Computing and Informatics (E-Journal - Institute of Informatics, SAS, Bratislava)
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Optimizing Memory Usage in L4-Based Microkernel
Get PDFMemory allocation is a critical aspect of any modern operating system kernel because it must run continuously for long periods of time, therefore memory leaks and inefficiency must be eliminated. This paper presents different memory management algorithms and their aplicability to an L4-based microkernel. We aim to reduce memory usage and increase the performance of allocation and deallocation of memory
Using an Actor Framework for Scientific Computing: Opportunities and Challenges
Get PDFWe examine the challenges and advantages of using an actor framework for programming and execution of scientific workflows. The following specific topics are studied: implementing workflow semantics and typical workflow patterns in the actor model, parallel and distributed execution of workflow activities using actors, leveraging event sourcing as a novel approach for workflow state persistence and recovery, and applying supervision as a fault tolerance model for workflows. In order to practically validate our research, we have created Scaflow, an Akka-based programming library and workflow execution engine. We study an example workflow implemented in Scaflow, and present experimental measurements of workflow persistence overhead
Parallel Solver of Large Systems of Linear Inequalities Using Fourier-Motzkin Elimination
Get PDFFourier-Motzkin elimination is a computationally expensive but powerful method to solve a system of linear inequalities. These systems arise e.g. in execution order analysis for loop nests or in integer linear programming. This paper focuses on the analysis, design and implementation of a parallel solver for distributed memory for large systems of linear inequalities using the Fourier-Motzkin elimination algorithm. We also measure the speedup of parallel solver and prove that this implementation results in good scalability
Exploiting Fine-Grained Spatial Optimization for Hybrid File System Space
Get PDFOver decades, I/O optimizations implemented in legacy file systems have been concentrated on reducing HDD disk overhead, such as seek time. As SSD (Solid-State Device) is becoming the main storage medium in I/O storage subsystems, file systems integrated with SSD should take a different approach in designing I/O optimizations. This is because SSD deploys the peculiar device characteristics that do not take place in HDD, such as erasure overhead on flash blocks and absence of seek time to positioning data. In this paper, we present HP-hybrid (High Performance-hybrid) file system that provides a single hybrid file system space, by combining HDD and SSD partitions. HP-hybrid targets for optimizing I/O while considering the strength and weakness of two different partitions, to store large-scale amounts of data in a cost-effective way. Especially, HP-hybrid proposes spatial optimizations that are executed in a hierarchical, fine-grained I/O unit, to address the limited SSD storage resources. We conducted several performance experiments to verify the effectiveness of HP-hybrid while comparing to ext2, ext4 and xfs mounted on both SSD and HDD
Three-Parametric Cubic Interpolation for Estimating the Fundamental Frequency of the Speech Signal
Get PDFIn this paper, we propose a three-parametric convolution kernel which is based on the one-parameter Keys kernel. The first part of the paper describes the structure of the three-parameter convolution kernel. Then, a certain analytical expression for finding the position of the maximum of the reconstructed function is given. The second part presents an algorithm for estimating the fundamental frequency of the speech signal processing in the frequency domain using Picking Picks methods and parametric cubic convolution. Furthermore, the results of experiments give the estimated fundamental frequency of speech and sinusoidal signals in order to select the optimal values of the parameters of the proposed convolution kernel. The results of the fundamental frequency estimation according to the mean square error are given by tables and graphics. Consequently, it is used as a basis for a comparative analysis. The analysis derived the optimal parameters of the kernel and the window function that generates the least MSE. Results showed a higher efficiency in comparison to two or three-parameter convolution kernel
Classic and Agent-Based Evolutionary Heuristics for Shape Optimization of Rotating Discs
Get PDFThe article presents a metaheuristic solution for the problem of shape optimization of a rotating annular disc. Such discs are important structural components of e.g. jet engines, steam turbines or disc brakes. The design goal is to find the disc shape that would ensure its maximal carrying capacity (corresponding to the speed of rotation), which is a variational problem with the objective functional defined by L-infinity norm. Such a definition makes the problem impossible to solve using analytical methods so utilization of metaheuristics is necessary. We present different algorithms to solve the problem starting with a classic evolutionary one, followed by agent-based and hybrid agent-based memetic algorithms, which are the main focus of this paper. The reason for this is that agent-based computing systems proved to be versatile as an optimization technique being especially efficient for the problems with complex fitness functions. The obtained experimental results encourage further application of such an approach to similar engineering problems
Evolution of Reactive Streams API for Context-Aware Mobile Applications
Get PDFThis article describes the role of reactive streams concept as a core communication pattern in mobile-first applications and proposes directions for evolution of its classic API to better match mobile application requirements. By designing the selected examples of mobile applications, the authors evaluate the Reactive Streams API which is an increasingly accepted standard for asynchronous communication with back-pressure. This design is then assessed with regard to solution expressiveness and the ability to satisfy functional and non-functional requirements of the stated problems. It is observed that the used API does not allow for a context propagation from a mobile subscriber to a publisher so that the streamed data can be well adjusted to the variable reception context of a given mobile device. To address this issues, a context-aware variant of this API is proposed and it is demonstrated and discussed by presenting an alternative application design
Effective Computation Resilience in High Performance and Distributed Environments
Get PDFThe work described in this paper aims at effective computation resilience for complex simulations in high performance and distributed environments. Computation resilience is a complicated and delicate area; it deals with many types of simulation cores, many types of data on various input levels and also with many types of end-users, which have different requirements and expectations. Predictions about system and computation behaviors must be done based on deep knowledge about underlying infrastructures, and simulations' mathematical and realization backgrounds. Our conceptual framework is intended to allow independent collaborations between domain experts as end-users and providers of the computational power by taking on all of the deployment troubles arising within a given computing environment. The goal of our work is to provide a generalized approach for effective scalable usage of the computing power and to help domain-experts, so that they could concentrate more intensive on their domain solutions without the need of investing efforts in learning and adapting to the new IT backbone technologies
Agent-Based Model of the Spectrum Auctions with Sensing Imperfections in Dynamic Spectrum Access Networks
Get PDFCognitive radio (CR) is the underlying platform for the application of dynamic spectrum access (DSA) networks. Although the auction theory and spectrum trading mechanisms have been discussed in the CR related works, their joint techno-economic impact on the efficiency of distributed CR networks has not been researched yet. In this paper we assume heterogeneous primary channels with network availability statistics unknown to each secondary user (SU) terminal. In order to detect the idle primary user (PU) network channels, the SU terminals trigger regularly the spectrum sensing mechanism and make the cooperative decision regarding the channel status at the fusion center. The imperfections of the spectrum mechanism create the possibility of the channel collision, resulting in the existence of the risk (in terms of user collision) in the network. The spectrum trading within SU network is governed by the application of the sealed-bid first-price auction, which takes into account the channel valuation as well as the statistical probability of the risk existence. In order to maximize the long-term payoff, the SU terminals take an advantage of the reinforcement comparison strategy. The results demonstrate that in the investigated model, total revenue and total payoff of the SU operator (auctioneer) and SU terminals (bidders) are characterized by the existence of the global optimum, thus there exists the optimal sensing time guaranteeing the optimum economic factors for both SU operator and SU terminals