Transparent and efficient shared-state management for optimistic simulations on multi-core machines

Traditionally, Logical Processes (LPs) forming a simulation model store their execution information into disjoint simulations states, forcing events exchange to communicate data between each other. In this work we propose the design and implementation of an extension to the traditional Time Warp (optimistic) synchronization protocol for parallel/distributed simulation, targeted at shared-memory/multicore machines, allowing LPs to share parts of their simulation states by using global variables. In order to preserve optimism's intrinsic properties, global variables are transparently mapped to multi-version ones, so to avoid any form of safety predicate verification upon updates. Execution's consistency is ensured via the introduction of a new rollback scheme which is triggered upon the detection of an incorrect global variable's read. At the same time, efficiency in the execution is guaranteed by the exploitation of non-blocking algorithms in order to manage the multi-version variables' lists. Furthermore, our proposal is integrated with the simulation model's code through software instrumentation, in order to allow the application-level programmer to avoid using any specific API to mark or to inform the simulation kernel of updates to global variables. Thus we support full transparency. An assessment of our proposal, comparing it with a traditional message-passing implementation of variables' multi-version is provided as well. © 2012 IEEE

Speculative Client Execution in Deferred Update Replication

ABSTRACT Deferred Update Replication (DUR) is a powerful replication technique that allows parallelism of clients' execution while a global certification phase checks the validity of the transactional execution against workloads running on remote nodes. The well-known favorable scenario of DUR is when remote transactions rarely conflict with each other. In this paper we show that, even in this case, the conflicts happening among local application threads can significantly decrease performance. We address this problem by using speculation. We let local transactions propagate their postexecution snapshot to other local transactions before the outcome of the global certification is notified. This way, in scenarios where accesses are partitioned across nodes, we prevent local transactions from aborting each other. Through experimental study based on well-known transactional benchmarks we assess the effectiveness of the approach, gaining more than 10× using TPC-C benchmark

State-machine replication for planet-scale systems

Online applications now routinely replicate their data at multiple sites around the world. In this paper we present Atlas, the first state-machine replication protocol tailored for such planet-scale systems. Atlas does not rely on a distinguished leader, so clients enjoy the same quality of service independently of their geographical locations. Furthermore, client-perceived latency improves as we add sites closer to clients. To achieve this, Atlas minimizes the size of its quorums using an observation that concurrent data center failures are rare. It also processes a high percentage of accesses in a single round trip, even when these conflict. We experimentally demonstrate that Atlas consistently outperforms state-of-The-Art protocols in planet-scale scenarios. In particular, Atlas is up to two times faster than Flexible Paxos with identical failure assumptions, and more than doubles the performance of Egalitarian Paxos in the YCSB benchmark.H2020 - Horizon 2020 Framework Programme(825184

Application Transparent Migration of Simulation Objects with Generic Memory Layout

This paper presents the design of a global memory management architecture supporting application transparent migration of simulation objects (or LPs) whose state is scattered across dynamically allocated memory chunks. Our approach is based on a non-intrusive background protocol that provides each instance of the simulation kernel with information on the current mapping of the virtual address space of all the other instances. Dynamic memory requests by the application layer are then locally mapped onto virtual-address ranges that maximize the likelihood of being portable onto the address space of a remote kernel instance. In this way, independently of the load-balancing trigger (or policy), we maximize the likelihood that a desirable migration across a specific couple of kernels can actually take place due to compliance of the corresponding source/destination address spaces. We have integrated the global memory manager within the ROme OpTimistic Simulator (ROOT-Sim), namely a run-time environment based on the optimistic synchronization paradigm which automatically and transparently parallelizes the execution of event-handler based simulation programs conforming to ANSI-C. Further, we provide a contribution in the direction of widening load balancing schemes for optimistic simulation systems by defining migration triggers and selection policies for the objects to be migrated on the basis of memory usage patterns. An experimental assessment of the architecture and of memory oriented load balancing is also provided. © 2011 IEEE

Supports for transparent object-migration in PDES systems

It is well known that Parallel Discrete Event Simulation systems may suffer, in terms of delivered performance, from imbalance of the computational load. In case of conservative synchronization we may experience CPU under-utilization and/or excessive communication overhead. On the other hand, for the optimistic paradigm we may even have rollback thrashing effects, with a consequent reduction of the percentage of productive (ie not rolled back) work carried out. This paper presents the design of a global memory management architecture supporting application-transparent migration of simulation objects whose state is scattered across dynamically allocated memory chunks. Our approach is based on a non-intrusive background protocol that provides each instance of the simulation kernel with information on the current mapping of the virtual address space of all the other instances. Dynamic memory requests by the application layer are then locally mapped onto virtual-address ranges that maximize the likelihood of being portable onto the address space of a remote kernel instance. In this way, independently of the load-balancing trigger (or policy), we maximize the likelihood that a desirable migration across a specific couple of kernels can actually take place due to compliance of the corresponding source/destination address spaces. We have integrated the global memory manager within the ROme OpTimistic Simulator (ROOT-Sim), namely a run-time environment based on the optimistic synchronization paradigm which automatically and transparently parallelizes the execution of event-handler-based simulation programs conforming to ANSI-C. Further, we provide a contribution in the direction of widening load-balancing schemes for optimistic simulation systems by defining migration triggers and selection policies for the objects to be migrated on the basis of memory usage patterns. An experimental assessment of the architecture and of memory-oriented load balancing is also provided. Journal of Simulation (2012) 6, 279-293. doi:10.1057/jos.2012.13; published online 20 July 201

Transactional Auto Scaler: Elastic Scaling of In-Memory Transactional Data Grids

In this paper we introduce TAS (Transactional Auto Scaler), a system for automating elastic-scaling of in-memory transactional data grids, such as NoSQL data stores or Distributed Transactional Memories. Applications of TAS range from on-line self-optimization of in-production applications to automatic generation of QoS/cost driven elastic scaling policies, and support for what-if analysis on the scalability of transactional applications. The key innovation at the core of TAS is a novel performance forecasting methodology that relies on the joint usage of analytical modeling and machine-learning. By exploiting these two, classically competing, methodologies in a synergic fashion, TAS achieves the best of the two worlds, namely high extrapolation power and good accuracy even when faced with complex workloads deployed over public cloud infrastructures. We demonstrate the accuracy and feasibility of TAS via an extensive experimental study based on a fully fledged prototype implementation, integrated with a popular open-source transactional in-memory data store (Red Hat’s Infinispan), and industry-standard benchmarks generating a breadth of heterogeneous workloads

On the viability of speculative transactional replication in database systems: A case study with PostgreSQL

We investigate the feasibility of systematic speculative processing in the context of Optimistic Atomic Broadcast (OAB) based replication of database systems. Specifically, we present the design and prototypal implementation of a fully speculative version of the Postgre SQL open source relational database, together with experimental results showing performance advantages over non-speculative replication. © 2013 IEEE