Development of a Quasi-Monte Carlo Method for Thermal Radiation

Radiative heat transfer in participating media is among the most challenging computational engineering problems due to the complex nonlinear, nonlocal nature of radiation transport. Many approximate methods have been developed in order to resolve radiative heat transfer in participating media; but approximate methods, by the nature of their approximations, suffer from various shortcomings both in terms of accuracy and robustness. The only methods that can resolve radiative transfer accurately in all configurations are the statistical Monte Carlo-based methods. While the Monte Carlo (MC) method is the most accurate method for resolving radiative heat transfer, it is also notoriously computationally prohibitive in large-scale simulations. To overcome this computational burden, this study details the development of a quasi-Monte Carlo (QMC) method for thermal radiation in participating media with a focus on combustion-related problems. The QMC method employs a low-discrepancy sequence (LDS) in place of the traditional random number sampling mechanism used in Monte Carlo methods to increase computational efficiency. In order to analyze the performance of the QMC method, a systematic comparison of accuracy and computational expense was performed. The QMC method was validated against formal solutions of radiative heat transfer in several one-dimensional configurations and extended to three practical combustion configurations: a turbulent jet flame, a high-pressure industrial gas turbine, and a high-pressure spray combustion chamber. The results from QMC and traditional Monte Carlo are compared against benchmark solutions for each case. It is shown that accuracy of the predicted radiation field from QMC is comparable to MC at lower computational costs. Three different low-discrepancy sequences – Sobol, Halton, and Niederreiter – were examined as part of this work. Finally, recommendations are made in terms of choice of the sequence and the number of the dimensions of the LDS for combustion-relevant configurations. In conclusion, significant improvements in computational costs and accuracy seen in the QMC method makes it a viable alternative to traditional Monte Carlo methods in high-fidelity simulations

A bibliography on parallel and vector numerical algorithms

This is a bibliography of numerical methods. It also includes a number of other references on machine architecture, programming language, and other topics of interest to scientific computing. Certain conference proceedings and anthologies which have been published in book form are listed also

Measurements and characterization of optical wireless communications through biological tissues

Abstract. Radio frequency (RF) has been predominantly utilized for wireless transmission of data across biological tissues. However, RF communications need to address several challenges like interference, safety, security, and privacy, which often hamper the communications through the tissues. To mitigate these challenges, light-based communication can be exploited, as optical wireless communications have unique advantages in terms of security, interference and safety. In this thesis work, we have utilized near-infrared (NIR) light to investigate the feasibility of optical wireless data transfer through biological tissues. To understand the basics of optical communications through biological tissues (OCBT), fresh meat samples and optical phantoms have been used as models of living biological tissues. An experimental testbed containing a data modulated light source and a photodetector was implemented to carry out different measurements regarding the OCBT concept. We have explored the influence of parameters like transmitted optical power, temperature of the tissue, tissue thickness, and position of the light source on the performance of the light-based through-tissue communication system. Analysis of the measurement data allowed us to compare and characterize the effect of used optical elements for better performance evaluation of the optical communication system. We have successfully transmitted a high-resolution image file through a 3 cm thick pork tissue sample. The maximum transmitted power through the tissue sample during the optical communication was 231.4 mW/cm2, which is well below the limits defined by standard of safety regulation. A data rate of 22 kilobits per second has been achieved with the experimental system. Practical limitations of the current testbed prevented obtaining a higher data throughput. The results indicate a dependence of optical received power with respect to the tissue temperature. Moreover, we found both thickness and compositional differences of the biological tissues have a significant impact on the transmittance rate. This thesis work can be considered as a part of the development of 6G technology. The outcomes of this pilot study are very promising, and in the future, numerous potential applications based on OCBT could be developed, including wireless communications to implanted devices, in-body sensors, smart pills, and others

Application-Specific Number Representation

Reconfigurable devices, such as Field Programmable Gate Arrays (FPGAs), enable application- specific number representations. Well-known number formats include fixed-point, floating- point, logarithmic number system (LNS), and residue number system (RNS). Such different number representations lead to different arithmetic designs and error behaviours, thus produc- ing implementations with different performance, accuracy, and cost. To investigate the design options in number representations, the first part of this thesis presents a platform that enables automated exploration of the number representation design space. The second part of the thesis shows case studies that optimise the designs for area, latency or throughput from the perspective of number representations. Automated design space exploration in the first part addresses the following two major issues: ² Automation requires arithmetic unit generation. This thesis provides optimised arithmetic library generators for logarithmic and residue arithmetic units, which support a wide range of bit widths and achieve significant improvement over previous designs. ² Generation of arithmetic units requires specifying the bit widths for each variable. This thesis describes an automatic bit-width optimisation tool called R-Tool, which combines dynamic and static analysis methods, and supports different number systems (fixed-point, floating-point, and LNS numbers). Putting it all together, the second part explores the effects of application-specific number representation on practical benchmarks, such as radiative Monte Carlo simulation, and seismic imaging computations. Experimental results show that customising the number representations brings benefits to hardware implementations: by selecting a more appropriate number format, we can reduce the area cost by up to 73.5% and improve the throughput by 14.2% to 34.1%; by performing the bit-width optimisation, we can further reduce the area cost by 9.7% to 17.3%. On the performance side, hardware implementations with customised number formats achieve 5 to potentially over 40 times speedup over software implementations

