Nobuyasu Ito

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EDBT 2026 Demo / reviewers in the wild / expert

dblp:69/4563 · DBLP profile ↗

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3ranked-venue papers

1as first author

2since 2021 · last 2026

—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 3 · 1 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems 1 paper		High-performance computing · 33% Performance modeling and evaluation · 33% Processor architecture and microarchitecture · 33%
Interdisciplinary, comprehensive, and emerging computing 1 paper		Computational science and engineering · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

Topic	Papers	Last	Evidence papers
Computational science and engineering › statistical physics statistical physics simulation	1	1990	Monte Carlo simulation of the Ising model and random number generation on the vector processor · SC 1990
Performance modeling and evaluation › simulation monte carlo simulation	1	1990	Monte Carlo simulation of the Ising model and random number generation on the vector processor · SC 1990
High-performance computing scientific computing systems	1	1990	Monte Carlo simulation of the Ising model and random number generation on the vector processor · SC 1990
Processor architecture and microarchitecture vector processing	1	1990	Monte Carlo simulation of the Ising model and random number generation on the vector processor · SC 1990

Methods — techniques the papers use, named apart from their topics

vectorizable algorithm · 0.0random number generation · 0.0

Year	Publication	Venue	Position
2026	C-3PQ: A Closeness Centrality-based Circuit Partitioner for Quantum Simulations abstract Simulating quantum circuits (QC) on high-performance computing (HPC) systems is essential for validating quantum algorithms and probing the potential of large-scale quantum computation before the advent of scalable quantum hardware. However, state vector simulations are resource-intensive, often requiring large clusters with thousands of compute nodes and large amounts of memory. To address this, we introduce C-3PQ, an end-to-end framework that minimizes inter-node data movement through an efficient circuit partitioning scheme alongside a flexible code generator to offer a portable simulation solution. By formulating the distribution of the state vector and circuit over multiple nodes as a graph problem, we utilize closeness centrality to assess gate importance and design a fast, scalable partitioning method. C-3PQ compiles the resulting partitions into highly optimized kernels targeting a wide range of hardware platforms from Intel, AMD, NVIDIA and ARM. Moreover, compared to a state-of-the-art implementation specific for NVIDIA platforms, C-3PQ achieves a speedup of up to \(40\%\) at a fraction of the cost when partitioning the state vector. Doru-Thom Popovici, Harlin Lee, Naoki Yoshioka, Mauro Del Ben, Nobuyasu Ito, Katherine Klymko, Daan Camps, Anastasiia Butko	ICS	5
2024	Quantum-centric supercomputing for materials science: A perspective on challenges and future directions Yuri Alexeev, Maximilian Amsler, Marco Antonio Barroca, Sanzio Bassini, Torey Battelle, Daan Camps, David Casanova, Young Jay Choi, Fred Chong, Charles Chung, Christopher Codella, Antonio D. Córcoles, James Cruise, Alberto Di Meglio, Ivan Duran, Thomas Eckl, Sophia E. Economou, Stephan J. Eidenbenz, Bruce Elmegreen, Clyde Fare, Ismael Faro, Cristina Sanz Fernández, Rodrigo Neumann Barros Ferreira, Keisuke Fuji, Bryce Fuller, Laura Gagliardi, Giulia Galli, Jennifer R. Glick, Isacco Gobbi, Pranav Gokhale, Salvador de la Puente Gonzalez, Johannes Greiner, William Gropp, Michele Grossi, Emanuel Gull, Burns Healy, Matthew R. Hermes, Benchen Huang, Travis S. Humble, Nobuyasu Ito, Artur F. Izmaylov, Ali Javadi-Abhari, Douglas M. Jennewein, Shantenu Jha, Bert de Jong, Petar Jurcevic, William M. Kirby, Stefan Kister, Masahiro Kitagawa, Joel Klassen, Katherine Klymko, Kwangwon Koh, Masaaki Kondo, Doga Murat Kürkçüoglu, Krzysztof Kurowski, Teodoro Laino, Ryan Landfield, Matthew L. Leininger, Vicente Leyton-Ortega, Ang Li 0006, Meifeng Lin, Junyu Liu, Nicolás Lorente, André Luckow, Simon Martiel, Francisco Martín-Fernández, Margaret Martonosi, Claire Marvinney, Arcesio Castañeda Medina, Dirk Merten, Antonio Mezzacapo, Kristel Michielsen, Abhishek Mitra, Tushar Mittal, Kyungsun Moon, Joel Moore, Sarah Mostame, Mario Motta, Young-Hye Na, Yunseong Nam, Prineha Narang, Yu-ya Ohnishi, Daniele Ottaviani, Matthew Otten, Scott Pakin, Vincent R. Pascuzzi, Edwin Pednault, Tomasz Piontek, Jed W. Pitera, Patrick Rall, Gokul Subramanian Ravi, Niall Robertson, Matteo A. C. Rossi, Piotr Rydlichowski, Hoon Ryu, Georgy Samsonidze, Mitsuhisa Sato, Nishant Saurabh, Kunal Sharma, Soyoung Shin, George Slessman, Mathias Steiner, Iskandar Sitdikov, In-Saeng Suh, Eric D. Switzer, Joel Thompson, Synge Todo, Minh C. Tran, Dimitar Trenev, Christian Trott, Huan-Hsin Tseng, Norm M. Tubman, Esin Tureci, David García Valiñas, Sofia Vallecorsa, Christopher Wever, Konrad W. Wojciechowski, Xiaodi Wu 0001, Shinjae Yoo, Nobuyuki Yoshioka, Victor Wen-zhe Yu, Seiji Yunoki, Sergiy Zhuk, Dmitry Zubarev	Future Gener. Comput. Syst.	40
1990	Monte Carlo simulation of the Ising model and random number generation on the vector processor abstract The Monte Carlo simulation of the Ising model on the vector processor is discussed with particular attention given to the development of the vectorizable algorithm and the implementation, tuning, and tests necessary for the large-scale computations. The machine is the HITAC S820/80. The maximum simulation speed is 0.9310/sup 9/ spins per second for the ferromagnetic Ising models on a simple cubic lattice. The random number generation algorithms are also explained. The present generator can produce 0.6210/sup 9/ 32-bit random integers per second. The results of randomness tests which use the two-dimensional Ising model are presented.> Nobuyasu Ito, Yasumasa Kanada	SC	1