University of Southern California Mork Family Department of Chemical Engineering and Materials Science The USC Andrew and Erna Viterbi School of Engineering USC
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Aiichiro Nakano


 
 
anakano@usc.edu



Aiichiro Nakano


Professor of Computer Science, Physics & Astronomy, and Chemical Engineering & Materials Science

 


Ph.D. University of Tokyo, Japan, 1989

 

 

Contact Information
Collaboratory for Advanced Computing and Simulations (CACS)

Department of Computer Science
Department of Physics & Astronomy
Mork Family Department of Chemical Engineering and Materials Science
University of Southern California
3651 Watt Way, VHE 610
Los Angeles, CA 90089-0242

Tel:
213-821-2657
Fax: 213-821-2664


In the News:
Campus's Supercomputing Center Hosts National Minority Engineering Workshop
DOE-SciDAC Funding awarded to Professors
USC Supercomputer Simulations Probe the Basis of Brittleness

 
Research Interests

High-end scientific computing on geographically distributed parallel supercomputers and virtual environment: 1) divide-and-conquer simulation algorithms with low time/space/bandwidth complexity and tight error controls; 2) scalable and sustainable parallel-and-distributed supercomputing frameworks; 3) immersive and interactive visualization and mining of large scientific datasets (billion-atom chemical bond networks); 4) hierarchical simulations and validations that automatically embed quantum-mechanical and atomistic calculations within continuum calculation with guaranteed quality-of-solutions; and 5) high-end computational materials science.

We have demonstrated: 1) unprecedented scales of quantum-mechanically accurate and well validated, chemically reactive molecular-dynamics (MD) simulations--1.06 billion-atom reactive force-field MD and 11.8 million-atom (1.04 trillion grid points) quantum-mechanical (QM) MD in the framework of density functional theory on adaptive multigrids--in addition to 134 billion-atom space-time multiresolution MD, with parallel efficiency 0.998 on 131,072 BlueGene/L processors; 2) an automated execution of hierarchical QM/MD simulation on a Grid of 6 supercomputer centers, in which the number of processors changed dynamically on demand and resources were allocated and migrated dynamically in response to unexpected faults; and 3) real-time visualization of a billion-atom chemical bond network, with an embedded graph-based topological analysis. 



Collaboratory for Advanced Computing and Simulations (CACS)

With Professors Priya Vashishta and Rajiv Kalia, I have co-founded CACS in 2002. The vision of CACS is: 1) to follow advances in computing technologies (hardware, software, algorithms) from teraflops to petaflops and beyond, to establish a comprehensive collaborative environment for geographically distributed computational scientists and information technology (IT) experts to perform the largest bio-nano simulations; and 2) to establish educational programs to propel students into careers in emerging areas of nano, bio, and information technologies both in academic and industrial settings. CACS has excellent computing and visualization facilities: a 2,048-processors, 6 teraflops Opteron- and Xeon-based Linux cluster, and a visualization laboratory with an 8' by 4' tiled display and an immersive and interactive 3D visualization environment. 


Dual-degree Graduate Education in High Performance Computing and Simulations

At USC, we have introduced a dual-degree program that allows students to obtain a Ph.D. in the physical sciences/engineering and an MS in Computer Science (CS). I have developed an MSCS program with specialization in High Performance Computing and Simulations (MSCS-HPCS), for which I serve as the coordinator. For the MSCS-HPCS program, I have developed HPCS courses: CSCI596 (Scientific Computing and Visualization), CSCI653 (High Performance Computing and Simulations), and PHYS516 (Methods of Computational Physics). 

 

Minority Research and Education 

CACS organizes annual Computational Science Workshops for Underrepresented Groups (CSWUG) to provide undergraduate students and mentors from underrepresented groups with hands-on experience in HPCS.

 

Selected Recent Publications

• A. Nakano, R. K. Kalia, K. Nomura, A. Sharma, P. Vashishta, F. Shimojo, A. C. T. van Duin, W. A. Goddard, III, R. Biswas, D. Srivastava, and L. H. Yang, "De novo ultrascale atomistic simulations on high-end parallel supercomputers," International Journal of High Performance Computing Applications, in press.
• A. Nakano, R. K. Kalia, K. Nomura, A. Sharma, P. Vashishta, F. Shimojo, A. C. T. van Duin, W. A. Goddard, III, R. Biswas,
and D. Srivastava, "A divide-and-conquer/cellular-decomposition framework for million-to-billion atom simulations of
chemical reactions," Computational Materials Science 38, 642 (2007).
• H. Takemiya, Y. Tanaka, S. Sekiguchi, S. Ogata, R. K. Kalia, A. Nakano, and P. Vashishta, "Sustainable adaptive Grid supercomputing: multiscale simulation of semiconductor processing across the Pacific," in Proceedings of Supercomputing 2006 (SC06), IEEE/ACM, 2006.
• C. Zhang, B. Bansal, P. S. Branicio, R. K. Kalia, A. Nakano, A. Sharma, and P. Vashishta, "Collision-free spatial hash functions for structural analysis of billion-vertex chemical bond networks," Computer Physics Communications 175, 339 (2006).
• I. Szlufarska, A. Nakano, and P. Vashishta, "A crossover in the mechanical response of nanocrystalline ceramics," Science 309, 911 (2005).
• F. Shimojo, R. K. Kalia, A. Nakano, and P. Vashishta, "Embedded divide-and-conquer algorithm on hierarchical real-space grids," Computer Physics Communications 167, 151 (2005).
• A. Sharma, A. Nakano, R. K. Kalia, P. Vashishta, S. Kodiyalam, P. Miller, W. Zhao, X. Liu, T. J. Campbell, and A. Haas, "Immersive and interactive exploration of billion-atom systems," Presence: Teleoperators and Virtual Environments 12, 85 (2003); Best Paper of IEEE Virtual Reality 2002.
• A. Nakano, R. K. Kalia, P. Vashishta, T. J. Campbell, S. Ogata, F. Shimojo, and S. Saini, "Scalable atomistic simulation algorithms for materials research," Scientific Programming 10, 263 (2002); the Best Paper Award of ACM/IEEE SC01