activity
20202025
most citedContinuous data assimilation of large eddy simulation by lattice Boltzmann method and local ensemble transform Kalman filter (LBM-LETKF)

6 citations · 15 across the 6 of their papers we have counts for

collaborators

6 papers

cs.DC2025★ 1 cited

ML-Based Optimum Number of CUDA Streams for the GPU Implementation of the Tridiagonal Partition Method

Milena Veneva, Toshiyuki Imamura

This paper presents a heuristic for finding the optimum number of CUDA streams by using tools common to the modern AI-oriented approaches and applied to the parallel partition algo…

cs.MS2024

Interface for Sparse Linear Algebra Operations

Ahmad Abdelfattah, Willow Ahrens, Hartwig Anzt +32

The standardization of an interface for dense linear algebra operations in the BLAS standard has enabled interoperability between different linear algebra libraries, thereby boosti…

physics.flu-dyn2023★ 4 cited

GPU Optimization of Lattice Boltzmann Method with Local Ensemble Transform Kalman Filter

Yuta Hasegawa, Toshiyuki Imamura, Takuya Ina +3

The ensemble data assimilation of computational fluid dynamics simulations based on the lattice Boltzmann method (LBM) and the local ensemble transform Kalman filter (LETKF) is imp…

physics.flu-dyn2023★ 6 cited

Continuous data assimilation of large eddy simulation by lattice Boltzmann method and local ensemble transform Kalman filter (LBM-LETKF)

Yuta Hasegawa, Naoyuki Onodera, Yuuichi Asahi +3

We investigate the applicability of the data assimilation (DA) to large eddy simulations (LESs) based on the lattice Boltzmann method (LBM). We carry out the observing system simul…

cs.LG2021★ 3 cited

MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems

Steven Farrell, Murali Emani, Jacob Balma +40

Scientific communities are increasingly adopting machine learning and deep learning models in their applications to accelerate scientific insights. High performance computing syste…

cs.DC2020★ 1 cited

White Paper from Workshop on Large-scale Parallel Numerical Computing Technology (LSPANC 2020): HPC and Computer Arithmetic toward Minimal-Precision Computing

Roman Iakymchuk, Daichi Mukunoki, Artur Podobas +15

In numerical computations, precision of floating-point computations is a key factor to determine the performance (speed and energy-efficiency) as well as the reliability (accuracy…