Brief Announcement: On the Correctness of Transaction Processing with External Dependency

We briefly introduce a unified model to characterize correctness levels stronger (or equal to) serializability in the presence of application invariant. We propose to classify relations among committed transactions into data-related and application semantic-related. Our model delivers a condition that can be used to verify the safety of transactional executions in the presence of application invariant

HaTS: Hardware-Assisted Transaction Scheduler

In this paper we present HaTS, a Hardware-assisted Transaction Scheduler. HaTS improves performance of concurrent applications by classifying the executions of their atomic blocks (or in-memory transactions) into scheduling queues, according to their so called conflict indicators. The goal is to group those transactions that are conflicting while letting non-conflicting transactions proceed in parallel. Two core innovations characterize HaTS. First, HaTS does not assume the availability of precise information associated with incoming transactions in order to proceed with the classification. It relaxes this assumption by exploiting the inherent conflict resolution provided by Hardware Transactional Memory (HTM). Second, HaTS dynamically adjusts the number of the scheduling queues in order to capture the actual application contention level. Performance results using the STAMP benchmark suite show up to 2x improvement over state-of-the-art HTM-based scheduling techniques