Ricerc@Sapienza

One limitation of current Software Transactional
Memory (STM) implementations is that a transaction that
has already become inconsistent because of updates of data
it has accessed by concurrently committing transactions is
anyhow allowed to run up to either its commit request or
its next transactional shared-data access. These are the points
where the STM layer gains control back from the application
code and can perform transaction re-validation. However, these
explicit interactions with the STM layer may occur well after
the materialization of the inconsistency of the transaction,
leading to waste of CPU time and low energy efficiency. In this
project we pursue timeliness of re-validation via the introduction of analytical models aimed at predicting the best moments for
attempting a proactive re-validation of the running transaction.
With this approach we aim at probabilistically aborting a no
longer consistent transaction way before the STM layer is
able to perform the same kind of midway consistency check
thanks to an explicit interaction requested by the overlying
application code. To inject model-based re-validation points
along the lifetime of the transaction we plan to exploit a Linux kernel module whose target is the one of enabling a control flow variation along threads running transactions with very fine time-granularity. Therefore it would allow triggering re-validation at the exact optimal point (or around it) that was predicted by the analytical models. We plan to experiment our approach within the well-known open source TinySTM platform and the TPC-C benchmark. The relevance of this research line is the one of improving both completion timeliness and energy consumption of transactions in modern applications hosted by last generation multi-core machines.