Gang FTP scheduling of periodic and parallel rigid real-time tasks

In this paper we consider the scheduling of periodic and parallel rigid tasks. We provide (and prove correct) an exact schedulability test for Fixed Task Priority (FTP) Gang scheduler sub-classes: Parallelism Monotonic, Idling, Limited Gang, and Limited Slack Reclaiming. Additionally, we study the predictability of our schedulers: we show that Gang FJP schedulers are not predictable and we identify several sub-classes which are actually predictable. Moreover, we extend the definition of rigid, moldable and malleable jobs to recurrent tasks

On the periodic behavior of real-time schedulers on identical multiprocessor platforms

This paper is proposing a general periodicity result concerning any deterministic and memoryless scheduling algorithm (including non-work-conserving algorithms), for any context, on identical multiprocessor platforms. By context we mean the hardware architecture (uniprocessor, multicore), as well as task constraints like critical sections, precedence constraints, self-suspension, etc. Since the result is based only on the releases and deadlines, it is independent from any other parameter. Note that we do not claim that the given interval is minimal, but it is an upper bound for any cycle of any feasible schedule provided by any deterministic and memoryless scheduler

Accelerated Steady-State Torque Computation for Induction Machines using Parallel-In-Time Algorithms

This paper focuses on efficient steady-state computations of induction machines. In particular, the periodic Parareal algorithm with initial-value coarse problem (PP-IC) is considered for acceleration of classical time-stepping simulations via non-intrusive parallelization in time domain, i.e., existing implementations can be reused. Superiority of this parallel-in-time method is in its direct applicability to time-periodic problems, compared to, e.g, the standard Parareal method, which only solves an initial-value problem, starting from a prescribed initial value. PP-IC is exploited here to obtain the steady state of several operating points of an induction motor, developed by Robert Bosch GmbH. Numerical experiments show that acceleration up to several dozens of times can be obtained, depending on availability of parallel processing units. Comparison of PP-IC with existing time-periodic explicit error correction method highlights better robustness and efficiency of the considered time-parallel approach

Update statistics in conservative parallel discrete event simulations of asynchronous systems

We model the performance of an ideal closed chain of L processing elements that work in parallel in an asynchronous manner. Their state updates follow a generic conservative algorithm. The conservative update rule determines the growth of a virtual time surface. The physics of this growth is reflected in the utilization (the fraction of working processors) and in the interface width. We show that it is possible to nake an explicit connection between the utilization and the macroscopic structure of the virtual time interface. We exploit this connection to derive the theoretical probability distribution of updates in the system within an approximate model. It follows that the theoretical lower bound for the computational speed-up is s=(L+1)/4 for L>3. Our approach uses simple statistics to count distinct surface configuration classes consistent with the model growth rule. It enables one to compute analytically microscopic properties of an interface, which are unavailable by continuum methods.Comment: 15 pages, 12 figure

Statistical Performance Analysis of an Ant-Colony Optimisation Application in S-NET

Kenneth MacKenzie, Philip K. F. Hölzenspies, Kevin Hammond, Raimund Kirner, Vu Thien Nga Nguyen, Iraneus te Boekhorst, Clemens Grelck, Raphael Poss, Merijn Verstraaten, 'Statistical Performance Analysis of an Ant-Colony Optimisation Application in S-NET'. Paper presented at the 2nd Workshop on Feedback-Directed Compiler Optimization for Multi-Core Architectures. Berlin, Germany, 12 January 2013.We consider an ant-colony optimsation problem implemented on a multicore system as a collection of asynchronous stream- processing components under the control of the S-NET coordina- tion language. Statistical analysis and visualisation techniques are used to study the behaviour of the application, and this enables us to discover and correct problems in both the application program and the run-time system underlying S-NET

Periodic Pattern Mining a Algorithms and Applications

Owing to a large number of applications periodic pattern mining has been extensively studied for over a decade Periodic pattern is a pattern that repeats itself with a specific period in a give sequence Periodic patterns can be mined from datasets like biological sequences continuous and discrete time series data spatiotemporal data and social networks Periodic patterns are classified based on different criteria Periodic patterns are categorized as frequent periodic patterns and statistically significant patterns based on the frequency of occurrence Frequent periodic patterns are in turn classified as perfect and imperfect periodic patterns full and partial periodic patterns synchronous and asynchronous periodic patterns dense periodic patterns approximate periodic patterns This paper presents a survey of the state of art research on periodic pattern mining algorithms and their application areas A discussion of merits and demerits of these algorithms was given The paper also presents a brief overview of algorithms that can be applied for specific types of datasets like spatiotemporal data and social network