Special Issue Preface pubs.acs.org/JPCB
Personal Observations: William C. Swope undergraduate research project with Roy Gordon included the task of writing a FORTRAN program to run on the department computer, which was essentially a minicomputer in an air conditioned glass room on display in the lobby of the chemistry building. I usually got the midnight to 3 am shift, but it gave me my first real taste of programming, and I finally got to use what I learned from the IBM programming books I stumbled upon in high school. I enjoyed a theoretical classical mechanics course in the physics department where molecular dynamics was given about 10 min of discussion, but at the time I could not believe anyone could actually learn anything from these kinds of simulations. The only undergraduate computer course offered at the time was in the applied math department, and it included Boolean algebra, IBM mainframe assembly language, and a laboratory component that involved building flip flop circuits from diodes. I went to the chemistry department at U.C. Berkeley for graduate school in 1975. I really liked the idea of studying chemistry from a theoretical perspective, but since I also enjoyed electronics and building instrumentation, I felt I could be at home in a world of light sources and vacuum pumps, so I interviewed with several physical chemistry experimental groups. However, having substituted physics laboratories for chemistry laboratories in college, I may have known how to make a hologram but realized I did not really have hands on knowledge of experimental physical chemistry, so I chose to join Fritz Schaefer’s quantum chemistry theory group. Nonetheless, the department selected me to be a teaching assistant for the undergraduate experimental physical chemistry course! Since I did not really know what most of the equipment did or how it worked, I would offer extra credit to the students if they could explain in detail the theory behind and the complete workings of the equipment they were using. I asked a lot of questions, but the undergrads at Berkeley were pretty bright, so these oral exams actually worked very well for me until one of the experiments broke down, which involved a failed, and ancient, homemade gas chromatograph. When I reported this to the professor, Gabor Somorjai, thinking he would give me a phone number to call to have it fixed, he told me that, as a Berkeley graduate student, I was expected to fix it myself. This occupied me for the next 2 weeks, but I eventually fixed it. I was also a teaching assistant for Robert Harris’ graduate quantum mechanics class. This class was offered out of phase with the regular quantum class that was taught at the time by Bill Miller, so the class was much smaller. Those of you who know Bob will not be surprised to learn that the assignments were truly imaginative, insightful, and unlike anything anyone had ever seen. The six students and I spent many days working these problem sets, and after a fair amount of work, I could usually solve them. However, on one week’s assignment, there was one problem that none of us could crack, and I sheepishly went to Bob’s office for some guidance. He had a big black
I grew up in Warren, Ohio, in what was then a steel mill town. For many years as a child, I worked on cars with my stepfather. I started out handing him wrenches as he worked under them, a good way to learn fractions. We not only kept the family cars in working order but fixed up several junk cars and sold them. This work included everything from taking apart and repairing engines and transmissions to electrical troubleshooting, body work, repainting, and upholstery repair. My stepfather also was an expert carpenter, and I worked with him on many projects including adding bathrooms and other forms of household remodeling. He was entirely self-taught, but I learned from his example that you could accomplish almost anything if you put your mind to it. At my mother’s insistence, and for many years, my brother, sister, and I cycled through churches of several different faiths. This encouraged us to respect the beliefs of others, but we could also be a real pain asking questions during Sunday school. We eventually settled on Sunday meetings at our local YWCA with a Unitarian group that organized a series of lectures each week from invited speakers. One set I remember was on the decisions that were made over time about what content was accepted and rejected for inclusion in the New Testament. I found these studies of religion to be extremely interesting, not as a source of personal faith but rather as an exercise in understanding what and why people believe what they do. Although these lessons were learned from the study of religions, I have found that dogmatism exists in science as well. In high school, I found in the trash a set of manuals and workbooks for a programmed learning course in FORTRAN IV from IBM. This was probably a remnant from a night school course one of the teachers was taking. I read through the whole set and worked all the exercises, without having access to a computer at the time. I wondered then if I would ever