Computational SSDs implement the in-storage computing (ISC) paradigm and benefit applications by taking over I/O-intensive tasks from the host. Existing works have proposed various frameworks aiming at easy access to ISC functionalities, and among them generic frameworks with file-based abstractions offer better usability. However, since intermediate output by ISC tasks may leave files in a dirty state, concurrent access to and the integrity of file data should be properly managed, which has not been fully addressed. In this paper, we present TxISC, a generic ISC framework that coordinates the host kernel and device firmware to offer a versatile file-based programming model. Under the hood, TxISC turns each invocation of an ISC task into a transaction with full ACID guarantee, fully covering concurrency control and data protection. TxISC implements transactions at low cost by leveraging the out-of-place write characteristic of NAND flash. Evaluation on full-stack hardware shows that transactions incur almost no runtime performance penalty compared with existing ISC architectures. Application case studies demonstrate that the programming model of TxISC can be used to offload complex logic and deliver significant speedup over host-only solutions.

Regular path queries (RPQs) in graph databases are bottlenecked by the memory wall. Emerging processing-in-memory (PIM) technologies offer a promising solution to dispatch and execute path matching tasks in parallel within PIM modules. We present Moctopus, a PIM-based data management system for graph databases that supports efficient batch RPQs and graph updates. Moctopus employs a PIM-friendly dynamic graph partitioning algorithm, which tackles graph skewness and preserves graph locality with low overhead for RPQ processing. Moctopus enables efficient graph update by amortizing the host CPU's update overhead to PIM modules. Evaluation of Moctopus demonstrates superiority over the state-of-the-art traditional graph database.