Supporting Preemptive Task Executions and Memory Copies in GPGPUs

GPGPUs (General Purpose Graphic Processing Units) provide massive computational power. However, applying GPGPU technology to real-time computing is challenging due to the non-preemptive nature of GPGPUs. Especially, a job running in a GPGPU or a data copy between a GPGPU and CPU is non-preemptive. As a result, a high priority job arriving in the middle of a low priority job execution or memory copy suffers from priority inversion. To address the problem, we present a new lightweight approach to supporting preemptive memory copies and job executions in GPGPUs. Moreover, in our approach, a GPGPU job and memory copy between a GPGPU and the hosting CPU are run concurrently to enhance the responsiveness. To show the feasibility of our approach, we have implemented a prototype system for preemptive job executions and data copies in a GPGPU. The experimental results show that our approach can bound the response times in a reliable manner. In addition, the response time of our approach is significantly shorter than those of the unmodified GPGPU runtime system that supports no preemption and an advanced GPGPU model designed to support prioritization and performance isolation via preemptive data copies

Active Queue Management via Event-Driven Feedback Control

Active queue management (AQM) is investigated to avoid incipient congestion in gateways to complement congestion control run by the transport layer protocol such as the TCP. Most existing work on AQM can be categorized as (1) ad-hoc event-driven control and (2) time-driven feedback control approaches based on control theory. Ad hoc event-driven approaches for congestion control, such as RED (random early detection), lack a mathematical model. Thus, it is hard to analyze their dynamics and tune the parameters. Time-driven control theoretic approaches based on solid mathematical models have drawbacks too. As they sample the queue length and run AQM algorithm at every fixed time interval, they may not be adaptive enough to an abrupt load surge. Further, they can be executed unnecessarily often under light loads due to the time-driven nature. To seamlessly integrate the advantages of both event-driven and control-theoretic time-driven approaches, we present an event-driven feedback control approach based on formal control theory. As our approach is based on a mathematical model, its performance is more analyzable and predictable than ad hoc event-driven approaches are. Also, it is more reactive to dynamic load changes due to its event-driven nature. Our simulation results show that our event-driven controller effectively maintains the queue length around the specified set-point. It achieves shorter E2E (end-to-end) delays and smaller E2E delay fluctuations than several existing AQM approaches, which are ad hoc event-driven and based on time-driven control theory, while achieving almost the same E2E delays and E2E delay fluctuations as the two other advanced control theoretic AQM approaches. Further, our AQM algorithm is invoked much less frequently than the tested baseline

Robust fuzzy CPU utilization control for dynamic workloads

In a number of real-time applications such as target tracking, precise workloads are unknown a priori but may dynamically vary, for example, based on the changing number of targets to track. It is important to manage the CPU utilization, via feedback control, to avoid severe overload or underutilization even in the presence of dynamic workloads. However, it is challenge to model a real-time system for feedback control, as computer systems cannot be modeled via physics laws. In this paper, we present a novel closed-loop approach for utilization control based on formal fuzzy logic control theory, which is very effective to support the desired performance in a nonlinear dynamic system without requiring a system model. We mathematically prove the stability of thefuzzy closed-loop system. Further, in a real-time kernel, we implement and evaluate our fuzzy logic utilization controller as well as two existing utilization controllers based on the linear and model predictive control theory for an extensive set of workloads. Our approach supports the specified average utilization set-point, while showing the best transient performance in terms of utilization control among the tested approaches

Comparison of adjacent segment degeneration in patients using cervical cage and disc prosthesis in anterior cervical surgery

Aim: To examine the prevalence of adjacent segment degeneration associated with the use of cages and disc prostheses in patients who underwent cervical disc surgery via an anterior cervical approach. Methods: We retrospectively reviewed the medical records of 60 patients who underwent cervical disc surgery via an anterior cervical approach at our clinic between 2018 and 2023. The patients were divided into two groups based on the type of implant used: those with a cervical cage (Group 1) and those with a cervical disc prosthesis (Group 2). Patients' demographic and clinical details, including age, gender, smoking habits, follow-up durations, and any additional comorbid diseases, were recorded. Radiological evaluations focused on degeneration rates in the segments adjacent to where either the cage or disc prosthesis was implanted. Results: In the study comparing two groups, participants' average ages were 48.9 in Group 1 and 48.1 in Group 2 (p=0.720). Group 1 had a higher proportion of smokers (p=0.052) and more discopathy (p=0.196). In terms of disc degenerations, variations existed but were not statistically significant (p=0.259). Utilizing the Pfirrmann grading, Group 1 had more Grade III degeneration (p=0.088) and a significantly higher presence of ossification or osteophytes (p=0.038). Both groups showed high rates of adjacent segment degeneration, yet Group 1 had notably more proximal degeneration (p=0.012). Stenosis and facet hypertrophy differences were not significant (p=0.417, p=0.071). Follow-up duration averaged around 38 months for both groups (p=0.929). Conclusions: No substantial difference in the overall incidence of adjacent segment degeneration between the two procedures. Nevertheless, further large-scale and long-term studies are essential to draw comprehensive conclusions regarding the optimal surgical intervention for cervical disc ailments

