A Low-Cost System for Quick Measurements on Noise Barriers in Situ

This paper describes the development of a low-cost device for measuring the acoustic intrinsic characteristics of noise barriers. The system is based on the Teensy 4.1 microcontroller combined with a few other components. The measurements are carried out using a vertical linear microphone antenna housing 6 microphones and a lightweight loudspeaker, wireless connected to the main unit. Both the main system unit and the amplified loudspeaker are powered from normal 5 V USB battery packs, which are easily rechargeable and interchangeable. The system measures 6 impulse responses using an MLS signal and performs a series of calculations and frequency analyses to characterize the device under test, following a simplified version of the European standards EN 1793-5 and EN 1793-6 (commonly referred to as the ’Adrienne method’). One measurement takes few minutes, obtaining results comparable to those obtained with the Adrienne method, which requires a more complicated and heavy measuring equipment and is much more expensive and time consuming

Acceleration Techniques for Sparse Recovery Based Plane-wave Decomposition of a Sound Field

Plane-wave decomposition by sparse recovery is a reliable and accurate technique for plane-wave decomposition which can be used for source localization, beamforming, etc. In this work, we introduce techniques to accelerate the plane-wave decomposition by sparse recovery. The method consists of two main algorithms which are spherical Fourier transformation (SFT) and sparse recovery. Comparing the two algorithms, the sparse recovery is the most computationally intensive. We implement the SFT on an FPGA and the sparse recovery on a multithreaded computing platform. Then the multithreaded computing platform could be fully utilized for the sparse recovery. On the other hand, implementing the SFT on an FPGA helps to flexibly integrate the microphones and improve the portability of the microphone array. For implementing the SFT on an FPGA, we develop a scalable FPGA design model that enables the quick design of the SFT architecture on FPGAs. The model considers the number of microphones, the number of SFT channels and the cost of the FPGA and provides the design of a resource optimized and cost-effective FPGA architecture as the output. Then we investigate the performance of the sparse recovery algorithm executed on various multithreaded computing platforms (i.e., chip-multiprocessor, multiprocessor, GPU, manycore). Finally, we investigate the influence of modifying the dictionary size on the computational performance and the accuracy of the sparse recovery algorithms. We introduce novel sparse-recovery techniques which use non-uniform dictionaries to improve the performance of the sparse recovery on a parallel architecture

Phonons and related properties of extended systems from density-functional perturbation theory

This article reviews the current status of lattice-dynamical calculations in crystals, using density-functional perturbation theory, with emphasis on the plane-wave pseudo-potential method. Several specialized topics are treated, including the implementation for metals, the calculation of the response to macroscopic electric fields and their relevance to long wave-length vibrations in polar materials, the response to strain deformations, and higher-order responses. The success of this methodology is demonstrated with a number of applications existing in the literature.Comment: 52 pages, 14 figures, submitted to Review of Modern Physic

Hydrodynamics of Suspensions of Passive and Active Rigid Particles: A Rigid Multiblob Approach

We develop a rigid multiblob method for numerically solving the mobility problem for suspensions of passive and active rigid particles of complex shape in Stokes flow in unconfined, partially confined, and fully confined geometries. As in a number of existing methods, we discretize rigid bodies using a collection of minimally-resolved spherical blobs constrained to move as a rigid body, to arrive at a potentially large linear system of equations for the unknown Lagrange multipliers and rigid-body motions. Here we develop a block-diagonal preconditioner for this linear system and show that a standard Krylov solver converges in a modest number of iterations that is essentially independent of the number of particles. For unbounded suspensions and suspensions sedimented against a single no-slip boundary, we rely on existing analytical expressions for the Rotne-Prager tensor combined with a fast multipole method or a direct summation on a Graphical Processing Unit to obtain an simple yet efficient and scalable implementation. For fully confined domains, such as periodic suspensions or suspensions confined in slit and square channels, we extend a recently-developed rigid-body immersed boundary method to suspensions of freely-moving passive or active rigid particles at zero Reynolds number. We demonstrate that the iterative solver for the coupled fluid and rigid body equations converges in a bounded number of iterations regardless of the system size. We optimize a number of parameters in the iterative solvers and apply our method to a variety of benchmark problems to carefully assess the accuracy of the rigid multiblob approach as a function of the resolution. We also model the dynamics of colloidal particles studied in recent experiments, such as passive boomerangs in a slit channel, as well as a pair of non-Brownian active nanorods sedimented against a wall.Comment: Under revision in CAMCOS, Nov 201

Intensional Cyberforensics

This work focuses on the application of intensional logic to cyberforensic analysis and its benefits and difficulties are compared with the finite-state-automata approach. This work extends the use of the intensional programming paradigm to the modeling and implementation of a cyberforensics investigation process with backtracing of event reconstruction, in which evidence is modeled by multidimensional hierarchical contexts, and proofs or disproofs of claims are undertaken in an eductive manner of evaluation. This approach is a practical, context-aware improvement over the finite state automata (FSA) approach we have seen in previous work. As a base implementation language model, we use in this approach a new dialect of the Lucid programming language, called Forensic Lucid, and we focus on defining hierarchical contexts based on intensional logic for the distributed evaluation of cyberforensic expressions. We also augment the work with credibility factors surrounding digital evidence and witness accounts, which have not been previously modeled. The Forensic Lucid programming language, used for this intensional cyberforensic analysis, formally presented through its syntax and operational semantics. In large part, the language is based on its predecessor and codecessor Lucid dialects, such as GIPL, Indexical Lucid, Lucx, Objective Lucid, and JOOIP bound by the underlying intensional programming paradigm.Comment: 412 pages, 94 figures, 18 tables, 19 algorithms and listings; PhD thesis; v2 corrects some typos and refs; also available on Spectrum at http://spectrum.library.concordia.ca/977460

High performance Java for multi-core systems

[Abstract] The interest in Java within the High Performance Computing (HPC) community has been rising during the last years thanks to its noticeable performance improvements and its productivity features. In a context where the trend to increase the number of cores per processor is leading to the generalization of many-core processors and accelerators, multithreading as an inherent feature of the language makes Java extremely interesting to exploit the performance provided by multi- and manycore architectures. This PhD Thesis presents a thorough analysis of the current state of the art regarding multi- and many-core programming in Java and provides the design, implementation and evaluation of several solutions to enable Java for the many-core era. To achieve this, a shared memory message-passing solution has been implemented to provide shared memory programming with the scalability of distributed memory paradigms, also with the benefits of a portable programming model that allows the developed codes to be run on distributed memory systems. Moreover, representative collective operations, involving computation and communication among different processes or threads, have been optimized, also introducing in Java new features for scalability from the MPI 3.0 specification, namely nonblocking collectives. Regarding the exploitation of many-core architectures, the lack of direct Java support forces to resort to wrappers or higher-level solutions to translate Java code into CUDA or OpenCL. The most relevant among these solutions have been evaluated and thoroughly analyzed in terms of performance and productivity. Guidelines for taking advantage of shared memory environments have been derived during the analysis and development of the proposed solutions, and the main conclusion is that the use of Java for shared memory programming on multi- and many-core systems is not only productive but also can provide high performance competitive results. However, in order to effectively take advantage of the underlying multi- and many-core architectures, the key is the availability of optimized middleware that abstracts multithreading details from the user, like the one proposed in this Thesis, and the optimization of common operations like collective communications