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Ishiyama Lab
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The lab runs computations of the universe on supercomputers and interprets the resulting data.
AboutAbout the lab
Refining supercomputer computation to get closer to the structure of the universe.
Ishiyama Lab studies computational methods for numerical simulations run on large-scale supercomputers, as well as methods for operating computing systems.
Methods for analyzing and visualizing the enormous amounts of data produced by simulations are also research subjects.
The main application is the universe: the lab investigates the formation and evolution of various structures in the universe, such as dark matter and galaxies.
The lab also works on analyzing simulations using machine learning.
Key terms
- Numerical simulation
- A method that reproduces how a phenomenon changes by computing equations such as physical laws on a computer.
- Dark matter
- Matter that does not emit light and cannot be seen directly, but whose existence is inferred from its gravitational effects.
- Parallel algorithm
- A procedure that splits work among many CPUs and computes simultaneously in order to solve a problem faster.
ResearchResearch themes
Ishiyama Lab studies computational methods for numerical simulations run on large-scale supercomputers, and methods for analyzing and visualizing the enormous amounts of data obtained from them. The main application is the universe, and the lab also works on analyzing simulations using machine learning.
*Illustrative imageMethods for Fast Computation on Supercomputers
The lab studies high-speed computation on supercomputers with tens of thousands of CPUs or more, such as Fugaku. It uses GPUs and SIMD operations to speed up basic algorithms such as sorting and to develop parallel algorithms, and it also deals with methods for operating PC clusters.
*Illustrative imageAnalyzing and Visualizing Big Data
The lab studies methods for analyzing and visualizing petabyte-scale data obtained from large-scale simulations on supercomputers. The main target is the universe, where the lab investigates the formation and evolution of various structures such as dark matter and galaxies.
*Illustrative imageSimulation and Machine Learning
The lab works on using machine learning to improve the accuracy of numerical simulations. It is also pursuing research that uses simulations as training data to extract more information from real data.
MembersFaculty
- Associate ProfessorTomoaki Ishiyama
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “NCCS Discover Supercomputer (GSFC )” NASA Goddard Space Flight Center / NASA/GSFC/Bill Hrybyk / Public domain (cropped)
- Methods for Fast Computation on Supercomputers: “RIKEN R-CCS Fugaku” Barsaka2 / CC0 (cropped)
- Analyzing and Visualizing Big Data: “Cosmic web” Volker Springel / Max Planck Institute For Astrophysics / CC BY-SA 4.0 (cropped)
- Simulation and Machine Learning: “Neural network explain” TseKiChun / CC BY-SA 4.0 (cropped)
- Related lab (コンピュータネットワーク・セキュリティ
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- Related lab (kawa-lab
（川本・ 計良研究室） ): “Artificial Intelligence (AI) and Robotics exhibition at the Heinz Nixdorf MuseumsForum” Sergei Magel/HNF / CC BY-SA 4.0 (cropped) - Related lab (岸本研究室): “Enigma (crittografia) - Museo scienza e tecnologia Milano” Alessandro Nassiri / CC BY-SA 4.0 (cropped)
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