FCM Clustering Approach Optimization Using Parallel High-Speed Intel FPGA Technology

Almomany, Abedalmuhdi; Jarrah, Amin; Assaf, Anwar Al

doi:10.1155/2022/8260283

Cited by 11 publications

(7 citation statements)

References 58 publications

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“…This design enables efficient implementation of high-speed sequential synchronous designs, with combinational logic segments assigned to the LUTs and associated flip flops serving as the base memory element. Modern FPGAs further enhance performance by leveraging functional and data parallel methods [14][15][16][17][18]. These methods enable simultaneous execution of problem space and/or data space on different FPGA portions, supported by separately addressable on-chip embedded SRAM memory blocks and hierarchical segmentation within the internal interconnect fabric.…”

Section: Plos Onementioning

confidence: 99%

Accelerating electrostatic particle-in-cell simulation: A novel FPGA-based approach for efficient plasma investigations

Almomany,

Sutcu,

Ibrahim

2024

PLoS ONE

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Particle-in-cell (PIC) simulation serves as a widely employed method for investigating plasma, a prevalent state of matter in the universe. This simulation approach is instrumental in exploring characteristics such as particle acceleration by turbulence and fluid, as well as delving into the properties of plasma at both the kinetic scale and macroscopic processes. However, the simulation itself imposes a significant computational burden. This research proposes a novel implementation approach to address the computationally intensive phase of the electrostatic PIC simulation, specifically the Particle-to-Interpolation phase. This is achieved by utilizing a high-speed Field Programmable Gate Array (FPGA) computation platform. The suggested approach incorporates various optimization techniques and diminishes memory access latency by leveraging the flexibility and performance attributes of the Intel FPGA device. The results obtained from our study highlight the effectiveness of the proposed design, showcasing the capability to execute hundreds of functional operations in each clock cycle. This stands in contrast to the limited operations performed in a general-purpose single-core computation platform (CPU). The suggested hardware approach is also scalable and can be deployed on more advanced FPGAs with higher capabilities, resulting in a significant improvement in performance.

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Section: Plos Onementioning

confidence: 99%

Accelerating electrostatic particle-in-cell simulation: A novel FPGA-based approach for efficient plasma investigations

Almomany,

Sutcu,

Ibrahim

2024

PLoS ONE

Self Cite

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“…Therefore, the program must be written in a way that exploits the features of the existing homogeneous architecture. There are many software libraries that provide the ability to create and manage threads, such as open multi-processing (OpenMP) [30], open computing language (OpenCL) [31][32][33], and Intel threading building blocks (ITBB) [34]. In this proposed study, the OpenCV library tool is used where several optimization techniques are possible; auto-parallelization and auto-vectorization are used to exploit all the capabilities of the heterogeneous multicore CPU-based system.…”

Section: Research Methods Techniques and Proceduresmentioning

confidence: 99%

A New Approach of Combining Optical Mapping Algorithm with Adaptive Kalman Filter to Achieve Fast and Early Detection of Cardiac Arrests: A Parallel Implementation

Jarrah¹,

Almomany²,

Al‐Khafaji³

2022

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This research aims to propose a new approach by combining the Optical Mapping Algorithm (OMA) with the Adaptive Kalman Filter (AKF) to improve the early detection of cardiac arrest. To improve the overall performance of the proposed approach and reduce the execution time significantly, a parallel implementation is suggested using the open-source computer vision (OpenCV) library tool and optimized for heterogeneous multi-core systems. The OpenCV library incorporates many image processing functions that are used to extract the distinctive features of the digital image to indicate the presence or absence of cardiac arrest in order to save the largest possible number of human lives. Experimental results confirm the efficiency of the proposed implementation; as for a loop with a sequence of operations repeated 64 times, the achieved speedup is 5X with an accuracy improvement of 96%. This is due to the exploitation of several optimization techniques, such as pipelining and loop unrolling. The accuracy of dark spot detection of blood vessels by combining the AKF with OMA was improved from 50% to 83.3% compared with the AKF approach alone. Thus, the proposed approach and its parallel implementation are very useful in early cardiac arrest detection to preserve human lives.

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“…The advent of high-level hardware synthesis languages, such as OpenCL, opens a new era in the implementation of custom architectures. Previous work discussing OpenCL as a framework for developing FPGA applications and its benefits includes [ 14 – 16 ].…”

Section: Related Workmentioning

confidence: 99%

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

et al. 2023

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Motion Estimation is one of the main tasks behind any video encoder. It is a computationally costly task; therefore, it is usually delegated to specific or reconfigurable hardware, such as FPGAs. Over the years, multiple FPGA implementations have been developed, mainly using hardware description languages such as Verilog or VHDL. Since programming using hardware description languages is a complex task, it is desirable to use higher-level languages to develop FPGA applications.The aim of this work is to evaluate OpenCL, in terms of expressiveness, as a tool for developing this kind of FPGA applications. To do so, we present and evaluate a parallel implementation of the Block Matching Motion Estimation process using OpenCL for Intel FPGAs, usable and tested on an Intel Stratix 10 FPGA. The implementation efficiently processes Full HD frames completely inside the FPGA. In this work, we show the resource utilization when synthesizing the code on an Intel Stratix 10 FPGA, as well as a performance comparison with multiple CPU implementations with varying levels of optimization and vectorization capabilities. We also compare the proposed OpenCL implementation, in terms of resource utilization and performance, with estimations obtained from an equivalent VHDL implementation.

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FCM Clustering Approach Optimization Using Parallel High-Speed Intel FPGA Technology

Cited by 11 publications

References 58 publications

Accelerating electrostatic particle-in-cell simulation: A novel FPGA-based approach for efficient plasma investigations

Accelerating electrostatic particle-in-cell simulation: A novel FPGA-based approach for efficient plasma investigations

A New Approach of Combining Optical Mapping Algorithm with Adaptive Kalman Filter to Achieve Fast and Early Detection of Cardiac Arrests: A Parallel Implementation

Implementation of a motion estimation algorithm for Intel FPGAs using OpenCL

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