Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Influence of grinding operations on surface integrity and chloride induced stress corrosion cracking of stainless steels

Stainless steels were developed in the early 20th century and are used where both the mechanical properties of steels and corrosion resistance are required. There is continuous research to allow stainless steel components to be produced in a more economical way and be used in more harsh environments. A necessary component in this effort is to correlate the service performance with the production processes. The central theme of this thesis is the mechanical grinding process.  This is commonly used for producing stainless steel components, and results in varied surface properties that will strongly affect their service life. The influence of grinding parameters including abrasive grit size, machine power and grinding lubricant were studied for 304L austenitic stainless steel (Paper II) and 2304 duplex stainless steel (Paper I). Surface integrity was proved to vary significantly with different grinding parameters. Abrasive grit size was found to have the largest influence. Surface defects (deep grooves, smearing, adhesive/cold welding chips and indentations), a highly deformed surface layer up to a few microns in thickness and the generation of high level tensile residual stresses in the surface layer along the grinding direction were observed as the main types of damage when grinding stainless steels. A large degree of residual stress anisotropy is interpreted as being due to mechanical effects dominating over thermal effects. The effect of grinding on stress corrosion cracking behaviour of 304L austenitic stainless steel in a chloride environment was also investigated (Paper III). Depending on the surface conditions, the actual loading by four-point bend was found to deviate from the calculated value using the formula according to ASTM G39 by different amounts. Grinding-induced surface tensile residual stress was suggested as the main factor to cause micro-cracks initiation on the ground surfaces. Grinding along the loading direction was proved to increase the susceptibility to chloride-induced SCC, while grinding perpendicular to the loading direction improved SCC resistance. The knowledge obtained from this work can provide a reference for choosing appropriate grinding parameters when fabricating stainless steel components; and can also be used to help understanding the failure mechanism of ground stainless steel components during service.

High-performance parallel systems for data-intensive computing

Thesis (Ph.D.)--University of Washington, 2016-08

Multi-physics modelling of materials processes on high performance parallel computers

Abstract not available

PORBS: A parallel observation-based slicer

Abstract—This paper presents PORBS, a parallelised observation-based slicing tool. The tool itself is written in Java making it platform independent and leverages the build chain of the system being sliced to avoid the need to replicate complex compiler analysis. The target audience of PORBS is software engineers and researchers working with and on tools and techniques for software comprehension, debugging, re-engineering, and maintenance.

A parallel method for solving pentadiagonal systems of linear equations

A new parallel approach for solving a pentadiagonal linear system is presented. The parallel partition method for this system and the TW parallel partition method on a chain of P processors are introduced and discussed. The result of this algorithm is a reduced pentadiagonal linear system of order P \Gamma 2 compared with a system of order 2P \Gamma 2 for the parallel partition method. More importantly the new method involves only half the number of communications startups than the parallel partition method (and other standard parallel methods) and hence is a far more efficient parallel algorithm.

Parallel optimisation algorithms for multilevel mesh partitioning

Abstract not available

A fast parallel hyperspectral coded aperture algorithm for compressive sensing using OpenCL

In this paper, we develop a fast implementation of an hyperspectral coded aperture (HYCA) algorithm on different platforms using OpenCL, an open standard for parallel programing on heterogeneous systems, which includes a wide variety of devices, from dense multicore systems from major manufactures such as Intel or ARM to new accelerators such as graphics processing units (GPUs), field programmable gate arrays (FPGAs), the Intel Xeon Phi and other custom devices. Our proposed implementation of HYCA significantly reduces its computational cost. Our experiments have been conducted using simulated data and reveal considerable acceleration factors. This kind of implementations with the same descriptive language on different architectures are very important in order to really calibrate the possibility of using heterogeneous platforms for efficient hyperspectral imaging processing in real remote sensing missions.

A generic strategy for dynamic load balancing of distributed memory parallel computational mechanics using unstructured meshes

A large class of computational problems are characterised by frequent synchronisation, and computational requirements which change as a function of time. When such a problem is solved on a message passing multiprocessor machine [5], the combination of these characteristics leads to system performance which deteriorate in time. As the communication performance of parallel hardware steadily improves so load balance becomes a dominant factor in obtaining high parallel efficiency. Performance can be improved with periodic redistribution of computational load; however, redistribution can sometimes be very costly. We study the issue of deciding when to invoke a global load re-balancing mechanism. Such a decision policy must actively weigh the costs of remapping against the performance benefits, and should be general enough to apply automatically to a wide range of computations. This paper discusses a generic strategy for Dynamic Load Balancing (DLB) in unstructured mesh computational mechanics applications. The strategy is intended to handle varying levels of load changes throughout the run. The major issues involved in a generic dynamic load balancing scheme will be investigated together with techniques to automate the implementation of a dynamic load balancing mechanism within the Computer Aided Parallelisation Tools (CAPTools) environment, which is a semi-automatic tool for parallelisation of mesh based FORTRAN codes.

A single-code software model for multiphysics analysis-engine on parallel and distributed computers with the PHYSICA toolkit

Abstract not available

Automatic generation of portable multi-dimensionally decomposed parallel structured mesh software

Abstract not available

Communication latency hiding in a parallel conjugate gradient method

Abstract not available

Large scale parallel simulations for the assembly of a flip-chip component to a printed circuit

Abstract not available

Load-balancing for parallel adaptive unstructured grids

A parallel method for the dynamic partitioning of unstructured meshes is outlined. The method includes diffusive load-balancing techniques and an iterative optimisation technique known as relative gain optimisationwhich both balances theworkload and attempts to minimise the interprocessor communications overhead. It can also optionally include amultilevel strategy. Experiments on a series of adaptively refined meshes indicate that the algorithmprovides partitions of an equivalent or higher quality to static partitioners (which do not reuse the existing partition) and much more rapidly. Perhaps more importantly, the algorithm results in only a small fraction of the amount of data migration compared to the static partitioners.