NCI Central Scientific Computing Resources

扩大了NIDAP中特定于组的临床数据聚合实例的生产，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资源以及R Studio开发套件。 在22财年，NCI Halo环境进行了大量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通过编程将映像移动到更冷(更便宜)的存储层。 数据管理和分析任务区是在上一项任务的基础上于2012财年开发的，将于2013财年正式启动。2012财年的主要成就包括开发从DME到云的程序化分层的能力、将R Studio IDE集成到NIDAP中，以及旨在满足高级显微镜模式用户的数据管理和分析需求的试点项目。 安装到我们的云资源的直接冗余光纤连接，以最大限度地减少延迟和加快数据传输速率。为科学工作站开发经过认证的安全Ubuntu Linux桌面客户端安装。集中化的matlab许可，提高了安装的简易性和可用模块的数量。

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.