use that knowledge. The steel industry in my home town at the time provided a tax base for a great local school system, and that educational foundation helped me gain acceptance to Harvard University in 1971. I had a minor crisis as a freshman, not being able to decide upon a field of concentration. I actually made an appointment with a counselor at the University Health Services to see if there was a test or something I could take that would tell me what to do. I could not decide between theology, art or music history, chemistry, or physics. The counselor was rather annoyed with me but finally asked what field I would regret losing the most, and I decided I would regret losing physical science the most. At Harvard, the smell of solvents in my organic chemistry lab gave me serious headaches. Since we could substitute some of the chemistry lab courses with physics lab courses, I found the undergraduate program in chemistry and physics to be ideal. My undergraduate advisor was Roy Gordon, and one of the high points for me was his graduate course in statistical mechanics. The teaching assistant for this course was Peter Wolynes, and we had many wide ranging and interesting discussions that ignited my interest in statistical mechanics. An © 2014 American Chemical Society
Special Issue: William C. Swope Festschrift Published: June 19, 2014 6360
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The Journal of Physical Chemistry B
Special Issue Preface
Working with Hans was fun and exciting, and it also had a profound influence on how I approach scientific work. I have not known a more deeply intelligent, yet patient, generous and sensitive person, an opinion shared by most everyone with whom he has collaborated. He is very careful, rigorous, and thorough, and while working with him I developed an appreciation for formal theory, lucid formulations, and their role in computational method development. Hans introduced to me his tendency to completely change fields every once in a while, providing a wonderful mechanism for reinventing oneself scientifically. We worked together on some very “rich” problem areas, as he called them (sometimes known to others as quagmires), and working with him showed me that being careful, thorough, and persistent could lead to progress and insights in unexpected and professionally fulfilling ways even without a large number of publications. My post academic career has been entirely at IBM, but within this context, I have had opportunities to work in many different and interesting scientific as well as nonscientific areas. In 1982, I started at IBM Instruments, formerly a subsidiary headquartered in Connecticut that was involved in making scientific instruments and a laboratory benchtop computer. Here I maintained a small scientific research effort simulating water clusters but worked for IBM on programming (compilers, improved math functions, hardware simulation, digital signal processing), hardware design, documentation, and technical marketing support and developed business cases related to scientific computing. For me this was IBM boot camp, basic training in a cross section of computer industry skills. On the personal side, Connecticut was a great place to buy antiques, and my wife Karen and I began collecting, repairing, and restoring 19th century clocks. In the mid 1980s, I moved back to California to work at the IBM Palo Alto Scientific Center, also now extinct, but then a part of an IBM division that engaged universities and national laboratories on issues related to numerically intensive computing. This gave me the opportunity to collaborate with a number of academic people on scientific and computing issues, including numerical analysis techniques. While there I worked on novel approaches for vectorizing and parallelizing molecular dynamics programs, and had an effort to model heat transport in crystalline materials from laser ablation, both projects done with my colleague Rad Olson. During this time, I started new work with Hans Andersen on the modeling of liquid−solid phase transitions in three dimensions. For a short while, we even held the record for the largest MD simulation, on a million particles! We also worked together on liquid−solid transitions in two dimensions, searching for the elusive hexatic phase, and developed a thermodynamic theory for computing the equilibrium number of defects in crystalline materials. In the early 1990s, I was recruited by Bowen Liu to move to the IBM Almaden Research Center in San Jose, a research division site where I still work. I was initially involved with a number of others in the development of a computational chemistry software package called Mulliken that was capable of both quantum chemistry and classical MD/Monte Carlo (free energy) methods. This software is still used internally at IBM as a framework for hybrid QM/MM method development and prototyping. After that, we worked on projects to address scientific and technical computation and data management, especially for the petroleum and life sciences industries, as well as helping to formulate IBM’s business strategy for the life sciences.