Grex: An Efficient MapReduce Framework for Graphics Processing Units

In this paper, we present a new MapReduce framework, called Grex, designed to leverage general purpose graphics processing units (GPUs) for parallel data processing. Grex provides several new features. First, it supports a parallel split method to tokenize input data of variable sizes, such as words in e-books or URLs in web documents, in parallel using GPU threads. Second, Grex evenly distributes data to map/reduce tasks to avoid data partitioning skews. In addition, Grex provides a new memory management scheme to enhance the performance by exploiting the GPU memory hierarchy. Notably, all these capabilities are supported via careful system design without requiring any locks or atomic operations for thread synchronization. The experimental results show that our system is up to 12.4x and 4.1x faster than two state-of-the-art GPU-based MapReduce frameworks for the tested applications. 1

UNILATERAL ARYTENOIDECTOMY FOR INTRACTABLE ASPIRATION FOLLOWING SUPRACRICOID LARYNGECTOMY: A CASE OF SURGICAL DILEMMA

Supracricoid partial laryngectomy (SCPL) is a procedure in which the functions of the larynx are preserved. Swallowing difficulties is the most common functional impairment following SCPL. It has been suggested that sparing the arytenoid cartilages is beneficial for the rapid recovery of the swallowing function after SCPL. In this case report we present a 67-year-old male who underwent SCPL in 2015, in which both arytenoid cartilages were preserved. Following the procedure, the patient had severe aspiration and swallowing problems. In order to save the patient from total laryngectomy a one sided arytenoidectomy was performed successfully. The patient no longer required his gastrostomy tube afer 3 months

Energy-Efficient Privacy Protection for Smart Home Environments Using Behavioral Semantics

Research on smart environments saturated with ubiquitous computing devices is rapidly advancing while raising serious privacy issues. According to recent studies, privacy concerns significantly hinder widespread adoption of smart home technologies. Previous work has shown that it is possible to infer the activities of daily living within environments equipped with wireless sensors by monitoring radio fingerprints and traffic patterns. Since data encryption cannot prevent privacy invasions exploiting transmission pattern analysis and statistical inference, various methods based on fake data generation for concealing traffic patterns have been studied. In this paper, we describe an energy-efficient, light-weight, low-latency algorithm for creating dummy activities that are semantically similar to the observed phenomena. By using these cloaking activities, the amount of fake data transmissions can be flexibly controlled to support a trade-off between energy efficiency and privacy protection. According to the experiments using real data collected from a smart home environment, our proposed method can extend the lifetime of the network by more than 2× compared to the previous methods in the literature. Furthermore, the activity cloaking method supports low latency transmission of real data while also significantly reducing the accuracy of the wireless snooping attacks

Comparison of drinking milk production with conventional and novel inductive heating in pasteurization in terms of energetic, exergetic, economic and environmental aspects

Scarcity of natural resources and global warming increase the importance of environmental awareness while making an economic decision for any kind of industry. The dairy industry is one of the impactful areas with high labor, water and energy demand is responsible for air pollution among other sectors in the food industry. In this study, drinking milk production was investigated for milk pasteurization system and its & rsquo; utilities such as steam, air, and water were studied in terms of energetic, exergetic, economic, and environmental aspects. A novel system including inductive heating (IMP) was proposed in this study with the aim of improving energy and exergy efficiencies and reducing environmental impacts. Each system was selected providing a temperature profile for high-temperature short time (HTST) for processing drinking milk. It was found that a novel design could be performed for 10 ton.h-1 milk with 44.35% less energy and less 53.27% exergy input compared to conventional application. In terms of processing cost, just replacing the heating process help reducing expenditure 3.38 EUR to 2.88 EUR per m3 milk. Apart from thermodynamic and economic performance, simplified Life Cycle Assessment (LCA) results showed that the IMP system generated smaller global warming potential (41%) and ozone layer depletion (51%) impact per m3 milk comparing the conventional system

Self-Configuring Indoor Localization Based on Low-Cost Ultrasonic Range Sensors

In smart environments, target tracking is an essential service used by numerous applications from activity recognition to personalized infotaintment. The target tracking relies on sensors with known locations to estimate and keep track of the path taken by the target, and hence, it is crucial to have an accurate map of such sensors. However, the need for manually entering their locations after deployment and expecting them to remain fixed, significantly limits the usability of target tracking. To remedy this drawback, we present a self-configuring and device-free localization protocol based on genetic algorithms that autonomously identifies the geographic topology of a network of ultrasonic range sensors as well as automatically detects any change in the established network structure in less than a minute and generates a new map within seconds. The proposed protocol significantly reduces hardware and deployment costs thanks to the use of low-cost off-the-shelf sensors with no manual configuration. Experiments on two real testbeds of different sizes show that the proposed protocol achieves an error of 7.16~17.53 cm in topology mapping, while also tracking a mobile target with an average error of 11.71~18.43 cm and detecting displacements of 1.41~3.16 m in approximately 30 s