Editor’s note: Reprinted with permission from ASCR Discovery.
Since the Department of Energy’s Office for Advanced Scientific Computing Research (ASCR) and Office of Science launched the Computational Science Graduate Fellowship (DOE CSGF) in 1991, the program has supported more than 430 scientists’ training and has built a community of leaders who continue to shape this dynamic field.
The program was created with a specific goal: to develop a workforce that could harness the world’s most powerful supercomputers to solve complex science and engineering problems. The fellowship has evolved with technological and scientific changes over the past three decades and has forged connections and collaborations among researchers. Physicists, materials scientists, chemists, biologists, mathematicians, computer scientists and engineers have applied these tools to address computational challenges across industry, academia and government laboratories.
“The program’s always been able to grow and adapt and continue to produce this cohort of really talented leaders in the community who have this broader view of what computational science is about, who then go out and shape what’s going on,” says Jeffrey Hittinger of Lawrence Livermore National Laboratory, a DOE CSGF recipient from 1996 to 2000 and now one of the program’s principal investigators (PIs).
During the 1980s, computers were changing quickly, becoming bigger, faster and more powerful with emerging capabilities for modeling fluid dynamics and other scientific phenomena. “With the rapidly increasing capabilities of these supercomputers, it was becoming clear to many of us that there was a potential for enormous impact if they could be used as tools for scientific discovery,” says David Brown, a fellowship co-PI and director of the Computational Research Division at Lawrence Berkeley National Laboratory who has worked with the DOE CSGF since its beginning. Because only a few facilities, such as major government laboratories, had these machines, the scientists working with them got much of their training on the job. Only a few universities had access to supercomputers and none offered formal training in the emerging field of computational science.
Key leaders in this emerging field met in 1990 to discuss the problem and craft a solution, leading to the fellowship’s launch the following year. At the time, other prestigious graduate fellowships primarily financed tuition and a provided a stipend, but the DOE CSGF incorporated additional features that remain hallmarks of the program today. For example, all recipients complete at least one practicum experience at a DOE national laboratory. To support broad interdisciplinary training in computational science, each recipient completes a program of study, an individualized course curriculum designed to expand their knowledge and support their research. Fellows also have access to professional development funds that can be used for conference travel or to buy a computer workstation.
James Corones of DOE’s Iowa State University-based Ames Laboratory was a chief architect of DOE CSGF as it exists today and began managing the program in 1993. In 1997, Corones founded the Krell Institute, which oversees the fellowship to this day.
The DOE CSGF held its first fellows’ meeting in Minneapolis in 1993, and the conference has been held yearly since 1999. Now known as the annual program review, this conference lets fellows share their research and connect with practicum hosts, alumni and program sponsors. “Because of the networking that we’ve done through the conferences in the annual review, DOE CSGF fellows and alumni make strong connections with people that they deal with even today,” says Barbara Helland, who is now ASCR’s associate director for science. She worked with Corones to manage the program at both Ames Laboratory and the Krell Institute.
James Hack, a former director of the National Center for Computational Sciences at Oak Ridge National Laboratory, has helped mold the program from the start. He notes that over the past 50 years, “computational capabilities have increased by a factor of 10 billion due to advances in technology and algorithms. I can’t think of any capability has grown that rapidly.”
Computers in the early 1990s were powerful enough to handle a growing range of simulation problems in fluid dynamics. In subsequent years, larger and faster computers could go even further, tackling complex simulations of chemical processes, more complete models of the climate system and even genomics and computational biology. “I do think of the computer as a virtual laboratory,” Hack says. As datasets have exploded in size and machine-learning algorithms and technologies have evolved, artificial intelligence is driving another revolution in how researchers use computational science to manage information and drive discovery.
The fellowship has overcome challenges across its many years. Frederick Howes, the fellowship’s program manager at ASCR in the early 1990s, advocated for its continuation when its funding was threatened. More recently, proposed reorganizations of government-supported graduate research fellowships jeopardized the program. The computational science community, including the hundreds of DOE CSGF fellows and alumni, rallied and successfully advocated for the program’s continuation under DOE.
Meanwhile the DOE CSGF has achieved its key purpose: Graduates are shaping the scientific landscape. Alumna Judith Hill (1999-2003), for example, used her DOE CSGF experience, including a practicum at Sandia National Laboratories, to get her first staff position at that laboratory. She has since served in computational leadership positions at Oak Ridge and now is a computational science project leader at Livermore. “As a computational scientist,” Hill says, “it’s useful for me to have not only the domain expertise, applied math in my case, but also the algorithmic computer science expertise – all the things that CSGF emphasizes in the program of study, in the practicum experience and in the experiences of the fellows.”
As deputy director of the Materials Project, Berkeley Lab’s Anubhav Jain (2006-2011) uses DOE supercomputers to model new materials for a range of energy challenges, including better batteries. “Computational materials scientists usually don’t receive much formal education about large computers, how they work and what limits they face,” he says, which inhibits researchers’ ability to apply high-performance computing (HPC). “The DOE CSGF brought many of these issues to the forefront and helped me develop an appreciation and understanding of computer science issues in large calculations.” In 2015, he received a $2.5 million DOE Early Career Research Program award focused on using high-throughput computations to discover new materials.
This year, the DOE CSGF supports 95 fellows pursuing graduate degrees at 40 different institutions. The incoming class this fall will comprise a record 32 fellows, half of whom are women. Nearly half come from groups that have been underrepresented in science, technology, engineering and mathematics.
ASCR’s Helland refers to computational science as science’s third leg, with experiment/observation and theory. “Having people who understand how to take the physical world and explain it in mathematical terms and in applications code – that need is never going away.”