chalkboard, I think it was about 30 feet long and went the length of his office. He erased it and starting at the left end eventually filled the entire board, as I looked on in awe. After about 2 hours, he admitted that the problem actually did not look solvable. Over the semester, I wrote up elaborate solutions for these problem sets that I understand were handed down, modified, and used for at least 10 years. It was an amazing experience and the students were very special. Some of us have remained in contact, and five of the six went on to become tenured faculty members at various universities: Geri Richmond, Randy Hampton, Morgan Ponder, Mary Blackwell, and Todd Silverman. We all remember and credit Bob with coining the phrase “random walk in idea space” to describe someone who may be continually babbling scientific nonsense. The time I spent with Bob was wonderful, and we collaborated on some work that became part of my thesis. We often discussed music and art. He even convinced me to take piano lessons and set me up with a teacher. I only kept up the lessons for about three years but eventually could play some Bach. Bob and I still see each other occasionally and talk over old times. My work with Fritz involved methodology development and applications of electronic structure theory to small molecules. His group was very dynamic and had excellent students as well as a large number of visiting faculty who brought with them a constant flow of exciting new ideas. Nick Handy from Cambridge and Peter Pulay from U. Texas were at Berkeley for much of the time when I was there. I worked with two of Fritz’s other students, Cliff Dykstra (U. Illinois) and Dave Yarkony (Johns Hopkins) during this time. Fritz really stressed good work habits. I have not known anyone who keeps up with the literature as well as he does, and no matter what question I had about electronic structure theory, he was able to go to a large bank of file cabinet drawers and pull out exactly the paper I needed to read. Besides learning the ins and outs of electronic structure theory, I developed very strong programming skills. If you spend much time working on quantum chemistry software, you will learn a lot about software development and a whole slew of programming tricks. Everyone in Fritz’s group at the time was involved in some form of programming effort. These skills opened opportunities for me to transition to the next phase of my career. Hans Andersen had contacted Fritz and explained that he wanted to start a big effort in modeling and simulation of liquids at Stanford, and was just about to buy all new computer equipment. He asked if he knew of anyone in the group that might be interested in joining him to help get this going, and Fritz recommended me. I looked forward to the idea of developing expertise to complement my quantum chemistry background, so I took the postdoctoral position at Stanford in 1979 to work in statistical mechanics with Hans. We developed formalism, methodology, and software and performed simulations (Monte Carlo and molecular dynamics) related to gas−liquid phase transitions, liquid state modeling, and solvation phenomena, including the computation of free energies of hydration. Working with Hans was very intense, and what I learned at Stanford was equivalent to earning a second doctorate. All the science, methodology, and every line of software was built from the ground up, and included the work on the velocity Verlet time step integration algorithm and a software implementation of his procedure for pressure control with an extended Lagrangian to support sampling consistent with isobaric (NpH and NpT) ensembles. 6361
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In the first decade of the 21st century, I was part of a large team working on the Blue Gene science program, a scientific effort to study protein folding, that was coupled with the Blue Gene supercomputer system development effort. This was a very exciting time. In addition to software development, this involved large replica exchange simulations, and included formal work on obtaining Markov models from the analysis of molecular dynamics trajectories, and formulations of expressions for quantifying statistical uncertainty with weighted histogram analysis methods (WHAM). The work to develop an improved water model, which became TIP4P-Ew, was done during this time period.
