waterloo',415'',416'[email protected]',417'invited',418'Parallelism perspectives for the LinBox library',419"""420LinBox is a generic library for efficient linear algebra with blackbox421or dense matrices over a finite field or Z. We first present a few422notions of the sequential implementations of selected problems, such423as the system resolution or multiple triangular system resolution, or424the chinese remaindering algorithm. Then we expose perspectives for425incorporating parallelism in LinBox, including multi-prime lifting for426system resolution over Q, or parallel chinese remaindering. This last427problem raises the difficult problem of combining early termination428and work-stealing techniques.429"""),430431Speaker('Yi Qiang',432'University of Washington',433'',434'http://www.yiqiang.net/',435'invited',436'Distributed Computing using SAGE',437"""438Distributed SAGE (DSAGE) is a distributed computing framework for439SAGE which allows users to easily parallelize computations and440interact with them in a fluid and natural way. This talk will be441focused on the design and implementation of the distributed computing442framework in SAGE. I will describe the application of the443distributed computing framework to several problems, including the444problem of integer factorization and distributed ray tracing.445Demonstrations of using Distributed SAGE to tackle both problems will446be given plus information on how to parallelize your own problems. I447will also talk about design issues and considerations that have been448resolved or are yet unresolved in implementing Distributed SAGE.449"""),450451Speaker('Jean-Louis Roch',452'ID-IMAG (France)',453'http://www-id.imag.fr/Laboratoire/Membres/Roch_Jean-Louis/perso.html',454'[email protected]',455'invited',456'Processor oblivious parallel algorithms with provable performances: applications',457"""458Based on a work-stealing schedule, the on-line coupling of two algorithms459(one sequential; the other one recursive parallel and fine grain) enables460the design of programs that scale with provable performances on various461parallel architectures, from multi-core machines to heterogeneous grids,462including processors with changing speeds. After presenting a generic scheme463and framework, on top of the middleware KAAPI/Athapascan that efficiently464supports work-stealing, we present practical applications such as: prefix465computation, real time 3D-reconstruction, Chinese remainder modular lifting466with early termination, data compression.467"""),468469Speaker('Vladimir Tonchev',470'Michigan Tech',471'',472'[email protected]',473'contributed',474'Combinatorial designs and code synchronization',475"""476Difference systems of sets are combinatorial designs that arise in connection477with code synchronization. Algebraic constructions based on cyclic difference478sets and finite geometry and algorithms for finding optimal difference systems479of sets are discussed.480"""),481482Speaker('Jan Verschelde',483'UIC',484'http://www.math.uic.edu/~jan/',485'[email protected]',486'invited',487'Parallel Homotopy Algorithms to Solve Polynomial Systems',488"""489A homotopy is a family of polynomial systems which defines a deformation490from a system with known solutions to a system whose solutions are needed.491Via dynamic load balancing we may distribute the solution paths so that a492close to optimal speed up is achieved. Polynomial systems -- such as the4939-point problem in mechanical design leading to 286,720 paths -- whose494solving required real supercomputers twenty years ago can now be handled495by modest personal cluster computers, and soon by multicore multiprocessor496workstations. Larger polynomial systems however may lead to more497numerical difficulties which may skew the timing results, so that498attention must be given to ``quality up'' as well. Modern homotopy methods499consist of sequences of different