PICASso Program in Integrated Computer and Application Sciences

1. Bio Genomics Center GFDL Geo Finance Center CS Engr. Astro PPPL PICASsoProgram in Integrated Computer and Application Sciences

2. Motivation • Computational science as third pillar of science • Explosion of information services • Both rely on scalable parallel systems • Technology marching apace, but challenge is to harness it • More complex phenomena: modeling and applied algorithms • Increasingly complex systems: computing, visualization, ... • Application researchers need CS understanding, collaboration • Seeking it increasingly at Princeton • Many major advances in CS are increasingly application-driven • CS must deal with scale and complexity of real applications

3. Motivation (contd.) • Next-generation researchers need to cross discipline boundaries • progress in own primary research areas • applications, algorithms, systems, visualization • new research challenges driven by new applications or technologies • new research areas developed at boundaries of existing ones • Lack of “bridge” people is hindering progress • especially in computational sciences • need to train such bridge people

4. Problems/Models Algorithms Parallel Software Analysis Tools Parallel Systems Data Visualization & Management Overall Goal Integrated Research and Training in entire computational pipeline

5. Specific Goals Research: Foster interdisciplinary research on campus • Between other departments and CS • Between other departments themselves Training: • Train science and engineering students in relevant aspects of CS • Train new generation of application-driven computer scientists • Train new breed of researcher: creates boundary areas, builds bridges Related Impact: • Add value to, and attract best students to, CS and other departments • Develop a successful program that others will emulate • Nucleus of a Computer and Application Sciences Center (?) • Hasten the simulation revolution in science

6. Why at Princeton? Why Now? • Excellent science/application departments • Growth in applications of scalable computing • Existing cross-disciplinary collaborations • Strong demand from other departments, undergrads, postdocs • Synergy with new Centers (Genomics, Finance) and local labs • Synergy with existing programs: PACM, PAC (undergrad) • Rapid change, and clear recognition of need • Keep computational science exciting for CS students

7. Existing Interdisciplinary Collaborations • Computational Biology • Singh (CS) and Weigert (MolBio): simulating immune response • Singh (CS) and Altman (Stanford Bio): protein structure • Biological Computing • Lipton (CS) and Landweber (MolBio) • Computational Cosmology • Singh (CS) and Ostriker (Astro) • Visualization • Dobkin (CS), Finkelstein (CS), Ostriker (Astro), Cen (Astro) • Display Wall (CS) with PPPL, Astro • Labs: GFDL, PPPL, AT&T, Lucent...

8. Bio Genomics Center GFDL Geo Finance Center CS Engr. Astro PPPL Support and Participation • NSF IGERT grant (in approval process) • Open to students/advisors from all departments • in proposal: CS, Astro, MolBio, EEB, Geo, Plasma Physics • plus others: Engineering departments, Genomics, Finance, etc. “Hub-and-spoke” model centered in Computer Science

9. Focus Areas • Computer Science • Models and methods • Parallel and distributed computing • Visualization and data management • Applications • Keep range of application areas wide and flexible • Natural sciences, engineering, finance and commercial, … • Scalable information services Not traditional numerical analysis or Scientific Computing program Research at boundary of applications and Computer Science (algorithms and systems)

10. Cross-Cutting CS Research Thrusts • New models • esp. for complex dynamic systems; e.g. immunology • Algorithms (sequential and parallel) • e.g.space- and time- adaptive methods • Tightly-coupled scalable parallel computing • algorithms, scaling, programming models, performance portability, programming environments, performance prediction • Parallel computing on clusters and “systems of systems” • room-wide and campus-wide • Visualization • extracting and steering through meaningful data • immersive visualization using display wall All areas highly application-driven

11. Initial Application Research Thrusts • Astrophysics • Galactic structure formation and nature of matter • Analyzing observational data: Sloan Sky Survey • Biology • Protein structure determination • Simulation of complex dynamic systems • Immunology, Neurobiology, Genomics • Geosciences • Earth’s surface circulation systems (ocean, atmosphere) • Earth’s interior circulation (solid-state deformation) • Information Management • scalable networked services

12. Structure and Infrastructure • Executive Committee • Jeremiah Ostriker (University Provost and Astro) • Jaswinder Pal Singh (CS) • Kai Li (CS) • David Dobkin (CS Chair) • Others in Managing Committee (one per department) • Weigert (MolBio), Spergel (Astro), Bunge (Geo), Held (GFDL), Tang (PPPL), Levin (EEB), Research Scientist • Equipment • 64-proc. Origin2000 (Astro/CS/PPPL), more to come • 128-proc. production cluster, 64-proc. development cluster • Display Wall • High-end rendering equipment (CS/Astro)

13. Key Features • Interdisciplinary curriculum development • CS courses in Computer Systems and Visualization • New computational courses in other departments • Team-taught cross-disciplinary vertical project courses • Tutorials and Seminars • Cross-department joint advising • Integrated research groups across disciplines • Internships in other departments and laboratories/industry • Cross-cutting annual thematic programs • Mechanisms to bring people together • “PICASso Central” in CS building • Computational Research in Princeton seminar series