In order to accelerate the execution of streaming applications on multi-core systems, this article studies the scheduling problem of synchronous data flow graphs (SDFG) on homogeneous multi-core systems. To describe the data flow computation process,...
Heterogeneous multi-core systems (HMCSs) typically face a dilemma: heuristics (e.g., Linux CFS) are fast but blind to global constraints, while meta-heuristics (e.g., GAs) are globally optimal but too slow for real-time OS interaction. To bridge this...
This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system f...
Conventional 2-level cache architecture is not efficient in mobile systems when small programs that do not require the large L2 cache run. Bypassing the L2 cache for those small programs has two benefits. When only a single program runs, bypassing th...
Dynamic voltage and frequency scaling (DVFS) is a well-known method for saving energy consumption. Several DVFS studies have applied learning-based methods to implement the DVFS prediction model instead of complicated mathematical models. This paper...
Contemporary embedded systems may execute multiple applications, potentially concurrently on heterogeneous platforms, with different system workloads (CPU- or memory-intensive or both) leading to different power signatures. This makes finding the mos...
Recently, computing platforms have been being configured on a large scale to satisfy the diverse requirements of emerging applications like big data and graph processing, neural network, speech recognition and so on. In these computing platforms, eac...
Embedded systems are the best solution to achieve high-performance edge terminal computing tasks. With the rapid increase in the amount of data generated by edge devices, it is imperative to implement intelligent algorithms with large amounts of data...
Today’s mobile processors generally have multiple cores and sufficient hardware resources to support AI-enabled software operation. However, very few AI applications make full use of the computing performance of mobile multiprocessors. This is becaus...
With the sharp rise of functionalities and connectivities in multi-core embedded systems, these systems have become notably vulnerable to security attacks. Conventional software security mechanisms fail to deliver full safety and also affect the syst...
This paper proposes a novel event-driven architecture for enhancing edge-based vehicular systems within smart transportation. Leveraging the inherent real-time, scalable, and fault-tolerant nature of the Elixir language, we present an innovative arch...
Accurately evaluating multi-core embedded systems remains a major challenge, as existing benchmarking methods and tools fail to reproduce realistic workloads with inter-core contentions. This study introduces a benchmark framework for Linux-based emb...
This paper proposes algorithms for optimization of the Remote Core Locking (RCL) synchronization method in multithreaded programs. We propose an algorithm for the initialization of RCL-locks and an algorithm for thread affinity optimization. The algo...
With the widespread application of GNSS, the delicate handling of biases among different systems and different frequencies is of critical importance, wherein the inter-frequency clock biases (IFCBs) and observable-specific signal biases (OSBs) should...
In recent years, the continuous development of artificial intelligence has largely been driven by algorithms and computing power. This paper mainly discusses the training and inference methods of artificial intelligence from the perspective of comput...
As technologies like Artificial Intelligence, Blockchain, Virtual Reality, etc., are advancing, there is a high requirement for High-Performance Computers and multi-core processors to find many applications in today’s Cyber–Physical World...
Multi-core processors have become widespread computing engines for recent embedded real-time systems. Efficient task partitioning plays a significant role in real-time computing for achieving higher performance alongside sustaining system correctness...
Securing multimedia data on disk drives is a major concern because of their rapidly increasing volumes over time, as well as the prevalence of security and privacy problems. Existing cryptographic schemes have high computational costs and slow respon...
This work evaluates the computing performance of finite element analysis in structural mechanics using modern multi-GPU systems. We can avoid the usual memory limitations when using one GPU device for many-core computing using multiple GPUs for scien...
Accurate detection is still a challenge in machine learning (ML) for Alzheimer’s disease (AD). Class imbalance in imbalanced AD data is another big challenge for machine-learning algorithms working under the assumption that the data are evenly...
Space-based target surveillance is important for aerospace safety. However, with the increasing complexity of the space environment, the stellar target and strong noise interference pose difficulties for space target detection. Simultaneously, it is...
Soft error is a key challenge in computer systems. Without soft error mitigation, control flow error (CFE) can lead to system crash. Signature-based CFE monitoring scheme is a representative technique for detecting CFEs during runtime. However, most...
Solving polynomial equations inevitably faces many severe challenges, such as easily occupying storage space and demanding prohibitively expensive computation resources. There has been considerable interest in exploiting the sparsity to improve compu...
In the study of dynamic systems, bifurcation diagrams are a very popular graphical tool for studying stability and nonlinear changes in behavior. They are instrumental in analyzing the system’s response to parameter changes. These diagrams show...
Cloud computing is a new information technology trend that moves computing and data away from desktops and portable PCs into large data centers. The basic principle of cloud computing is to deliver applications as services over the Internet as well a...
