Main-memory near-data acceleration with concurrent host access

Processing-in-memory is attractive for applications that exhibit low temporal locality and low arithmetic intensity. By bringing computation close to data, PIMs utilize proximity to overcome the bandwidth bottleneck of a main memory bus. Unlike discrete accelerators, such as GPUs, PIMs can potentially accelerate within main memory so that the overhead for loading data from main memory to processor/accelerator memories can be saved. There are a set of challenges for realizing processing in the main memory of conventional CPUs, including: (1) mitigating contention/interference between the CPU and PIM as both access the same shared memory devices, and (2) sharing the same address space between the CPU and PIM for efficient in-place acceleration. In this dissertation, I present solutions to these challenges that achieve high PIM performance without significantly affecting CPU performance (up to 2.4\% degradation). Another major contribution is that I identify killer applications that cannot be effectively accelerated with discrete accelerators. I introduce two compelling use cases in the AI domain for the main-memory accelerators where the unique advantage of a PIM over other acceleration schemes can be leveraged.Electrical and Computer Engineerin

A Distributed ADMM Approach to Non-Myopic Path Planning for Multi-Target Tracking

This paper investigates non-myopic path planning of mobile sensors for multi-target tracking. Such problem has posed a high computational complexity issue and/or the necessity of high-level decision making. Existing works tackle these issues by heuristically assigning targets to each sensing agent and solving the split problem for each agent. However, such heuristic methods reduce the target estimation performance in the absence of considering the changes of target state estimation along time. In this work, we detour the task-assignment problem by reformulating the general non-myopic planning problem to a distributed optimization problem with respect to targets. By combining alternating direction method of multipliers (ADMM) and local trajectory optimization method, we solve the problem and induce consensus (i.e., high-level decisions) automatically among the targets. In addition, we propose a modified receding-horizon control (RHC) scheme and edge-cutting method for efficient real-time operation. The proposed algorithm is validated through simulations in various scenarios.Comment: Copyright 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work

A study on the differences in the perceived importance of jet fighter performance improvement factors

The rapid advancement in software-based technology has significantly shortened product life cycles, leading to the proliferation of new products. However, the high initial investment makes it practically impossible for armed forces to rapidly replace existing weapons systems with new ones due to technological obsolescence. A more realistic alternative is to focus on performance improvements (or weapon upgrades) in existing systems. The challenge lies in making the right upgrades with the right technology at the right cost and time given the limited defense budget. Unfortunately, weapons upgrade decisions have mostly been based on costs and politically considered budget allocations to different branches of the armed forces rather than by considering a comprehensive range of decision factors. In light of the escalating national security threats, it is necessary to maximize the cost-effectiveness of weapons upgrade projects and effectively address rising national security challenges. The objective of this study is to develop a performance improvement Decision Index that quantifies the opinions of field-operating experts. Field experts are believed to possess the necessary expertise to select the appropriate fighter types, technologies, and upgrade timings, making it beneficial to factor in their opinions to determine what, how, and when to upgrade. Specifically, this study aims to establish weighted values for major decision factors regarding fighter performance improvement programs in the Republic of Korea Air Force. To achieve this, we collected survey data from 134 active-duty pilots and maintenance, operations, and repair (MRO) personnel from major fighter wings of the Republic of Korea Air Force and analyzed the data using the Fuzzy-AHP (Analytical Hierarchy Process). The analysis results indicate that the highest weighted value is given to the “relative (fighter) performance”against hostile nations, followed by “operating rate,” “durability,” “performance improvement cycle,” and “budget.” Furthermore, this study identified perceptual differences among field experts—particularly between pilots and MRO personnel—regarding the importance of relative performance, budget, performance improvement intervals, and operating rates of different fighter types. The proposed performance improvement index aims to provide a quantitative tool that incorporates field experts’ opinions into the decision-making process to upgrade weapons, facilitating balanced decisions and departing from a policymaker-centered approach. This balanced approach to weapons upgrade decisions will contribute to maximizing cost-effectiveness and, eventually, enhancing combat readiness

Least squares estimation of acoustic reflection coefficient

The work presented in this thesis develops further the two-microphone transfer function method used for the measurement of acoustic reflection coefficient of a porous material in an impedance tube.  With the use of a least squares solution, the measurement of the transfer functions between multiple microphones can be used to produce an optimal estimation of reflection coefficient.  The advantage of using this technique is to extend the frequency range of broadband measurements.  The limitations of using the two-microphone transfer function method are analysed in terms of the microphone separations that dictate the upper frequency limit of measurements and it is shown how the measurement of multiple transfer functions can assist in extending the frequency range.  Least squares estimation with multiple transfer functions is also applied to free-field measurements based on an image source model of the reflection process.  The use of an image source model is found to give good results when used with the least squares solution for measurement of reflection coefficient at normal incidence.  Results at oblique incidence seem more difficult to measure accurately in practice because of the precision required in locating microphones.  The use of a reflection model, that is associated with plane wave decomposition, is also introduced although this needs a numerical approach in order to enable the application of least squares estimation.  The numerical process is demonstrated in a simulation that suggests this technique may ultimately be of practical use.</p

Least squares estimation of acoustic reflection coeffficient

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Development of village appraisal system for constructing ecovillages

University of Tokyo (東京大学

An Analysis of Difference in Preventive Health Behaviors for COVID-19 by Personality Characteristics in College Athletes

Background: Due to the uniqueness of COVID-19 compared with other infectious diseases, the need for various countermeasures against it should be emphasized, and considering that most athletes are not allowed to wear masks during competitions, stricter preventive health behaviors for COVID-19 are required among these individuals. Therefore, in an attempt to yield data that may be used to increase the engagement in preventive health behaviors for COVID-19 among college athletes, this study investigated the differences in preventive health behaviors for COVID-19 according to personality types. Material and Methods: Based on the Big Five personality theory, the relationship between preventive health behaviors for COVID-19 and personality characteristics was tested. Data were collected from 65 participants (male: n = 53, female: n = 12) through a questionnaire survey. Results: The results showed no differences in preventive health behaviors according to demographic characteristics such as sex, grade, sports type, and career. The highest score for a personality type was for conscientiousness, and those with a higher level of conscientiousness, extraversion, neuroticism, and openness reported higher scores for preventive health behavior for COVID-19. Interestingly, those with low openness also reported higher scores for preventive health behaviors for COVID-19. Conclusions: These results are expected to be used as important information to restrict the spread of COVID-19 and promote preventive health behaviors among college athletes

Physicochemical Characteristics of Meat Analogs Supplemented with Vegetable Oils

This study identified the effect of the type and concentration of vegetable oil on the quality of meat analogs and analyzed the differences in their physiochemical characteristics. Various vegetable oils, such as castor oil, orange oil, palm oil, shortening, and margarine, were added to meat analogs. The meat analog was prepared by adding 10, 20, 30, 40, and 50 g of each vegetable oil based on 100 g of textured vegetable protein. The cooking loss, water content, liquid-holding capacity, texture, and antioxidant content of the meat analogs were assessed, and a sensory evaluation was performed. The meat analog with orange oil had a higher water content than the others, regardless of the amount of added oil, and it had a relatively high liquid-holding capacity. The DPPH(2,2-diphenyl-1-picrylhydrazyl) radical scavenging activity of the meat analog with orange oil was higher than that of the others. The sensory evaluation also showed a decrease in soy odor and an increase in juiciness. Therefore, adding orange oil improves the preference, juiciness, soy odor, and quality of meat analogs. Our results demonstrate that orange oil has positive effects on the productivity of meat analogs and can help to improve meat analog consumption