The 1982 NASA/ASEE Summer Faculty Fellowship Program

A NASA/ASEE Summer Faculty Fellowship Research Program was conducted to further the professional knowledge of qualified engineering and science faculty members, to stimulate an exchange of ideas between participants and NASA, to enrich and refresh the research and teaching activities of participants' institutions, and to contribute to the research objectives of the NASA Centers

Exploring Computational Chemistry on Emerging Architectures

Emerging architectures, such as next generation microprocessors, graphics processing units, and Intel MIC cards, are being used with increased popularity in high performance computing. Each of these architectures has advantages over previous generations of architectures including performance, programmability, and power efficiency. With the ever-increasing performance of these architectures, scientific computing applications are able to attack larger, more complicated problems. However, since applications perform differently on each of the architectures, it is difficult to determine the best tool for the job. This dissertation makes the following contributions to computer engineering and computational science. First, this work implements the computational chemistry variational path integral application, QSATS, on various architectures, ranging from microprocessors to GPUs to Intel MICs. Second, this work explores the use of analytical performance modeling to predict the runtime and scalability of the application on the architectures. This allows for a comparison of the architectures when determining which to use for a set of program input parameters. The models presented in this dissertation are accurate within 6%. This work combines novel approaches to this algorithm and exploration of the various architectural features to develop the application to perform at its peak. In addition, this expands the understanding of computational science applications and their implementation on emerging architectures while providing insight into the performance, scalability, and programmer productivity

Uncertainty in Engineering

This open access book provides an introduction to uncertainty quantification in engineering. Starting with preliminaries on Bayesian statistics and Monte Carlo methods, followed by material on imprecise probabilities, it then focuses on reliability theory and simulation methods for complex systems. The final two chapters discuss various aspects of aerospace engineering, considering stochastic model updating from an imprecise Bayesian perspective, and uncertainty quantification for aerospace flight modelling. Written by experts in the subject, and based on lectures given at the Second Training School of the European Research and Training Network UTOPIAE (Uncertainty Treatment and Optimization in Aerospace Engineering), which took place at Durham University (United Kingdom) from 2 to 6 July 2018, the book offers an essential resource for students as well as scientists and practitioners

Accelerating Reconfigurable Financial Computing

This thesis proposes novel approaches to the design, optimisation, and management of reconfigurable computer accelerators for financial computing. There are three contributions. First, we propose novel reconfigurable designs for derivative pricing using both Monte-Carlo and quadrature methods. Such designs involve exploring techniques such as control variate optimisation for Monte-Carlo, and multi-dimensional analysis for quadrature methods. Significant speedups and energy savings are achieved using our Field-Programmable Gate Array (FPGA) designs over both Central Processing Unit (CPU) and Graphical Processing Unit (GPU) designs. Second, we propose a framework for distributing computing tasks on multi-accelerator heterogeneous clusters. In this framework, different computational devices including FPGAs, GPUs and CPUs work collaboratively on the same financial problem based on a dynamic scheduling policy. The trade-off in speed and in energy consumption of different accelerator allocations is investigated. Third, we propose a mixed precision methodology for optimising Monte-Carlo designs, and a reduced precision methodology for optimising quadrature designs. These methodologies enable us to optimise throughput of reconfigurable designs by using datapaths with minimised precision, while maintaining the same accuracy of the results as in the original designs

Architecture and Performance of the Mether Network Shared Memory

Mether is a Network Shared Memory (NSM). It allows applications on autonomous computers connected by a network to share a segment of memory. NSMs offer the attraction of a simple abstraction for shared state, i.e., shared memory. NSMs have a potential performance problem in the cost of remote references, which is typically solved by grouping memory into larger units such as pages, and caching pages. While Mether employs grouping and caching to reduce the average memory reference delay, it also removes the need for many remote references (page faults) by providing a facility with relaxed consistency requirements. Applications ported from a multiprocessor supercomputer with shared memory to a 16-workstation Mether configuration showed a cost/performance advantage of over 300 in favor of the Mether system. While Mether is currently implemented for Sun-3 and Sun-4 systems connected via Ethernet, other characteristics (such as a choice of page sizes and a semaphore-like access mode useful for process synchronization) should suit it to a wide variety of networks. A reimplementation for an alternate configuration employing packet-switched networks is in progress

NASA Tech Briefs, August 2010

Topics covered include: Technology Focus: Mechanical Components; Electronics/Computers; Software; Materials; Mechanics/Machinery; Manufacturing; Bio-Medical; Physical Sciences; Information Sciences; and Books and Reports