Delta: Data Reduction for Integrated Application Workflows and Data Storage

Abstract

Data sizes are growing far faster than storage bandwidth. To address this growing gap, Integrated Application Workflows (IAWs) are being investigated as a potential to replace using a centralized storage array for storing intermediate data. IAWs run multiple simulation workflow components concurrently on an HPC resource connecting these components using compute area resources. These IAWs require high frequency and high volume data transfers between compute nodes and staging area nodes during the lifetime of a large parallel computation. The available network bandwidth between the two areas may not be enough to efficiently support the data movement. As the processing power available to compute resources increases, the requirements for this data transfer will become more difficult to satisfy and perhaps will not be satisfiable at all since network capabilities are not expanding at a comparable rate. It is necessary to reduce the volume of data without reducing the quality of data when it is being processed and analyzed. Delta resolves the issue by addressing the lifetime data transfer operations. Delta removes subsequent identical copies of already transmitted data prior to transfer and restores those pieces once the data has reached the destination using previously transmitted data. Delta is able to identify duplicated information and determine the most space efficient way to represent it. Initial tests show about 50 % reduction in data movement while maintaining the same data quality and transmission frequency. Given the simplicity of the approach and the log-based format employed by ADIOS, the approach can also be used to write less data to the storage array outside of IAW considerations.