The graphics processing unit (GPU) plays a crucial role in boosting application performance and enhancing computational tasks. Thanks to its parallel architecture and energy efficiency, the GPU has become essential in many computing scenarios. On the...
Driven by the emergence of Graphics Processing Units (GPUs), the solution of increasingly large and intricate numerical problems has become feasible. Yet, the integration of GPUs into Computational Fluid Dynamics (CFD) codes still presents a signific...
In this work, we examine the performance, energy efficiency, and usability when using Python for developing high-performance computing codes running on the graphics processing unit (GPU). We investigate the portability of performance and energy effic...
Graphics processing units (GPUs) are extensively used as accelerators across multiple application domains, ranging from general purpose applications to neural networks, and cryptocurrency mining. The initial utilization paradigm for GPUs was one appl...
The increasing incorporation of Graphics Processing Units (GPUs) as accelerators has been one of the forefront High Performance Computing (HPC) trends and provides unprecedented performance; however, the prevalent adoption of the Single-Program Multi...
Large numbers of small tensor kernels are executed by GPUs in modern deep learning frameworks, where total performance is frequently constrained by memory bandwidth and kernel launch overheads. Systems such as TensorFlow XLA, PyTorch JIT, and cuDNN o...
Unified memory allows a central processing unit (CPU) and a graphics processing unit (GPU) to share data, simplifying the development of applications that use both processors. However, a shared memory interface does not eliminate the performance effe...
12 November 2026
The increasing complexity of Internet of Things (IoT) environments necessitates efficient and reliable anomaly detection. This study experimentally evaluates established tree-based machine-learning models instead of proposing a new detection algorith...
This study aims to collect GPU rendering programs and analyze their characteristics to construct a benchmark dataset that reflects the characteristics of GPU rendering programs, providing a reference basis for designing the next generation of graphic...
This paper presents software advances to easily exploit computer architectures consisting of a multi-core CPU and CPU+GPU to accelerate diverse types of high-performance computing (HPC) applications using a single code implementation. The paper descr...
Limited by the computational performance limits of the CPU(Central Processing Unit), the traditional Spark architecture struggles to achieve high throughput and low latency under the dual pressure of a large data scale and real-time requirements in c...
Efficiently simulating solid mechanics is vital across various engineering applications. As constitutive models grow more complex and simulations scale up in size, harnessing the capabilities of modern computer architectures has become essential for...
Molecular docking is widely used in computed drug discovery and biological target identification, but getting fast results can be tedious and often requires supercomputing solutions. AMIDE stands for AutoMated Inverse Docking Engine. It was initially...
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...
Large language models (LLMs) commonly employ key–value (KV) caching to avoid recomputing previous attention states during autoregressive inference. However, its measured performance benefit depends on workload characteristics and the memory env...
This paper aims to develop a low-cost, high-performance and high-reliability computing system to process large-scale data using common data mining algorithms in the Internet of Things (IoT) computing environment. Considering the characteristics of Io...
Using artificial intelligence tools to evaluate financial derivatives has become increasingly popular. PSO (particle swarm optimization) is one such tool. We present a comprehensive study of PSO for pricing American options on GPUs using OpenCL. PSO...
Graphics processing units (GPUs) have delivered a remarkable performance for a variety of high performance computing (HPC) applications through massive parallelism. One such application is sparse matrix-vector (SpMV) computations, which is central to...
The exponential growth of AI applications has intensified the demand for efficient inference hardware capable of delivering low-latency, high-throughput, and energy-efficient performance. This study presents a systematic, empirical comparison of GPU-...
Energy optimization is an increasingly important aspect of today’s high-performance computing applications. In particular, dynamic voltage and frequency scaling (DVFS) has become a widely adopted solution to balance performance and energy consu...
Eye tracking is a well-established tool that is often utilised in research. There are currently many different types of eye trackers available, but they are either expensive, or provide a relatively low sampling frequency. The focus of this paper was...
Methods of increasing complexity are currently being proposed for ultrasound (US) echographic signal processing. Graphics Processing Unit (GPU) resources allowing massive exploitation of parallel computing are ideal candidates for these tasks. Many h...
This study presents a comprehensive performance evaluation of field-programmable gate array (FPGA), graphics processing unit (GPU), and central processing unit (CPU) platforms for implementing finite impulse response (FIR) filters in semiconductor-ba...
With the increasing emphasis on energy-efficient computing, edge devices accelerated by graphics processing units (GPUs) are gaining attention for their potential in scientific workloads. These platforms support compute-intensive simulations under st...
Enterprises increasingly run GPU-bound workloads such as Large Language Model (LLM) inference inside virtualized infrastructure, yet practitioners have little systematic guidance on how the choice of virtualization platform affects GPU passthrough in...
