Abstract-In this article we introduce GMU, a genuine partial replication protocol for transactional systems, which exploits an innovative, highly scalable, distributed multiversioning scheme. Unlike existing multiversion-based solutions, GMU does not rely on a global logical clock, which represents a contention point and can limit system scalability. Also, GMU never aborts read-only transactions and spares them from distributed validation schemes. This makes GMU particularly efficient in presence of read-intensive workloads, as typical of a wide range of real-world applications.GMU guarantees the Extended Update Serializability (EUS) isolation level. This consistency criterion is particularly attractive as it is sufficiently strong to ensure correctness even for very demanding applications (such as TPC-C), but is also weak enough to allow efficient and scalable implementations, such as GMU. Further, unlike several relaxed consistency models proposed in literature, EUS has simple and intuitive semantics, thus being an attractive, scalable consistency model for ordinary programmers.We integrated the GMU protocol in a popular open source in-memory transactional data grid, namely Infinispan. On the basis of a large scale experimental study performed on heterogeneous experimental platforms and using industry standard benchmarks (namely TPC-C and YCSB), we show that GMU achieves linear scalability and that it introduces negligible overheads (less than 10%), with respect to solutions ensuring non-serializable semantics, in a wide range of workloads.
Abstract. In this article we present SCORe, a scalable one-copy serializable partial replication protocol. Differently from any other literature proposal, SCORe jointly guarantees the following properties: (i) it is genuine, thus ensuring that only the replicas that maintain data accessed by a transaction are involved in its processing, and (ii) it guarantees that read operations always access consistent snapshots, thanks to a one-copy serializable multiversion scheme, which never aborts read-only transactions and spares them from any (distributed) validation phase. This makes SCORe particularly efficient in presence of read-intensive workloads, as typical of a wide range of real-world applications. We have integrated SCORe into a popular open source distributed data grid and performed a large scale experimental study with well-known benchmarks using both private and public cloud infrastructures. The experimental results demonstrate that SCORe provides stronger consistency guarantees (namely One-Copy Serializability) than existing multiversion partial replication protocols at no additional overhead.
This paper describes a non-blocking checkpointing mode in support of optimistic parallel discrete event simulation. This mode allows real concurrency in the execution of state saving and other simulation specific operations (e.g. event list update, event execution), with the aim at removing the cost of recording state information from the completion time of the parallel simulation application. We present an implementation of a C library supporting non-blocking checkpointing on a myrinet based cluster, which demonstrates the practical viability of this checkpointing mode on standard off-the-shelf hardware. By the results of an empirical study on classical parameterized synthetic benchmarks we show that, except for the case of minimal state granularity applications, non-blocking checkpointing allows improvement of the speed of the parallel execution, as compared to commonly adopted, optimized checkpointing methods based on the classical blocking mode. A performance study for the case of a Personal Communication System (PCS) simulation is additionally reported to point out the benefits from non-blocking checkpointing for a real world application.
In this article we address the reshuffle of the design of optimistic simulation kernels in order to fit multi-core/multiprocessor machines. This is done by providing a reference optimistic simulation architecture based on the symmetric multithreaded paradigm, where each simulation kernel instance is allowed to run a dynamically changing set of worker threads that share the whole load of LPs hosted by that kernel, and that can run both application-level event handlers and kernellevel housekeeping tasks. With this organization, CPU-cores can be dynamically reassigned to the different kernels depending on fluctuations of the workload, so to maximize productivity in an orthogonal manner with respect to traditional load balancing schemes, typically employed in the context of single-threaded simulation kernels. In order to optimize efficiency and reduce wait-for-lock-release phases while synchronizing worker threads running in kernel mode, we borrow from Operating Systems' theory by readapting the top/bottom-halves paradigm to the design of optimistic simulation systems. We also present a real implementation of our multi-threaded architecture within the ROme OpTimistic Simulator (ROOT-Sim), namely an opensource C-based simulation platform implemented according to the PDES paradigm and the optimistic synchronization approach. Experimental results for an assessment of the validity of our proposal are presented as well.
We present the design and implementation of an autonomic state manager (ASM) tailored for integration within optimistic parallel discrete event simulation (PDES) environments based on the C programming language and the executable and linkable format (ELF), and developed for execution on x86_64 architectures. With ASM, the state of any logical process (LP), namely the individual (concurrent) simulation unit being part of the simulation model, is allowed to be scattered on dynamically allocated memory chunks managed via standard API (e.g., malloc/free). Also, the application programmer is not required to provide any serialization/ deserialization module in order to take a checkpoint of the LP state, or to restore it in case a causality error occurs during the optimistic run, or to provide indications on which portions of the state are updated by event processing, so to allow incremental checkpointing. All these tasks are handled by ASM in a fully transparent manner via (A) runtime identification (with chunk-level granularity) of the memory map associated with the LP state, and (B) runtime tracking of the memory updates occurring within chunks belonging to the dynamic memory map. The co-existence of the incremental and non-incremental log/restore modes is achieved via dual versions of the same application code, transparently generated by ASM via compile/link time facilities. Also, the dynamic selection of the best suited log/ restore mode is actuated by ASM on the basis of an innovative modeling/optimization approach which takes into account stability of each operating mode with respect to variations of the model/environmental execution parameters.
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