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Ino Lab
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A lab studying parallel processing that speeds up large-scale computation using GPUs and other hardware.
AboutAbout the lab
Speeding up large-scale computation with parallel processing.
Ino Lab studies high-performance computing technologies broadly, from basic theory to application software.
Its subjects include GPUs, clusters, grid computing, and medical image processing.
Through joint and commissioned research with companies and universities, the lab aims to train people who can work on the front lines of software development.
Key terms
- GPU
- A component for rendering images on a display. This lab uses it to speed up scientific computing
- Cluster
- A mechanism that connects multiple computers and uses them as a single system
- in silico
- Done on a computer. This lab simulates the physiology and pathology of living organisms in this way
ResearchResearch themes
To speed up computation-intensive scientific computing and data processing, the lab studies high-performance computing technologies, from basic theory to application software. Current work includes making use of GPUs, big data analysis, visualization of large-scale data, and biological simulation.
*Illustrative imageGeneral-Purpose Computing on GPUs
Using GPUs, which are components for rendering images on displays, the lab aims to speed up computation-intensive scientific computing. The appeal lies in pioneering new GPU application software that goes beyond graphics processing.
*Illustrative imageAccelerating Big Data Analysis
Using cluster systems that connect multiple computers, the lab works to speed up big data analysis, where data processing capacity is crucial. By functionally integrating hundreds of computers, it takes on the challenge of achieving both ease of use and high performance.
*Illustrative imageVisualization of Large-Scale 4D Data
The lab aims to visualize time-series 3D data, such as that from X-ray CT scanners, so that it can be understood intuitively. The rewarding part is achieving real-time processing at 10 frames per second or more for large-scale data exceeding tens of GB.
*Illustrative imageAccelerating Biological Simulators
The lab develops Flint, parallel software that simulates the physiology and pathology of living organisms entirely in silico (on a computer). It mainly contributes research on automatic parallelization techniques.
MembersFaculty
The members of Ino Lab consist of faculty, administrative assistants, and doctoral, master's, and undergraduate students.As of 2026
- ProfessorFumihiko Ino
- Associate ProfessorMasao Okita
- Assistant ProfessorKoki Masui
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: “DHL Netherlands local site computer room server racks (2) - IMG 3299” Jemimus / CC BY 2.0 (cropped)
- General-Purpose Computing on GPUs: “EVGA GeForce GTX 590” Intel Free Press / CC BY 2.0 (cropped)
- Accelerating Big Data Analysis: “PDC server room” Esquilo / CC BY-SA 3.0 (cropped)
- Visualization of Large-Scale 4D Data: “Climate visualization of atmosphere” UCRL and Forrest Hoffman and Jamison Daniel of Oak Ridge National Laboratory / Public domain (cropped)
- Accelerating Biological Simulators: “Dutch national supercomputer "Huygens"” Dennis van Zuijlekom / CC BY-SA 2.0 (cropped)
- Related lab (Izumi Lab): “Cluster.SlashFive” MEGWARE Computer GmbH / CC BY-SA 3.0 (cropped)
- Related lab (Koizumi Lab): “Network-Engineering Ashlan Chidester 36” Cloud899 / CC BY-SA 4.0 (cropped)
- Related lab (Nakashima Lab): “Sample view of data collection process using artificial intelligence application” Captain Andrew M. Freeman, Air Force Institute of Technology / Air Force Research Laboratories (AFRL), Sensors, ATR, Target Recognition Branch. / Public domain (cropped)
- Related lab (Uranishi Lab): “ISS-50 Shane Kimbrough uses a virtual reality headset in the Destiny lab” NASA / Public domain (cropped)
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