This paper presents a database containing 'ground truth' segmentations produced by humans for images of a wide variety of natural scenes. We define an error measure which quantifies the consistency between segmentations of differing granularities and find that different human segmentations of the same image are highly consistent. Use of this dataset is demonstrated in two applications: (1) evaluating the performance of segmentation algorithms and (2) measuring probability distributions associated with Gestalt grouping factors as well as statistics of image region properties.

/pdf/a-database-of-human-segmented-natural-images-and-its-2ve1vk356s.pdf

A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

https://deim.urv.cat/~alexandre.arenas/publicacions/pdf/review.pdf

Synchronization in complex networks

This survey covers rollback-recovery techniques that do not require special language constructs. In the first part of the survey we classify rollback-recovery protocols into checkpoint-based and log-based.Checkpoint-based protocols rely solely on checkpointing for system state restoration. Checkpointing can be coordinated, uncoordinated, or communication-induced. Log-based protocols combine checkpointing with logging of nondeterministic events, encoded in tuples called determinants. Depending on how determinants are logged, log-based protocols can be pessimistic, optimistic, or causal. Throughout the survey, we highlight the research issues that are at the core of rollback-recovery and present the solutions that currently address them. We also compare the performance of different rollback-recovery protocols with respect to a series of desirable properties and discuss the issues that arise in the practical implementations of these protocols.

/pdf/a-survey-of-rollback-recovery-protocols-in-message-passing-bnrpate93a.pdf

A survey of rollback-recovery protocols in message-passing systems

Parallel discrete event simulation (PDES), sometimes called distributed simulation, refers to the execution of a single discrete event simulation program on a parallel computer. PDES has attracted a considerable amount of interest in recent years. From a pragmatic standpoint, this interest arises from the fact that large simulations in engineering, computer science, economics, and military applications, to mention a few, consume enormous amounts of time on sequential machines. From an academic point of view, parallel simulation is interesting because it represents a problem domain that often contains substantial amounts of parallelism (e.g., see [59]), yet paradoxically, is surprisingly difficult to parallelize in practice. A sufficiently general solution to the PDES problem may lead to new insights in parallel computation as a whole. Historically, the irregular, data-dependent nature of PDES programs has identified it as an application where vectorization techniques using supercomputer hardware provide little benefit [14].A discrete event simulation model assumes the system being simulated only changes state at discrete points in simulated time. The simulation model jumps from one state to another upon the occurrence of an event. For example, a simulator of a store-and-forward communication network might include state variables to indicate the length of message queues, the status of communication links (busy or idle), etc. Typical events might include arrival of a message at some node in the network, forwarding a message to another network node, component failures, etc.We are especially concerned with the simulation of asynchronous systems where events are not synchronized by a global clock, but rather, occur at irregular time intervals. For these systems, few simulator events occur at any single point in simulated time; therefore parallelization techniques based on lock-step execution using a global simulation clock perform poorly or require assumptions in the timing model that may compromise the fidelity of the simulation. Concurrent execution of events at different points in simulated time is required, but as we shall soon see, this introduces interesting synchronization problems that are at the heart of the PDES problem.This article deals with the execution of a simulation program on a parallel computer by decomposing the simulation application into a set of concurrently executing processes. For completeness, we conclude this section by mentioning other approaches to exploiting parallelism in simulation problems.Comfort and Shepard et al. have proposed using dedicated functional units to implement specific sequential simulation functions, (e.g., event list manipulation and random number generation [20, 23, 47]). This method can provide only a limited amount of speedup, however. Zhang, Zeigler, and Concepcion use the hierarchical decomposition of the simulation model to allow an event consisting of several subevents to be processed concurrently [21, 98]. A third alternative is to execute independent, sequential simulation programs on different processors [11, 39]. This replicated trials approach is useful if the simulation is largely stochastic and one is performing long simulation runs to reduce variance, or if one is attempting to simulate a specific simulation problem across a large number of different parameter settings. However, one drawback with this approach is that each processor must contain sufficient memory to hold the entire simulation. Furthermore, this approach is less suitable in a design environment where results of one experiment are used to determine the experiment that should be performed next because one must wait for a sequential execution to be completed before results are obtained.