families of polynomial systems so that500not only the solution paths but also parametric polynomial systems must be501exchanged frequently.502"""),503504Speaker('Thomas Wolf and Winfried Neun',505'',506'',507'[email protected] [email protected]',508'contributed',509'Parallel sparsening and simplification of systems of equations',510"""511In a Groebner Basis computation the guiding principle for pairing and512`reducing' equations is a total ordering of monomials or of derivatives for513differential Groebner Bases. If reduction based on an ordering is replaced by514reduction to minimize the number of terms of an equation through another515equation then on the downside the resulting (shorter) system does depend on the516order of pairing of equations for shortening but on the upside there are number517of advantages that makes this procedure a perfect addition/companion to the518Groebner Basis computation. Such features are:519520* In contrast to Groebner Basis computations, this algorithm is safe in the sense that it does not need any significant amount of memory, even not temporarily.521* It is self-enforcing, i.e. the shorter equations become, the more useful for shortening other equations they potentially get.522* Equations in a sparse system are less coupled and a cost effective elimination strategy (ordering) is much easier to spot (for humans and computers) than for a dense system.523* Statistical tests show that the probability of random polynomials to factorize increases drastically the fewer terms a polynomial has.524* By experience the shortening of partial differential equations increases their chance to become ordinary differential equations which are usually easier to solve explicitly.525* The likelihood of shortenings to be possible is especially high for large overdetermined systems. This is because the number of pairings goes quadratically with the number of equations but for overdetermined systems, more equations does not automatically mean more unknowns to occur which potentially obstruct shortening by introducing terms that can not cancel.526* The algorithm offers a fine grain parallelization in the computation to shorten one equation with another one and a coarse grain parallelization in that any pair of two equations of a larger system can be processed in parallel. In the talk we will present the algorithm, show examples supporting the above statements and give a short demo.527"""),528529Speaker('Kathy Yelick',530'UC Berkeley',531'http://www.cs.berkeley.edu/~yelick/',532'[email protected]',533'invited',534'Programming Models for Parallel Computing',535"""536The introduction of multicore processors into mainstream computing is537creating a revolution in software development. While Moore's538Law continues to hold, most of the increases in transistor density will be539used for explicit, software-visible parallelism, rather than increasing540clock rate. The major open question is how these machines will be541programmed.542In this talk I will give an overview of some of the hardware trends, and543describe programming techniques using Partitioned Global Address Space544(PGAS)545languages. PGAS languages have emerged as a viable alternative to message546passing programming models for large-scale parallel machines and clusters.547They also offer an alternative to shared memory programming models (such as548threads and OpenMP) and the possibility of a single programming model that549will work well across a wide range of shared and distributed memory550platforms.551PGAS languages provide a shared memory abstraction with support for locality552through the user of distributed data types. The three most mature PGAS553languages (UPC, CAF and Titanium) offer a statically partitioned global554address space with a static SPMD control model, while languages emerging555from the DARPA HPCS program are more dynamic. I will describe these556languages as well