paper / mitsuhisasato / Oct 31
This paper demonstrates a closed-loop workflow integrating a Heron quantum processor with the Fugaku supercomputer (152,064 nodes) for electronic structure calculations. This hybrid approach enables approximations of chemistry models beyond exact diagonalization, achieving accuracy comparable to classical approximation methods. The work highlights advancements in orchestrating computational resources at an unprecedented scale for current supercomputers.
quantum-computinghybrid-computinghpcquantum-chemistryhigh-performance-computingelectronic-structure
“The research conducted the largest-scale electronic structure computation involving both quantum and classical high-performance computing.”
paper / mitsuhisasato / Sep 18
This paper details methods for accelerating the IPOP-CMA-ES algorithm on high-performance computing architectures. By integrating BLAS/LAPACK routines and employing two distinct parallelization strategiesâsequential-ordering and concurrent processingâthe researchers achieved substantial, including superlinear, speedups on a 6144-core supercomputer. The concurrent processing strategy demonstrated superior performance.
cma-esblackbox-optimizationhigh-performance-computingparallel-computingmpiopenmpsupercomputers
“IPOP-CMA-ES can be accelerated using parallel computing.”
paper / mitsuhisasato / Jul 16
This preliminary study demonstrates the successful application of the Fugaku supercomputer for accelerating MRI data processing using the FMRIB Software Library (FSL). The study found high consistency in tensor-based measurements and subcortical structure segmentations between Fugaku and conventional systems, while significantly reducing processing time. This indicates a viable solution for handling the growing volume of MRI data and the computational demands of its analysis.
mri-data-processingsupercomputingmedical-imaginghigh-performance-computingneurosciencefsl
“The Fugaku supercomputer can process MRI data using FSL.”
paper / mitsuhisasato / Jun 6
CORTEX is a new algorithmic framework for large-scale brain simulation, leveraging the Fugaku Supercomputer. Its core innovation, Indegree Sub-Graph Decomposition, enables efficient parallel processing of synaptic interactions by segmenting the global graph into independent sub-graphs. This approach eliminates data racing without mutexes and enhances communication-computation overlap, leading to significant performance improvements over existing solutions like NEST Simulator.
brain-simulationhigh-performance-computingneuromorphic-computingparallel-algorithmssupercomputerscomputational-neurosciencefugaku-supercomputer
“CORTEX is an algorithmic framework for large-scale brain simulation.”