In current systems-on-chip (SoCs) designs, processing elements, i.e., intellectual property (IP) cores, may come from different providers, and executable code may have varying levels of trust, all executing on the same compute platform and sharing re...
This paper investigates the feasibility of a backend design for real-time, multiple-channel processing digital phased array system, particularly for high-performance embedded computing platforms constructed of general purpose digital signal processor...
There has been a trend towards using multicore platforms for real-time embedded systems due to their high computing performance. In the scheduling of a multicore hard real-time system, there are interference delays due to contention of shared hardwar...
Today’s embedded systems often operate computer-vision applications, and are associated with timing and power constraints. Since it is not simple to capture the symmetry between the application and the model, the model-based design approach is...
To address the limitations of traditional analytical models in characterising multi-core coupling effects and the excessive computational cost of finite element simulations, this paper presents a high-precision analytical model for a novel T-II compo...
The number of processing elements per solution is growing. From embedded devices now employing (often heterogeneous) multi-core processors, across many-core scientific computing platforms, to distributed systems comprising thousands of interconnected...
Power flow analysis is critical for power systems due to the development of multiple energy supplies. For safety, stability, and real-time response in grid operation, grid planning, and analysis of power systems, it requires designing high-performanc...
As recent heterogeneous systems comprise multi-core CPUs and multiple GPUs, efficient allocation of multiple data-parallel applications has become a primary goal to achieve both maximum total performance and efficiency. However, the efficient orchest...
In this paper, an event-oriented simulation analysis approach was established for the schedulability analysis of multi-core embedded systems. To the best of our knowledge, this work is the first to introduce an event-oriented simulation strategy into...
Aircraft information service systems, such as airborne information systems, airborne integrated maintenance management systems, and cabin management systems, have greatly improved the ease of use and maintenance of civil aircraft. The current computi...
In the Fog Computer (FC), the process of data is prone to problems such as low data similarity and poor data tolerance. This paper proposes a hierarchical data job scheduling strategy Based on Intelligent Sensor-Cloud in Fog Computer (HDJS). HDJS dyn...
Remote-sensing platforms, such as Unmanned Aerial Vehicles, are characterized by limited power budget and low-bandwidth downlinks. Therefore, handling hyperspectral data in this context can jeopardize the operational time of the system. FPGAs have be...
The work is devoted to developing the parallel algorithms for solving the initial boundary problem for the time-fractional diffusion equation. After applying the finite-difference scheme to approximate the basis equation, the problem is reduced to so...
We present a new approach to searching for Continuous gravitational Waves (CWs) emitted by isolated rotating neutron stars, using the high parallel computing efficiency and computational power of modern Graphic Processing Units (GPUs). Specifically,...
The problem of determining the position of the lidar with optimal accuracy is relevant in various fields of application. This is an important task of robotics that is widely used as a model when planning the route of vehicles, flight control systems,...
Mobile edge computing architecture (MEC) can provide users with low latency services by integrating computing, storage and processing capabilities near users and data sources. As such, there has been intense interest in this topic, especially in sing...
Profiling and parallel computing techniques in a cluster of six embedded systems with multiprocessors are introduced herein to implement a chaotic cryptosystem for digital color images. The proposed encryption method is based on stream encryption usi...
The simulation of realistic systems plays a crucial role in modern sciences. Complex organs such as the brain can be described by mathematical models to reproduce biological behaviors. In the brain, the hippocampus is a critical region for memory and...
Quantitative reliability evaluation is essential for optimizing control policies and maintenance strategies in complex industrial systems. While Reliability Block Diagrams (RBDs) are a natural formalism for modeling these hierarchical systems, modern...
The rapid expansion of the Internet of Medical Things (IoMT) and intelligent assistive technologies has intensified the need for resource-optimized cryptographic hardware to protect sensitive biometric data. Cryptographic hardware performance relies...
In this paper, we examine deflation-based algebraic multigrid methods for solving large systems of linear equations. Aggregation of the unknown terms is applied for coarsening, while deflation techniques are proposed for improving the rate of converg...
High-throughput microarrays contain a huge number of genes. Determining the relationships between all these genes is a time-consuming computation. In this paper, the authors provide a parallel algorithm for finding the Pearson’s correlation coe...
This paper is devoted to the development of a parallel algorithm for solving the inverse problem of identifying the space-dependent source term in the two-dimensional fractional diffusion equation. For solving the inverse problem, the regularized ite...
Scheduling computing is a well-studied area focused on improving task execution by reducing processing time and increasing system efficiency. Divisible Load Theory (DLT) provides a structured analytical framework for distributing partitionable comput...
This article presents a dataset and experimental evaluation of a parallelized variant of Junker’s QuickXPlain algorithm, designed to efficiently compute minimal conflict sets in constraint-based diagnosis tasks. The dataset includes performance...
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