(now at U. Chicago), and Lee-Ping Wang (Stanford), at UC Berkeley with Teresa Head-Gordon and Lisa Felberg, and at Rutgers with David Case and David Cerutti (now at Schrodinger). Besides the people already mentioned, many other scientists have had a lasting and personal impact on my life. In particular, I would like to acknowledge Peter Kollman (UCSF), Ken Dill (UCSF, now at Stony Brook), Wilfred van Gunsteren (ETH), David Spellmeyer (UCSF, now at Nodality), and David Mobley (UCSF, now at UC Irvine). I have been extremely fortunate to have worked closely and productively for a large part of my career with personal friends and amazing computational chemists at IBM: Julia Rice, Hans Horn, and Jed Pitera. With regard to the evolution of computing technology, I am constantly reminded that the more things change, the more they stay the same. A couple of examples can illustrate this point. In the 1970s, Fritz Schaefer heralded the age of the dedicated minicomputer for computational chemistry, a radical idea at the time, since the trend then was for computational scientists to get smaller and smaller fractions of time at larger and larger supercomputer installations. When I started working in the 1980s with Hans Andersen at Stanford, the cool idea then was to get a minicomputer (usually a Digital Equipment Corporation PDP-11) and an attached vector processor (e.g., a Floating Point Systems Array Processor). These vector processors were painfully programmed in an assembly language that mapped to different bit fields of a 60-bit instruction word each of which controlled different hardware components in a highly pipelined CPU architecture. Since the vector processor was connected to the minicomputer using a relatively low bandwidth bus, data traffic had to be minimal and carefully organized. Furthermore, the vector processor we used was designed primarily for seismic processing for the petroleum industry, for which an intermediate precision 38-bit floating point arithmetic was adequate. To use this, we had to develop many tricks and needed to be very careful about the order of operations to accomplish suitable numerical precision in the result. As ancient as all this sounds, the issues are not much different from what people need to be concerned about today, and they are recurring themes in science. The interplay continues between supercomputer proponents and others involved in financing, building, maintaining, and upgrading dedicated large clusters of workstations. The world will always have supercomputers, and it will also have home grown systems, including such interesting contemporary efforts as Vijay Pande’s Folding at Home. Attached processors have come, left, and come back again most recently in the form of graphics processing units (GPUs). The recent craze for workstations loaded with GPUs is requiring scientists to address the same programming challenges with bandwidth, memory usage, and numerical precision as for the vector processors of the 1980s. Similarly, memory hierarchies have evolved in complexity but the issues with using them effectively are as old as figuring out how to get the fastest results when using magnetic tape. Integrated vector processors were the rage in the 1980s and 1990s and had a profound effect at the time on programming styles, but effective use of today’s pipelined scalar processors and multithreading still call for many of the same approaches. At IBM, we have had a large number of undergraduate and graduate summer students as well as postdoctoral researchers. Working with them has been richly rewarding. Having been a
We then worked with a major pharmaceutical company to assess the state of the art for force fields, which led to work still ongoing to understand in detail the effects on the electronic structure of solutes due to interactions with a polarizing solvent, and better ways to obtain classical force field parameters based on quantum chemical calculations. These efforts have catalyzed many lasting and fruitful relationships, notably at Stanford with Vijay Pande, Michael Shirts (now at U. Virginia), John Chodera (now at Memorial Sloan-Kettering), Nina Singhal Hinrichs 6362
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computational chemist in industry, I am frequently asked by students to compare and contrast academic and industrial careers in computational science. An increasingly important aspect of industrial research is the ability to work in teams, and especially for modeling, simulation, and theoretical researchers to work closely with experimentalists. This is actually a very good thing, since it guides even those of us with a primary interest in theory or methods development to work on important and relevant practical problems and to do work that is grounded in reality and responsive to commercial and/or societal needs. Working within time constraints and on specific important problems is not necessarily constricting; it also liberates one to employ whatever resources and methodologies are needed, even if they have to be invented, rather than to apply a single approach over and over to a limited class of problems. New techniques have to be invented and integrated with existing ones to address the complex problems of today. And learning new fields allows us to reinvent ourselves, which can be personally and professionally rewarding. For example, recently I have been performing simulations of the synthesis of polymeric nanoparticles in order to develop an understanding of how their physical properties are determined and can be controlled during the synthetic process. These polymeric materials are being considered as potential drug delivery vehicles. Finally, as a word of advice to students, I would highlight the importance of scientific cross training. This could include blending experiment and theory, chemistry and biology, or physics and materials science. Cross training allows one to bring new ideas and tools to bear on problems. Solutions to the technical problems of today will require a multidisciplinary approach. And the most exciting things in science often happen at the interface between fields. Concluding on a personal note, I have been married to my wife, Karen Maschino, for almost 30 years now, and I thank her for putting up with so much. We have two incredible children, Helen who is 15 and Finney who is 11, both of whom seem interested in science for some reason. Many people close to me also know that my family and I have grown grapes and made wine, Vino Maschino, for about 20 years. I wish to thank all of the peoplefamily, friends, and colleagueswho have helped make my scientific career a fun and interesting journey.
William C. Swope
IBM Almaden Research Center
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dx.doi.org/10.1021/jp502441b | J. Phys. Chem. B 2014, 118, 6360−6363
