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

An overview of technologies concerned with distributing the execution of simulation programs across multiple processors is presented. Here, particular emphasis is placed on discrete event simulations. The High Level Architecture (HLA) developed by the Department of Defense in the United States is first described to provide a concrete example of a contemporary approach to distributed simulation. The remainder of this paper is focused on time management, a central issue concerning the synchronization of computations on different processors. Time management algorithms broadly fall into two categories, termed conservative and optimistic synchronization. A survey of both conservative and optimistic algorithms is presented focusing on fundamental principles and mechanisms. Finally, time management in the HLA is discussed as a means to illustrate how this standard supports both approaches to synchronization.

Parallel simulation: distributed simulation systems

This paper describes results of an empirical study to evaluate the effect of communications delays on the performance of the Time Warp mechanism in order to assess the effectiveness of Time Warp in distributed computing environments An implementation of Time Warp on a collection of networked workstations is used in this study Performance using synchronous and asynchronous message passing primitives are compared, and it is observed that Time Warp experiences much more rolled back computation when using the synchronous primitives for certain applications Message passing is decomposed into a computation component at the sender and receiver processors, and a transmission delay component that represents the amount of time the message remains “in transit” within the network The effect of each of these components on Time Warp performance is studied It is observed that communications latency in distributed computing environments can significantly degrade the efficiency of Time Warp for applications containing large numbers of simulator objects with small event granularity (by increasing the amount of rolled back computation), particularly applications using “self-driving” simulator objects However, for applications containing large grained events, communication delay appears to have little effect on rollback behavior in Time Warp

Effect of communication overheads on Time Warp performance: an experimental study

Parallel discrete event simulation techniques have enabled the realization of large-scale models of communication networks containing millions of end hosts and routers. However, the performance of these parallel simulators could be severely degraded if proper synchronization algorithms are not utilized. In this paper, we compare the performance and scalability of synchronous and asynchronous algorithms for conservative parallel network simulation. We develop an analytical model to evaluate the efficiency and scalability of certain variations of the well-known null message algorithm, and present experimental data to verify the accuracy of this model. This analysis and initial performance measurements on parallel machines containing hundreds of processors suggest that for scenarios simulating scaled network models with constant number of input and output channels per logical process, an optimized null message algorithm offers better scalability than efficient global reduction based synchronous protocols.

/pdf/conservative-synchronization-of-large-scale-network-4b8hxkxewu.pdf

Conservative synchronization of large-scale network simulations

Neural systems are composed of a large number of highly-connected neurons and are widely simulated within the neurological community. In this paper, we examine the application of parallel discrete event simulation techniques to networks of a complex model called the Hodgkin-Huxley neuron[1]. We describe the conversion of this model into an event-driven simulation, a technique that offers the potential of much greater performance in parallel and distributed simulations compared to time-stepped techniques. We report results of an initial set of experiments conducted to determine the feasibility of this parallel event-driven Hodgkin-Huxley model and analyze its viability for large-scale neural simulations.

https://www.cs.mcgill.ca/~carl/neuralsim.pdf

Parallel Event-Driven Neural Network Simulations Using the Hodgkin-Huxley Neuron Model

It is well known that Time Warp may suffer from poor performance due to excessive rollbacks caused by overly optimistic execution. Here we present a simple flow control mechanism using only local information and GVT that limits the number of uncommitted messages generated by a processor, thus throttling overly optimistic TW execution. The flow control scheme is analogous to traditional networking flow control mechanisms. A ``window'' of messages defines the maximum number of uncommitted messages allowed to be scheduled by a process. Committing messages is analogous to acknowledgments in networking flow control. The initial size of the window is calculated using a simple analytical model that estimates the instantaneous number of messages that a process will eventually commit. This window is expanded so that the process may progress up to the next commit point (generally the next fossil collection), and to accommodate optimistic execution. The expansions to the window are based on monitoring TW performance statistics so the window size automatically adapts to changing program behaviors.The flow control technique presented here is simple and fully automatic. No global knowledge or synchronization (other than GVT) is required. We also develop an implementation of the flow control scheme for shared memory multiprocessors that uses dynamically sized pools of free message buffers. Experimental data indicates that the adaptive flow control scheme maintains high performance for "balanced workloads'', and achieves as much as a factor of 7 speedup over unthrottled TW for certain irregular workloads.

Richard M. Fujimoto

Papers

Parallel simulation: distributed simulation systems

Effect of communication overheads on Time Warp performance: an experimental study

Conservative synchronization of large-scale network simulations

Parallel Event-Driven Neural Network Simulations Using the Hodgkin-Huxley Neuron Model

Adaptive flow control in time warp