/pdf/parallel-discrete-event-simulation-m759whzicd.pdf

Parallel discrete event simulation

A number of library based parallel and sequential network simulators have been designed. The paper describes a library, called GloMoSim (Global Mobile system Simulator), for parallel simulation of wireless networks. GloMoSim has been designed to be extensible and composable: the communication protocol stack for wireless networks is divided into a set of layers, each with its own API. Models of protocols at one layer interact with those at a lower (or higher) layer only via these APIs. The modular implementation enables consistent comparison of multiple protocols at a given layer. The parallel implementation of GloMoSim can be executed using a variety of conservative synchronization protocols, which include the null message and conditional event algorithms. The paper describes the GloMoSim library, addresses a number of issues relevant to its parallelization, and presents a set of experimental results on the IBM 9076 SP, a distributed memory multicomputer. These experiments use models constructed from the library modules.

GloMoSim: a library for parallel simulation of large-scale wireless networks

Research and development efforts in the parallel and distributed simulation field over the last 15 years has progressed, largely independently, in two separate camps: the largely academic high performance parallel and distributed (discrete event) simulation (PADS) community, and the DoD-centered distributed interactive simulation (DIS) community. This tutorial gives an overview and comparison of work in these two areas, emphasizing issues related to distributed execution where these fields have the most overlap. Differences in the fundamental assumptions routinely used within each community are contrasted, followed by overviews of work in each community.

Parallel and distributed simulation

The High Level Architecture (HLA) provides the specification of a common technical architecture for use across all classes of simulations in the US Department of Defense. It provides the structural basis for simulation interoperability. The baseline definition of the HLA includes (1) the HLA Rules, (2) the HLA Interface Specification, and (3) the HLA Object Model Template. This paper describes the motivations and processes used to develop the High Level Architecture and provides a technical description of key elements of the architecture and supporting software. Services defined in the interface specification for providing time management (TM) and data distribution management (DDM) for distributed simulations are described.

/pdf/the-department-of-defense-high-level-architecture-3gberipv9v.pdf

The Department of Defense High Level Architecture

In optimistic parallel simulations, state-saving techniques have traditionally been used to realize rollback. In this article, we propose reverse computation as an alternative approach, and compare its execution performance against that of state-saving. Using compiler techniques, we describe an approach to automatically generate reversible computations, and to optimize them to reap the performance benefits of reverse computation transparently. For certain fine-grain models, such as queuing network models, we show that reverse computation can yield significant improvement in execution speed coupled with significant reduction in memory utilization, as compared to traditional state-saving. On sample models using reverse computation, we observe as much as a six-fold improvement in execution speed over traditional state-saving.

Efficient optimistic parallel simulations using reverse computation

High-performance message-based supercomputers have only recently emerged from the research laboratory. The commercial manufacturing of such products as the Intel iPSC, the Ametek s/14, the NCUBE/ten, and the FPS T Series - all based on multicomputer network technology - has sparked lively interest in high-performance computation, and particularly in the message-passing paradigm for parallel computation.This book makes readily available information on many aspects of the design and use of multicomputer networks, including machine organization, system software, and application programs. It provides an introduction to the field for students and researchers and a survey of important recent results for practicing engineers. The emphasis throughout is on design principles and techniques; however, there are also descriptions and comparison of research and commercial machines and case studies of specific applications."Multicomputer Networks" covers such major design areas as communication hardware, operating systems, fault tolerance, algorithms, and the selection of network topologies. The authors present results in each of these areas, emphasizing analytic models of interconnection networks, VLSI constraints and communication, communication paradigms and hardware support, multicomputer operating systems, and applications for distributed simulation and for partial differential equations. They survey the hardware designs and the available software and present a comparative performance study of existing machines.

Multicomputer Networks: Message-Based Parallel Processing

: A variation of the Time Warp parallel discrete event simulation mechanism is presented that is optimized for execution on a shared memory multiprocessor. In particular, the direct cancellation mechanism is proposed that eliminates the need for anti-messages and provides an efficient mechanism for canceling erroneous computations. The mechanism thereby eliminates many of the overheads associated with conventional, message-based implementations of Time Warp. More importantly, this mechanism effects rapid repairs of the parallel computation when an error is discovered. Initial performance measurements of an implementation of the mechanism executing on a BBN Butterfly multiprocessor are presented. These measurements indicate that the mechanism achieves good performance, particularly for many workloads where conservative clock synchronization algorithms perform poorly. Speedups as high as 56.8 using 64 processors were obtained. However, our studies also indicate that state saving overheads represent a significant stumbling block for many parallel simulations using Time Warp.

Richard M. Fujimoto

Papers

Parallel and distributed simulation

The Department of Defense High Level Architecture

Efficient optimistic parallel simulations using reverse computation

Multicomputer Networks: Message-Based Parallel Processing

Time Warp on a Shared Memory Multiprocessor.