as our experience using them in both numeric and557symbolic applications.""")558559]560561562def find(name):563name = name.lower()564ans = None565for v in speakers:566if name in v.name.lower():567if not ans is None:568raise RuntimeError, "ambiguous search for '%s'"%name569ans = v570if ans is None:571raise RuntimeError, "Speaker '%s' not found"%name572return ans573574575576##############577578def html_talks(file='a'):579a = open('%s.html'%file,'w')580a.write(r"""581<html>582<head>583<title>584Interactive Parallel Computation in Support of Research585in Algebra, Geometry and Number Theory: Abstracts586</title>587588<style>589div.box {590border:1px solid #004400;591padding:10px;592margin-left:30px;593margin-right:30px;594}595table {596border-bottom:1px solid lightgray;597border-top:1px solid lightgray;598}599600a:active { color: #ff0000; }601a:hover { background-color: #aaffaa}602a { text-decoration: none; }603604div.space {605padding:50px;606margin-top:15px;607background-color:#eeeeee;608}609610611h2.top {612text-align:center;613}614615div.bar {616padding:1px;617background-color:#999999;618border-top: 1px solid black;619border-bottom: 1px solid black;620margin:2px;621}622623</style>624625<body>626<h1 align=center>Titles and Abstracts</h1>627628These are the abstracts for all the talks scheduled for <a href="index.html">MSRI Parallel Computation629the workshop</a>, listed in630alphabetical order. For times, see the <a href="schedule.html">the schedule</a> itself.631<br>632<hr>633""")634for s in speakers:635a.write(s.html_full())636a.write('<br><br><hr>')637a.write('</body></html>')638a.close()639640def wiki_talks():641a = open('%s.txt'%file,'w')642a.write(r"""643= Titles and Abstracts =644These are the abstracts for all the talks scheduled for [:msri07: the workshop], listed in645alphabetical order. For times, see the [:msri07/schedule: schedule] itself.646647[[TableOfContents]]648649""")650651for s in speakers:652a.write(s.wiki_full())653a.write('\n\n')654a.close()655656def pdf_abstracts(file='a', verbose=False):657a = open('%s.tex'%file,'w')658a.write(r"""659\documentclass{article}660\usepackage{url}661\usepackage{fullpage}662\title{Titles and Abstracts:\vspace{4ex}\mbox{}\\663\Large Interactive Parallel Computation in Support of Research in\\Algebra, Geometry664and Number Theory\vspace{4ex}\mbox{}\\665\large A Workshop at MSRI Jan 29-Feb 2 organized by\\Burhanuddin, Demmel, Goins, Kaltofen, Perez, Stein, Verrill, and Weening}666\begin{document}667\maketitle668\par\noindent669""")670for s in speakers:671a.write(s.latex_full())672a.write('\\mbox{}\\vspace{6ex}\n\n\n\\par\\noindent')673a.write('\\end{document}')674a.close()675if not verbose:676z = '1>/dev/null'677else:678z = ''679os.system('pdflatex %s.tex < /dev/null %s'%(file, z))680681########################################################################################682683class Day:684def __init__(self, name, theme='', discussion='', invited=[], contributed=[]):685self.name = name686self.theme = theme687self.discussion = discussion688self.invited = invited689self.contributed = contributed690691def __repr__(self):692return self.name693694def html_contrib(self, n):695c = self.contributed696if n < len(c):697if 'Cohn' in c[n].name:698return c[n].html_short() + ' (part %s)'%n699else:700return '(Optional) ' + c[n].html_short()701else:702return 'Break'703704def latex_contrib(self, n):705c = self.contributed706if n < len(c):707if 'Cohn' in c[n].name:708return c[n].latex_short() + ' (part %s)'%n709else:710return '(Optional) '+ c[n].latex_short()711else:712return 'Break'713714def html(self):715s = """716<a name="%s">717<table class="ws" width=90%% align=center>718<tr><td class='time' width=10%%></td><td class="day" width=80%%><font size=+3><b>%s</b><br><font size=+2><b>Theme: %s</b></font></td></tr>719<tr><td class='time'>9:00-10:00</td><td>%s</td></tr>720<tr><td class='time'>10:00-10:30</td><td class="break">Tea