In response to the issue of adapting to the dynamic characteristics of distributed photovoltaics and their impact on energy metering, this article first simulates and analyzes the harmonic and voltage fluctuations cau...
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Heterogeneous systems, consisting of CPUs and GPUs, offer the capability to address the demands of compute- and data-intensive applications. However, programming such systems is challenging, requiring knowledge of var...
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ISBN:
(纸本)9783031506833;9783031506840
Heterogeneous systems, consisting of CPUs and GPUs, offer the capability to address the demands of compute- and data-intensive applications. However, programming such systems is challenging, requiring knowledge of various parallel programming frameworks. This paper introduces COMPAR, a component-based parallel programming framework that enables the exposure and selection of multiple implementation variants of components at runtime. The framework leverages compiler directive-based language extensions to annotate the source code and generate the necessary glue code for the StarPU runtime system. COMPAR provides a unified view of implementation variants and allows for intelligent selection based on runtime context. Our evaluation demonstrates the effectiveness of COMPAR through benchmark applications. The proposed approach simplifies heterogeneous parallel programming and promotes code reuse while achieving optimal performance.
Performing machine learning inference at the network edge, named Edge Inference, showing benefits like low latency, reduced data traffic, and improved user privacy, has attracted massive attention. computing Power Net...
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The energy supply framework has transformed over the recent time from tradition to a more flexible energy topology. This has resulted in the introduction of using distributed generation technologies to improve the sus...
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ISBN:
(纸本)9798350320886
The energy supply framework has transformed over the recent time from tradition to a more flexible energy topology. This has resulted in the introduction of using distributed generation technologies to improve the sustainability of energy supply. However, the introduction of distributed generation for grid-integration has technical disadvantages, such as increase in power and voltage losses. In this paper, a technique based on discrete wavelet transform (DWT) and the genetic algorithm ( GA) is proposed to determine the optimal location and size of the DGs to be connected into the grid for power loss minimisation and voltage improvement. The technique is tested using the 33 and 69 IEEE test bus system. The results obtained show that the power losses are significantly reduced with an increase in the voltage profile.
In demanding environments like space, avionics or robotics, computing systems face challenges affecting their lifetime and reliability. Traditional approaches like static hardware redundancy prove ineffective for mode...
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ISBN:
(纸本)9798350364613;9798350364606
In demanding environments like space, avionics or robotics, computing systems face challenges affecting their lifetime and reliability. Traditional approaches like static hardware redundancy prove ineffective for modern, complex systems. This work presents an overview of self-aware, reliable, and reconfigurable computing systems leveraging Field Programmable Gate Arrays (FPGAs). Despite increasing application demands, FPGA resources remain limited, posing challenges in implementing static redundancy alongside high performance and energy efficiency. Addressing these challenges requires innovative resilience concepts, emphasizing adaptability, reliability, and energy optimization. This paper surveys existing literature and identifies open challenges in achieving resilient computing systems for demanding applications.
The charging of electric vehicles (EVs) via common DC bus charging infrastructure based on hybrid renewable energy sources such as solar photovoltaic (PV) and fuel cell is presented here. The requisite to incorporate ...
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The charging of electric vehicles (EVs) via common DC bus charging infrastructure based on hybrid renewable energy sources such as solar photovoltaic (PV) and fuel cell is presented here. The requisite to incorporate renewable energy based distributed energy resources (DERs) is attributed to the escalating concern for decarbonisation with improved power quality requirements. Furthermore, the bidirectional flow of power enables the charging/discharging of EVs during the grid presence/absence modes of operation. In addition, the utilization of common DC bus charging mechanism for EVs, facilitates fast charging capability at higher voltage levels. The satisfactory operation during the grid availability/unavailability is attained through the current and voltage based control mechanisms, along with the seamless transition capability via switching (STS-1/0) of the static transfer switches. Furthermore, in compliance with the IEEE standards, the power quality (PQ) improvement is obtained with the utilization of an adaptive comb-filter based current control during the grid-tied mode of operation. The need for improving PQ, stems from the fact that an uninterrupted supply is essential to the critical loads along with an improved power quality. Thus, for validation and corroboration of the system behavior, its performance is authenticated during weak grid conditions, in conjunction with grid connected/islanded modes of operation.
Inference of Large Language Models (LLMs) across computer clusters has become a focal point of research in recent times, with many acceleration techniques taking inspiration from CPU speculative execution. These techn...
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ISBN:
(数字)9798350352917
ISBN:
(纸本)9798350352924;9798350352917
Inference of Large Language Models (LLMs) across computer clusters has become a focal point of research in recent times, with many acceleration techniques taking inspiration from CPU speculative execution. These techniques reduce bottlenecks associated with memory bandwidth, but also increase end-to-end latency per inference run, requiring high speculation acceptance rates to improve performance. Combined with a variable rate of acceptance across tasks, speculative inference techniques can result in reduced performance. Additionally, pipeline-parallel designs require many user requests to maintain maximum utilization. As a remedy, we propose PipeInfer, a pipelined speculative acceleration technique to reduce inter-token latency and improve system utilization for single-request scenarios while also improving tolerance to low speculation acceptance rates and low-bandwidth interconnects. PipeInfer exhibits up to a 2.15x improvement in generation speed over standard speculative inference. PipeInfer achieves its improvement through Continuous Asynchronous Speculation and Early Inference Cancellation, the former improving latency and generation speed by running single-token inference simultaneously with several speculative runs, while the latter improves speed and latency by skipping the computation of invalidated runs, even in the middle of inference.
This paper presents an impedance-based non-iterative fault location algorithm for a two-terminal line considering unsynchronized measurements to account for the loss of Global Positioning System (GPS) signal. Based on...
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This paper presents an impedance-based non-iterative fault location algorithm for a two-terminal line considering unsynchronized measurements to account for the loss of Global Positioning System (GPS) signal. Based on the availability of pre-fault signals two algorithms are proposed, one using pre-fault data and the other without using pre-fault data. The algorithms are formulated by using fundamental frequency phasor based decoupled modal components of the measured signals at both ends of the line while considering distributed line model. Application of decoupled modal components with distributed model enhances the accuracy of the presented algorithms in both transposed and untransposed configuration of the line. The proposed algorithms have been tested and analyzed with different fault conditions simulated in EMTP-RV platform. Comparative analysis with existing methods is also presented to establish prominent features of the proposed methods. The algorithms have also been tested with practical data of Power grid Corporation of India Limited (PGCIL) and the test result validates the accuracy of the developed fault location algorithms.
Microgrids are low-voltage distribution network which comprise of controllable loads and distributed energy resources (DERs) that can be used in an isolated or grid-connected mode. The microgrid energy management syst...
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Medical Image AI Systems can assist doctors in making diagnoses, thereby improving diagnostic accuracy. These systems are now widely used in hospitals. However, current AI diagnostic methods typically rely on various ...
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