NUMA architectures posed the challenge of rethinking parallel applications due to the non-homogeneity introduced by their design, and their real benefits are limited to the characteristics of the particular workload. We name as partitionable transactional workloads such workloads that may be able to exploit the distributed nature of NUMA, such as transactional workloads where data and accesses can be easily partitioned among the so called NUMA zones. However, in case those workloads require the synchronization on shared data, we have to face the issue of exploiting the NUMA architecture also in the concurrency control for their transactions. Therefore in this paper we present a NUMA-aware concurrency control for transactional memory that we designed for promoting scalability in scenarios where both the transactional workload is prone to scale, and the characteristics of the underlying memory model are inherently non-uniform, such as NUMA architectures.
This paper shows the issues to face while designing contention management policies that involve best-effort hardware transactions. Also, in this paper we present Octonauts, a solution for scheduling HTM transactions without relying on on-the-fly information. Octonauts learns the objects accessed by a hardware transaction while running and it uses them in case of conflict. It also proposes an innovative scheme for optimizing the communication between transactions running in hardware and software.
Multicore architectures are increasingly becoming prone to transient faults. In this paper we briefly present Shield, a middleware to provide transactional applications with resiliency to those faults that can happen anytime during the execution of a processor but do not cause any hardware interruption. Shield is inspired by the state machine replication approach, where computational resources are partitioned, the shared state is fully replicated, and requests are executed by all partitions in the same order. Shield embeds a set of algorithmic and system innovations to limit the overhead with respect to non-fault-tolerant solutions. They include a fast total order layer that lets application threads and computational nodes co-operate in order to fast deliver.
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