Break</td></tr>721<tr><td class='time'>10:30-11:30</td><td>%s</td></tr>722<tr><td class='time'>11:30-12:30</td><td>%s</td></tr>723<tr><td class='time'>12:30-1:30</td><td class="break">Lunch</td></tr>724<tr><td class='time'>1:30-2:00</td><td>%s</td></tr>725<tr><td class='time'>2:00-2:30</td><td>%s</td></tr>726<tr><td class='time'>2:30-3:30</td><td class="discuss"><b>Discussion:</b> %s</td></tr>727"""%(728self.name.split()[0].strip(',').lower(),729self.name, self.theme,730self.invited[0].html_short(),731self.invited[1].html_short(),732self.invited[2].html_short(),733self.html_contrib(0),734self.html_contrib(1),735self.discussion)736if self.name != 'Friday, Feb 2':737s += """738<tr><td class='time'>3:30-4:00</td><td class="break">Tea Break</td></tr>739<tr><td class='time'>4:00-5:30</td><td>Working Sessions</td></tr>740<tr><td class='time'>6:00-8:00</td><td class="break">Dinner</td></tr>741<tr><td class='time'>8:00-10:00</td><td class="break">Coffee Shops...</td></tr>742"""743s += """744</table>745"""746return s747748def latex(self):749s = """750{\\Large \\bf %s}\\vspace{1ex}751752\\begin{tabular}{|l|l|}\\hline753& \\begin{minipage}{0.7\\textwidth}Theme: %s\\end{minipage} \\\\ \\hline7549:00--10:00 & \\begin{minipage}{0.7\\textwidth}%s\\end{minipage} \\\\75510:00--10:30 & \\begin{minipage}{0.7\\textwidth}Tea Break\\end{minipage} \\\\75610:30--11:30 & \\begin{minipage}{0.7\\textwidth}%s\\end{minipage} \\\\75711:30--12:30 & \\begin{minipage}{0.7\\textwidth}%s\\end{minipage} \\\\ \\hline75812:30--1:30 & \\begin{minipage}{0.7\\textwidth}Lunch\\end{minipage} \\\\7591:30--2:00 & \\begin{minipage}{0.7\\textwidth}%s\\end{minipage} \\\\7602:00--2:30 & \\begin{minipage}{0.7\\textwidth}%s\\end{minipage} \\\\ \\hline7612:30--3:30 & \\begin{minipage}{0.7\\textwidth}Discussion: %s\\end{minipage} \\\\762"""%(763self.name, self.theme,764self.invited[0].latex_short(),765self.invited[1].latex_short(),766self.invited[2].latex_short(),767self.latex_contrib(0),768self.latex_contrib(1),769self.discussion770)771if self.name != 'Friday, Feb 2':772s += """7733:30--4:00 & \\begin{minipage}{0.7\\textwidth}Tea Break\\end{minipage} \\\\7744:00--5:30 & \\begin{minipage}{0.7\\textwidth}Working Sessions\\end{minipage} \\\\7756:00--8:00 & \\begin{minipage}{0.7\\textwidth}Dinner\\end{minipage} \\\\7768:00--10:00 & \\begin{minipage}{0.7\\textwidth}Coffee Shops...\\end{minipage} \\\\ \\hline777"""778s += '\\end{tabular}'779return s780781days = [\782Day('Monday, Jan 29',783'What do we want and what can we expect from applying parallel techniques to pure mathematics research tools?',784"""Parallel methods for mathematics software for doing algebra, geometry785and number theory -- What can we expect? What are the right problems to attack first786and get the most for our work?787""",788[find('pernet'),789find('granger'),790find('roch')],791[find('cohn'), find('cohn')]),792793Day('Tuesday, Jan 30',794'Algebra',795'Parallel methods for algebra (commutative algebra, linear algebra, group theory).',796[find('yelick'), find('hida'), find('noel')],797[find('Leykin'), find('tonchev')]798),799800Day('Wednesday, Jan 31',801'Number Theory',802"Parallel methods for number theory.",803[find('martin'), find('hart'), find('qiang')],804[find('bradshaw'), find('kotsireas')]805),806807Day('Thursday, Feb 1',808'Geometry',809'Parallel methods for geometry',810[find('verschelde'), find('moreno'), find('bailey')],811[find('wolf'), find('neun')]),812813Day('Friday, Feb 2',814'Large-Scale Parallel Computation',815'Wrap-up session',816[find('harrison'), find('cooperman'), find('edelman')],817[find('khan')])818]819820821def html_sched(file='a'):822a = open('%s.html'%file,'w')823a.write(r"""824<html>825<head>826<title>827Interactive Parallel Computation in Support of Research828in Algebra, Geometry and Number Theory: Schedule829</title>830831<style>832div.box {833border:1px solid #004400;834padding:10px;835margin-left:30px;836margin-right:30px;837}838839table.ws {840border-width: 1px 1px 1px 1px;841border-spacing: 0px;842border-style: solid solid solid solid ;843border-color: gray gray gray gray;844border-collapse: separate;845background-color: #333355;846}847table.ws th {848border-width: 1px 1px 1px 1px;849padding: 1px 1px 1px 1px;850border-style: solid solid solid solid ;851border-color: gray gray gray gray;852background-color: white;853-moz-border-radius: 0px 0px 0px 0px;854padding:10px;855}856table.ws td {857border-width: 1px 1px 1px 1px;858padding: 1px 1px 1px 1px;859border-style: solid solid solid solid ;860border-color: gray gray gray gray;861background-color: white;862-moz-border-radius: 0px 0px 0px 0px;863padding:10px;864}865table.ws td.break {866border-width: 1px 1px 1px 1px;867padding: 1px 1px 1px 1px;868border-style: solid solid solid solid ;869border-color: gray gray gray gray;870background-color: #80ff80;871-moz-border-radius: 0px 0px 0px 0px;872padding:10px;873}874875table.ws td.day {876border-width: 1px 1px 1px 1px;877padding: 1px 1px 1px 1px;878border-style: solid solid solid solid ;879border-color: gray gray gray gray;880background-color: #e0e0ff;881-moz-border-radius: 0px 0px 0px 0px;882padding:10px;883}884885table.ws td.discuss {886border-width: 1px 1px 1px 1px;887padding: 1px 1px 1px 1px;888border-style: solid solid solid solid ;889border-color: gray gray gray gray;890background-color: #e0ffe0;891-moz-border-radius: 0px 0px 0px 0px;892padding:10px;893}894895table.ws td.time {896border-width: 1px 1px 1px 1px;897padding: 1px 1px 1px 1px;898border-style: solid solid solid solid ;899border-color: gray gray gray gray;900background-color: #ffffe0;901-moz-border-radius: 0px 0px 0px 0px;902padding:10px;903}904905a:active { color: #ff0000; }906a:hover { background-color: #aaffaa}907a { text-decoration: none; }908909div.space {910padding:50px;911margin-top:15px;912background-color:#eeeeee;913}914915916h2.top {917text-align:center;918}919920div.bar {921padding:1px;922background-color:#999999;923border-top: 1px solid black;924border-bottom: 1px solid black;925margin:2px;926}927928</style>929930<body>931<h1 align=center>Schedule and <a href="#abstracts">Abstracts</a></h1>932<h3>933This is the schedule of talks and list of abstracts for this <a href="index.html">MSRI Parallel Computation934workshop</a>. There is also <a href="schedule.pdf">a PDF schedule</a> and935<a href="abstracts.pdf">a PDF list of abstracts</a>.936</h3>937<h3 align=center>938<a href="#monday">Monday</a> | <a href="#tuesday">Tuesday</a> |939<a href="#wednesday">Wednesday</a> |940<a href="#thursday">Thursday</a> |941<a href="#friday">Friday</a>942</h3>943<div class='bar'></div>944""")945946for d in days:947a.write(d.html())948a.write("<br><div class='bar'></div><br>")949950a.write('<a name="abstracts"><h1>Abstracts</h1>')951for s in speakers:952a.write(s.html_full())953a.write('<br><br><hr>')954955a.write('</body></html>')956957a.close()958959960961def pdf_sched(file='a', verbose=False):962a = open('%s.tex'%file,'w')963a.write(r"""964\documentclass{article}965\usepackage{url}966\usepackage{fullpage}967\title{Schedule: Jan 29 -- Feb 2, 2007\vspace{3ex}\mbox{}\\968\Large MSRI: Interactive Parallel Computation in Support of Research in\\Algebra, Geometry969and Number Theory}970\date{}971\begin{document}972\maketitle973\vspace{-3ex}974975\mbox{}\par\noindent976\begin{center}977""".strip())978for d in days:979a.write(d.latex())980a.write('\\mbox{}\\vspace{4ex}\n\n\n\\par\\noindent')981a.write('\\end{center}')982a.write('\\end{document}')983a.close()984if not verbose:985z = '1>/dev/null'986else:987z = ''988os.system('pdflatex %s.tex < /dev/null %s'%(file, z))989990991def gen():992dir='/home/was/conferences/2007-msri-parallel/'993pdf_sched(file='schedule', verbose=True)994pdf_abstracts(file='abstracts', verbose=True)995html_sched(file='schedule')996os.system('cp -v *.pdf *.html %s/'%dir)997998