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

This paper reports main results of a peer study on future trends in distributed simulation and distributed virtual environments (Strassburger et al. 2008). The peer study was based on the opinions of more than 60 experts which were collected by means of a survey and personal interviews. The survey collected opinions concerning the current state-of-the-art, relevance, and research challenges that must be addressed to advance and strengthen these technologies to a level where they are ready to be applied in day-to-day business in industry. Most important result of this study is the observation that as research areas, both distributed simulation and distributed virtual environments are attributed a high future practical relevance and a high economic potential. At the same time the study shows that the current adoption of these technologies in the industrial sector is rather low. The study analyses reasons for this observation and identifies open research challenges.

/pdf/future-trends-in-distributed-simulation-and-distributed-56fgz2jf7f.pdf

Future trends in distributed simulation and distributed virtual environments: results of a peer study

This tutorial reviews issues concerning the execution of discrete event simulation programs on multiprocessor and distributed computing platforms. The synchronization problem that has driven much of the research in this field is reviewed. Space-parallel and time-parallel approaches to concurrent execution are described. Experiences in applying these techniques to specific applications are examined. Finally, issues that must be considered to develop efficient concurrent simulation programs are discussed.

http://rsim.cs.illinois.edu/arch/qual_papers/systems/15a.pdf

Parallel and distributed discrete event simulation: algorithms and applications

An abstraction called space-time memory is discussed that allows parallel discrete event simulation programs using the Time Warp mechanism to be written using shared memory constructs. A few salient points concerning the implementation and use of space-time memory in parallel simulation are discussed. It is argued that this abstraction is useful from a programming standpoint for certain applications, and can yield good performance. Initial performance measurements of a prototype implementation of the abstraction on a shared-memory multiprocessor are described, and compared with a conventional, message-based implementation of Time Warp.

Parallel Discrete Event Simulation Using Space-Time Memory

This paper investigates issues concerning federations of sequential and/or parallel simulators. An approach is proposed for creating federated simulations by defining a global conceptual model of the entire simulation, and then mapping individual entities of the conceptual model to implementations within individual federates. Proxy entities are defined as a means for linking entities that are mapped to different federates. Using this approach, an implementation of a federation of optimistic simulators is examined. Issues concerning the adaptation of optimistic simulators to a federated system are discussed. The performance of the federated system utilizing runtime infrastructure (RTI) software executing on a shared memory multiprocessor (SMP) is compared with a native (non-federated) SMP-based optimistic parallel simulator. It is demonstrated that a well designed federated simulation system can yield performance comparable to a native, parallel simulation engine, but important implementation issues must be properly addressed.

An approach for federating parallel simulators

The behavior of n interacting processors synchronized by the Time Warp protocol is analyzed using a discrete-state, continuous-time Markov chain model. The performance and dynamics of the processes (or processors) are analyzed under the following assumptions: exponential task times and timestamp increments on messages, each event message generates one new message that is sent to a randomly selected process, negligible rollback, state saving, and communication delay, unbounded message buffers, and homogeneous processors. Several performance measures are determined, such as: the fraction of processed events that commit, speedup, rollback probability, expected length of rollback, the probability mass function for the number of uncommitted processed events, the probability distribution function for the virtual time of a process, and the fraction of time the processors remain idle. The analysis is approximate, thus the results have been validated through performance measurements of a Time Warp testbed executing on a shared-memory multiprocessor. >

Richard M. Fujimoto

Papers

Future trends in distributed simulation and distributed virtual environments: results of a peer study

Parallel and distributed discrete event simulation: algorithms and applications

Parallel Discrete Event Simulation Using Space-Time Memory

An approach for federating parallel simulators

Performance analysis of Time Warp with multiple homogeneous processors