• MRI
  • fNIRS
  • HPC
  • Cognition
  • Animals
  • With the rapid development of hardware and software, the spatial and temporal resolution of various brain imaging techniques are becoming higher and higher, leading to the rapid growth in the volume of brain imaging data. This has made storage and calculation of massive follow-up data a great challenge and has become one of the technical barriers to cognitive neuroscience research and brain medical research. For the increasing volume of brain imaging data, the State Key Laboratory has specially constructed a high-performance computing facility. The hardware of the facility is mainly composed of two-way blade servers and four-way and eight-way rack servers. The total core count exceeds 2000, with a total RAM capacity of 7.2TB and a theoretical floating-point capacity is 33.4 trillion FLOPS. The storage resources are composed of a large-scale parallel file system and a backup storage system. The storage space of the parallel file system is 540 TB, and that of the backup storage system is 460 TB. The software resources include software suites developed by world-famous laboratories / companies (such as MATLAB, FSL, SPM, REST, FreeSurfer, Python, DPABI, AFNI, Anaconda, Tracula, and CIVET), as well as brain imaging data analysis and visualization software independently developed by ourselves (such as PANDA, GRETNA, and BrainNetViewer). Together, the hardware and software provide big data computing and storage support services for brain imaging.