NCI Central Scientific Computing Resources

NCI 中央科学计算资源

• 批准号: 10707819
• 负责人: Jeffrey Shilling
• 金额: $ 1706.03万
• 依托单位: OFFICE OF THE DIRECTOR, NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10707819
• 关键词: Address; Adopted; Area; Back; Client; Clinical; Clinical Data; Collaborations; Data; Data Aggregation; Data Analyses; Data Storage and Retrieval; Development; Environment; Fiber; Fostering; Foundations; Genomics; Glacier; Image; Image Analysis; Intelligence; Licensing; Linux; Methods; Microscopy; Modality; Monitor; National Center for Advancing Translational Sciences; Performance; Pilot Projects; Production; Proteomics; Resources; Secure; Speed; System; Systems Analysis; United States National Institutes of Health; base; computing resources; cost; cost efficient; data and analysis portal; data exchange; data interoperability; data management; data resource; data sharing; digital pathology; improved; metabolomics; microbiome; multimodality; programs; scientific computing; task analysis

Production of group-specific clinical data aggregation instances in NIDAP was expanded and several new data resources were incorporated, including the FRCE computational cluster, HALO 2D Image Analysis and Digital Pathology Resource, and the R Studio development suite. Numerous technical upgrades aimed at enhancing performance and reducing costs were made to the NCI HALO environment in FY22, including upgrading to v3.4, migrating from SMB to NFS, adopting Glacier for user back-ups, developing an automated performance monitoring SOP, and implementing Intelligent Tiering for programmatically moving images to colder (less expensive) storage tiers. The Data Management and Analysis task area was developed in FY22 from a prior task and will formally launch in FY23. Major FY22 accomplishments include developing capabilities for programmatic tiering to the cloud from DME, integration of the R Studio IDE into NIDAP, and pilot projects aimed at addressing data management and analysis needs for users of advanced microscopy modalities. Installation of direct redundant fiber connections to our cloud resources to minimize latency and speed data transfer rates. Development of a certified secure Ubuntu Linux desktop client installation for scientific workstations. Centralization of MatLab licensing which improves ease of installation and number of available modules.

NIDAP中特定于组的临床数据聚合实例的生产得到了扩展，并纳入了几个新的数据资源，包括FRCE计算集群、HALO 2D图像分析和数字病理学资源以及R Studio开发套件。 NCI HALO环境在2022财年进行了多项旨在提高性能和降低成本的技术升级，包括升级到v3.4、从SMB迁移到NFS、采用Glacier进行用户备份、开发自动化性能监控SOP，以及实施智能分层，以便以编程方式将映像移动到较冷（较便宜）的存储层。 数据管理和分析任务领域是在2022财年根据之前的任务开发的，并将于2023财年正式启动。 2022财年的主要成就包括开发从DME到云的编程分层功能，将R Studio IDE集成到NIDAP中，以及旨在满足高级显微镜用户的数据管理和分析需求的试点项目。 安装直接冗余光纤连接到我们的云资源，以最大限度地减少延迟并加快数据传输速率。为科学工作站开发经认证的安全Ubuntu Linux桌面客户端安装。MatLab许可的集中化，提高了安装的便利性和可用模块的数量。