Currently, many of the leading supercomputers are equipped with GPUs from manufacturers such as NVIDIA, AMD, or Intel, which provide substantial parallelism and high throughput. It is common for a single compute node to host multiple GPUs (typically...
This study addresses the growing demand for scalable data encryption by evaluating the performance of AES (Advanced Encryption Standard) encryption and decryption using CBC (Cipher Block Chaining) and CTR (Counter Mode) modes across various CPU (Cent...
In remote procedure call (RPC)-based graphic processing unit (GPU) virtualization environments, GPU tasks requested by multiple-user virtual machines (VMs) are delivered to the VM owning the GPU and are processed in a multi-process form. However, bec...
The ability to automate machine translation has various applications in international commerce, medicine, travel, education, and text digitization. Due to the different grammar and lack of clear word boundaries in Chinese, it is challenging to conduc...
In this paper we show how to efficiently implement parallel discrete simulations on multicore and GPU architectures through a real example of an application: a cellular automata model of laser dynamics. We describe the techniques employed to build an...
The primary function of multimedia systems is to seamlessly transform and display content to users while maintaining the perception of acceptable quality. For images and videos, perceptual quality assessment algorithms play an important role in deter...
Performance analysis tools allow application developers to identify and characterize the inefficiencies that cause performance degradation in their codes, allowing for application optimizations. Due to the increasing interest in the High Performance...
Quantitative kinetic parameters derived from dynamic contrast-enhanced (DCE) data are dependent on signal measurement quality and choice of pharmacokinetic model. However, the fundamental optimization analysis method is equally important and its impa...
High-resolution spectrum estimation has continually attracted great attention in spectrum reconstruction based on Fourier transform imaging spectroscopy (FTIS). In this paper, a parallel solution for interference data processing using high-resolution...
This paper examines the performance of two popular GPU programming platforms, Numba and CuPy, for Monte Carlo radiation transport calculations. We conducted tests involving random number generation and one-dimensional Monte Carlo radiation transport...
We present SimDSL, a domain-specific language (DSL) for executing large-scale simulations on the GPU using an Entity Component System (ECS) architecture. Systems written in SimDSL are analyzed, lowered into an intermediate representation, and compile...
Rapid data processing is crucial for distributed optical fiber vibration sensing systems based on a phase-sensitive optical time domain reflectometer (Φ-OTDR) due to the huge amount of continuously refreshed sensing data. The vibration sensing pr...
Time–frequency analysis of EEG data is a key step in exploring the internal activities of the human brain. Studying oscillations is an important part of the analysis, as they are thought to provide the underlying mechanism for communication bet...
Coupled sewer–surface flood simulations are computationally demanding. We evaluated twelve surface-flow and exchange-discharge precision combinations in a graphics processing unit (GPU)-accelerated urban flood model for Jinju, Korea, using rain...
As a foundation for numerical solvers in computational electromagnetics, particularly for multiphysics and electromagnetic compatibility applications, Jefimenko’s equations offer a generalized solution to Maxwell’s equations, enabling the...
Heterogeneous architectures consisting of both central processing units and graphics processing units are common in contemporary computer systems. For that reason, several programming models have been developed to exploit available parallelism, such...
High-Performance Computing (HPC) has become essential for training medium- and large-scale Artificial Intelligence (AI) models, yet two bottlenecks remain under-exploited: the semantic coherence of training data and the interaction between distribute...
Deep learning models are increasingly used for time-series applications; however, they introduce significant computational challenges, particularly when handling the largest workload datasets. Long Short-Term Memory (LSTM) networks are widely used in...
The rapid integration of Artificial Intelligence (AI) into higher education is creating increasingly demanding computational requirements for teaching, research, administration, and institutional services. At the same time, High-Performance Computing...
In this paper, we consider the finite difference approximation for a one-dimensional mathematical model of heat conduction in a three-layered solid with interfacial conditions for temperature and heat flux between the layers. The finite difference sc...
In real applications, massive data with graph structures are often incomplete due to various restrictions. Therefore, graph data imputation algorithms have been widely used in the fields of social networks, sensor networks, and MRI to solve the graph...
Numerical models are useful tools to analyze water quality by computing the concentration of physical, chemical and biological parameters. The present work introduces a two-dimensional depth-averaged model that computes the most relevant and frequent...
Power consumption is a significant challenge in the sustainability of computational science. The growing energy demands of increasingly complex simulations and algorithms lead to substantial resource use, which conflicts with global sustainability go...
To simulate flood processes at the basin level, the GPU-based High-Performance Integrated Hydrodynamic Modelling System (HiPIMS) is gaining interest as computational capability increases. However, the difficulty of coping with rainfall input to HiPIM...
This short review shows how innovative processing units—including graphical processing units (GPUs)—are used in high-performance computing (HPC) in meteorology, introduces current scientific studies relevant to HPC, and discusses the late...
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