In high-end computing environments, remote file transfers of very large data sets to and from computational resources are commonplace as users are typically widely distributed across different organizations and must transfer in data to be processed and transfer out results for further analysis. Local transfers of this same data across file systems are also frequently performed by administrators to optimize resource utilization when new file systems come on-line or storage becomes imbalanced between existing file systems. In both cases, files must traverse many components on their journey from source to destination where there are numerous opportunities for performance optimization as well as failure. A number of tools exist for providing reliable and/or high performance file transfer capabilities, but most either do not support local transfers, require specific security models and/or transport applications, are difficult for individual users to deploy, and/or are not fully optimized for highest performance.
Shift is a framework for Self-Healing Independent File Transfer that provides high performance and resilience for local and remote transfers through a variety of techniques. These include end-to-end integrity via cryptographic hashes, throttling of transfers to prevent resource exhaustion, balancing transfers across resources based on load and availability, and parallelization of transfers across multiple source and destination hosts for increased redundancy and performance. In addition, Shift was specifically designed to accommodate the diverse heterogeneous environments of a widespread user base with minimal assumptions about operating environments. In particular, Shift is unique in its ability to provide advanced reliability and automatic single and multi-file parallelization to any stock command-line transfer application while being easily deployed by both individual users as well as entire organizations.\