Waiting algorithms for synchronization in large-scale multiprocessors

Waiting time is an important transport quantity that is complementary to average current and its fluctuation. So far all the studies of waiting time distribution (WTD) are limited to steady state transport (either dc or ac). In this work, we present a theory to calculate WTD for coherent electronic systems in transient regime. We express the generating function of full counting statistics using Keldysh non-equilibrium Green's functions formalism. Our analysis goes beyond the wideband approximation and is suitable for first principles calculation on realistic systems. Analytic solution has been obtained for short and long time behaviors of waiting times. At short times, the WTD shows a linear dependence on the waiting time while in the long time limit, WTD follows Poisson distribution. We have applied this theory to a quantum dot connected by two leads and calculated cumulants of transferred charge as well as WTD in the transient regime. We have demonstrated how to relate WTD to experimental measured data.

Large-scale MIN-based shared-memory multiprocessor systems have long shared memory latency. Private caches can improve memory access latency but they may suf fer from the cache coherence problem and potentially lower data locality due to data sharing and multiproces sor scheduling. These two problems also increase shared memory load and may result in frequent memory stalls. In this paper, we evaluate the performance of memory caches, a cache memory placed in front of shared memory, in a large-scale multiprocessor system in the presence of pro cessor caches. The memory cache is shown to have good performance and scalability.

For a class of renewal process waiting time distributions defined herein, one may describe the distribution of asymptotic residual waiting times. The relationship between the two distributions characterizes the class, which includes the gamma distribution. Possible consequences for hypothesis testing are discussed.

Human dynamics is known to be inhomogeneous and bursty but the detailed understanding of the role of human factors in bursty dynamics is still lacking. In order to investigate their role we devise an agent-based model, where an agent in an uncertain situation tries to reduce the uncertainty by communicating with information providers while having to wait time for responses. Here the waiting time can be considered as cost. We show that the optimal choice of the waiting time under uncertainty gives rise to the bursty dynamics, characterized by the heavy tailed distribution of optimal waiting time. We find that in all cases the efficiency for communication is relevant to the scaling behavior of the optimal waiting time distribution. On the other hand, the cost turns out in some cases to be irrelevant depending on the degree of uncertainty and efficiency.

In this paper, we describe an elementary combinatorial approach for deriving the waiting and response time distributions in a few classical priority queueing models. By making use of lattice paths that are linked in a natural way to the stochastic processes analyzed, the proposed method offers new insights and complements the results previously obtained by inverting the associated Laplace transforms.

We consider the stationary waiting time distribution under the FIFO discipline for multi-server queues with (possibly heterogeneous) phase type servers and renewal arrivals, and for queues which can be represented as a quasi-birth-and-death process. It is shown that the complementary distribution function of the stationary waiting time in these queues is of the form where θ is positive and the dj are probabilities. A complete characterization of θ and dj , which lends itself to interesting probabilistic interpretations, is given for all these cases. Except in the case of the multiserver GI/PH/c queue which is to be discussed in detail elsewhere, we provide an efficient algorithm to compute the waiting time distribution.

As faults are unavoidable in large scale multiprocessor systems, it is important to be able to determine which units of the system are working and which are faulty. System-level diagnosis is a long-standing realistic approach to detect faults in multiprocessor systems. Diagnosis is based on the results of tests executed on the system units. In this work we evaluate the performance of evolutionary algorithms applied to the diagnosis problem. Experimental results are presented for both the traditional genetic algorithm (GA) and specialized versions of the GA. We then propose and evaluate specialized versions of Estimation of Distribution Algorithms (EDA) for system-level diagnosis: the compact GA and Population-Based Incremental Learning both with and without negative examples. The evaluation was performed using four metrics: the average number of generations needed to find the solution, the average fitness after up to 500 generations, the percentage of tests that got to the optimal solution and the average time until the solution was found. An analysis of experimental results shows that more sophisticated algorithms converge faster to the optimal solution.

Racial/ethnic disparities in emergency department wait times in the United States, 2013-2017.

A single-server subject to random breakdowns (or preemptive interruptions) insure the service of customers who arrive in the system according to a homogeneous Poisson process. The customer who arrive when the server is blocked (out of order or busy) is admitted to repeat his call until the server can provide his service. The purpose of this paper is to provide a simple approach to compute the stationary probability distribution of the customer's sojourn time in the system. We also obtain the probability distribution of the work which is different from the sojourn time contrary to the classical FIFO discipline. We show how mean performance measures such as mean waiting time and mean sojourn time can be obtained. Finally, we obtain asymptotic distributions of the waiting and sojourn times in heavy traffic and in the case of low retrial rate.

Hippopotamus algorithm for optimal sizing of hybrid renewable energy system

Directory-based cache coherence scheme using number-balanced binary tree

The drastically reduced costs and improved performance of fiber optic components in recent years offers an opportunity to economically incorporate high-bandwidth optical communication links within a large-scale multiprocessor system. In this paper, the design, implementation, and initial performance of a fiber optic bus for a tightly coupled multiprocessor system are discussed. This optical bus ulitizes a multiple fiber-multiple star configuration with data rates of up to 80 MHz. It transmits bus control line information by repetitively scanning the control lines and transmitting their states as a packet of bits. It is currently being used for a 30-processor system called the Heidelberg Polyp, which has a custom bus design. However, the design approach is a general one that could easily be adapted to other buses, especially asynchronous buses such as the VME bus.

Surgical outpatient clinics continuously face challenges in delivering efficient and effective care. An expanding population and chronic staff shortages makes sustainability critical. The primary objective of this study was to identify modifiable factors contributing to longer wait times in an orthopaedic outpatient clinic. A single-centre prospective observational cohort study was conducted at Western Australia's state trauma centre. Over a four-week period, clinicians completed forms identifying delays in clinic, and clinic numbers were captured through an electronic booking system. Data was analysed using SPSS v27. Face-to-face (FTF) and telehealth (TH) clinic volumes grew by 18.9% and 361.1% respectively between 2018 and 2022. For the study period, 754 forms were completed for attending clinic patients. This captured 42.4% and 96.8% of FTF and TH actual attendance. The average wait time for doctor consultation was 63.9 min. Wait times significantly reduced when x-rays were performed prior to clinic (P < 0.001), and when an unaccredited registrar held the on-call phone (P < 0.001). Trauma clinics ran overtime in 95% of cases compared to elective clinics in which 25% ran overtime. The golden staffing ratio was one doctor for 13 patients. TH experienced few delays related to technological fault. This study demonstrates that clinic volume continues to rise. It highlights the demand for adequate staffing and identifies several modifiable factors that influence clinic efficiency. It demonstrates the growth of TH as an alternative modality for outpatient surgical services and its potential for future expansion.

In the application of probabilistic models to waiting time problems it is sometimes necessary to compare two or more different service patterns to determine which pattern is most effective in decreasing waiting times. In many cases the mean waiting time of the customer is the criterion used to measure the effectiveness of the service because it is the easiest property of the waiting time distribution to calculate. It is the purpose of this note to give an example of a simple waiting time problem in which it is intuitively clear that the mean waiting time gives a misleading indication of the effectiveness of the service and that some other measure should be considered. Suppose there are N independent bus routes passing a particular bus stop A which by different paths arrive at a particular destination point B. Let T,,(') (i = 1, 2, . . . N; n1, 2, . . .) be the instant at which the nth arrival of a bus on the ith route occurs at point A. We will assume that On(i) = T1+1'i'Tn), (n = 1 2 . . .) are independent identically distributed positive random variables such that

Design and optimization of a CMOS power amplifier using innovative fractional-order particle swarm optimization