Load sharing for optimistic parallel simulations on multicore machines

Parallel Discrete Event Simulation (PDES) is based on the partitioning of the simulation model into distinct Logical Processes (LPs), each one modeling a portion of the entire system, which are allowed to execute simulation events concurrently. This allows exploiting parallel computing architectures to speedup model execution, and to make very large models tractable. In this article we cope with the optimistic approach to PDES, where LPs are allowed to concurrently process their events in a speculative fashion, and rollback/ recovery techniques are used to guarantee state consistency in case of causality violations along the speculative execution path. Particularly, we present an innovative load sharing approach targeted at optimizing resource usage for fruitful simulation work when running an optimistic PDES environment on top of multi-processor/multi-core machines. Beyond providing the load sharing model, we also define a load sharing oriented architectural scheme, based on a symmetric multi-threaded organization of the simulation platform. Finally, we present a real implementation of the load sharing architecture within the open source ROme OpTimistic Simulator (ROOT-Sim) package. Experimental data for an assessment of both viability and effectiveness of our proposal are presented as well. Copyright is held by author/owner(s)

TaskPoint: sampled simulation of task-based programs

Sampled simulation is a mature technique for reducing simulation time of single-threaded programs, but it is not directly applicable to simulation of multi-threaded architectures. Recent multi-threaded sampling techniques assume that the workload assigned to each thread does not change across multiple executions of a program. This assumption does not hold for dynamically scheduled task-based programming models. Task-based programming models allow the programmer to specify program segments as tasks which are instantiated many times and scheduled dynamically to available threads. Due to system noise and variation in scheduling decisions, two consecutive executions on the same machine typically result in different instruction streams processed by each thread. In this paper, we propose TaskPoint, a sampled simulation technique for dynamically scheduled task-based programs. We leverage task instances as sampling units and simulate only a fraction of all task instances in detail. Between detailed simulation intervals we employ a novel fast-forward mechanism for dynamically scheduled programs. We evaluate the proposed technique on a set of 19 task-based parallel benchmarks and two different architectures. Compared to detailed simulation, TaskPoint accelerates architectural simulation with 64 simulated threads by an average factor of 19.1 at an average error of 1.8% and a maximum error of 15.0%.This work has been supported by the Spanish Government (Severo Ochoa grants SEV2015-0493, SEV-2011-00067), the Spanish Ministry of Science and Innovation (contract TIN2015-65316-P), Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272), the RoMoL ERC Advanced Grant (GA 321253), the European HiPEAC Network of Excellence and the Mont-Blanc project (EU-FP7-610402 and EU-H2020-671697). M. Moreto has been partially supported by the Ministry of Economy and Competitiveness under Juan de la Cierva postdoctoral fellowship JCI-2012-15047. M. Casas is supported by the Ministry of Economy and Knowledge of the Government of Catalonia and the Cofund programme of the Marie Curie Actions of the EUFP7 (contract 2013BP B 00243). T.Grass has been partially supported by the AGAUR of the Generalitat de Catalunya (grant 2013FI B 0058).Peer ReviewedPostprint (author's final draft

Assessing load-sharing within optimistic simulation platforms

The advent of multi-core machines has lead to the need for revising the architecture of modern simulation platforms. One recent proposal we made attempted to explore the viability of load-sharing for optimistic simulators run on top of these types of machines. In this article, we provide an extensive experimental study for an assessment of the effects on run-time dynamics by a load-sharing architecture that has been implemented within the ROOT-Sim package, namely an open source simulation platform adhering to the optimistic synchronization paradigm. This experimental study is essentially aimed at evaluating possible sources of overheads when supporting load-sharing. It has been based on differentiated workloads allowing us to generate different execution profiles in terms of, e.g., granularity/locality of the simulation events. © 2012 IEEE

QuEST and High Performance Simulation of Quantum Computers

We introduce QuEST, the Quantum Exact Simulation Toolkit, and compare it to ProjectQ, qHipster and a recent distributed implementation of Quantum++. QuEST is the first open source, OpenMP and MPI hybridised, GPU accelerated simulator of universal quantum circuits. Embodied as a C library, it is designed so that a user's code can be deployed seamlessly to any platform from a laptop to a supercomputer. QuEST is capable of simulating generic quantum circuits of general single-qubit gates and multi-qubit controlled gates, on pure and mixed states, represented as state-vectors and density matrices, and under the presence of decoherence. Using the ARCUS Phase-B and ARCHER supercomputers, we benchmark QuEST's simulation of random circuits of up to 38 qubits, distributed over up to 2048 compute nodes, each with up to 24 cores. We directly compare QuEST's performance to ProjectQ's on single machines, and discuss the differences in distribution strategies of QuEST, qHipster and Quantum++. QuEST shows excellent scaling, both strong and weak, on multicore and distributed architectures.Comment: 8 pages, 8 figures; fixed typos; updated QuEST URL and fixed typo in Fig. 4 caption where ProjectQ and QuEST were swapped in speedup subplot explanation; added explanation of simulation algorithm, updated bibliography; stressed technical novelty of QuEST; mentioned new density matrix suppor

A load-sharing architecture for high performance optimistic simulations on multi-core machines

In Parallel Discrete Event Simulation (PDES), the simulation model is partitioned into a set of distinct Logical Processes (LPs) which are allowed to concurrently execute simulation events. In this work we present an innovative approach to load-sharing on multi-core/multiprocessor machines, targeted at the optimistic PDES paradigm, where LPs are speculatively allowed to process simulation events with no preventive verification of causal consistency, and actual consistency violations (if any) are recovered via rollback techniques. In our approach, each simulation kernel instance, in charge of hosting and executing a specific set of LPs, runs a set of worker threads, which can be dynamically activated/deactivated on the basis of a distributed algorithm. The latter relies in turn on an analytical model that provides indications on how to reassign processor/core usage across the kernels in order to handle the simulation workload as efficiently as possible. We also present a real implementation of our load-sharing architecture within the ROme OpTimistic Simulator (ROOT-Sim), namely an open-source 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

Rational physical agent reasoning beyond logic

The paper addresses the problem of defining a theoretical physical agent framework that satisfies practical requirements of programmability by non-programmer engineers and at the same time permitting fast realtime operation of agents on digital computer networks. The objective of the new framework is to enable the satisfaction of performance requirements on autonomous vehicles and robots in space exploration, deep underwater exploration, defense reconnaissance, automated manufacturing and household automation