A Vector-Like Reconfigurable Floating-Point Unit for the Logarithm by Nikolaos Alachiotis, Alexandros Stamatakis

“…The use of reconfigurable computing for accelerating floating-point intensive codes is becoming common due to the availability of DSPs in new-generation FPGAs. …”
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Development of Floating-Point MAC Engine for 2-D Convolution of Image by Ajay Kumar Sahu, Vishnumurthy Kedlaya K., Subramanya G. Nayak

“…This paper proposes a single-precision Floating Point MAC engine to accelerate the sliding window algorithm for the 2-D convolution of image. …”
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Multi‐precision binary multiplier architecture for multi‐precision floating‐point multiplication by Geetam Singh Tomar, Marcus Llyode George, Abhineet Singh Tomar

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FPGA‐based implementation of floating point processing element for the design of efficient FIR filters by Tintu Mary John, Shanty Chacko

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The Coarse-Grained/Fine-Grained Logic Interface in FPGAs with Embedded Floating-Point Arithmetic Units by Chi Wai Yu, Julien Lamoureux, Steven J. E. Wilton, Philip H. W. Leong, Wayne Luk

“…Specifically, it presents an empirical study that covers the location, pin arrangement, and interconnect between embedded floating point units (FPUs) and the fine-grained logic fabric in FPGAs. …”
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A Decimal Floating-Point Accurate Scalar Product Unit with a Parallel Fixed-Point Multiplier on a Virtex-5 FPGA by Malte Baesler, Sven-Ole Voigt, Thomas Teufel

“…Decimal Floating Point operations are important for applications that cannot tolerate errors from conversions between binary and decimal formats, for instance, commercial, financial, and insurance applications. …”
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Large-Eddy Simulation of the Flow Past a Circular Cylinder at Re = 130,000: Effects of Numerical Platforms and Single- and Double-Precision Arithmetic by Dmitry A. Lysenko

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Fast and low‐power leading‐one detectors for energy‐efficient logarithmic computing by Mohammad Saeed Ansari, Shyama Gandhi, Bruce F. Cockburn, Jie Han

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Performance Evaluation of FPGA-Based Design of Modified Chua Oscillator by Filips Capligins, İsmail Koyuncu, Anna Litvinenko, Muhammed Furkan Taşdemir

“…One of the most essential structures in chaotic systems is chaotic oscillator which generates chaotic signals. IQ-Math and floating point number systems are one of the preferred number standards. …”
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On Accuracy of Testing Decryption Failure Rate for Encryption Schemes under the LWE Assumption by Lin Wang, Yang Wang, Huiwen Jia

“…Therein explicit criteria are given to select the floating-point datatype and to decide which small probabilities should be abandoned. …”
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The Potential for a GPU-Like Overlay Architecture for FPGAs by Jeffrey Kingyens, J. Gregory Steffan

“…In particular, our soft processor architecture exploits multithreading, vector operations, and predication to supply a floating-point pipeline of 64 stages via hardware support for up to 256 concurrent thread contexts. …”
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Sector determination for SVPWM based four‐switch three‐phase VSI by O.C. Kivanc, S.B. Ozturk

“…The proposed method has been simulated by using MATLAB/Simulink and implemented using a VSI with a TMS320F28335 floating‐point digital signal processing. Simulation and experimental results show the feasibility and effectiveness of the proposed SVPWM algorithm for FSTP inverter.…”
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Accurate Evaluation of Polynomials in Legendre Basis by Peibing Du, Hao Jiang, Lizhi Cheng

“…Since the coefficients of the evaluated polynomial are fractions, we propose to store these coefficients in two floating point numbers, such as double-double format, to reduce the effect of the coefficients’ perturbation. …”
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CSGD-YOLO: A Corn Seed Germination Status Detection Model Based on YOLOv8n by Wenbin Sun, Meihan Xu, Kang Xu, Dongquan Chen, Jianhua Wang, Ranbing Yang, Quanquan Chen, Songmei Yang

“…Compared with the YOLO v8n, CSGD-YOLO improves performance in terms of accuracy, model size, parameter number, and floating-point operation counts by 1.39, 1.43, 1.77, and 2.95 percentage points, respectively. …”
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A Domain-Specific Architecture for Elementary Function Evaluation by Anuroop Sharma, Christopher Kumar Anand

“…Two new instructions are required, a table lookup instruction and an extended-precision floating-point multiply-add instruction with special treatment for exceptional inputs. …”
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Theoretical understanding of gradients of spike functions as boolean functions by DongHyung Yoo, Doo Seok Jeong

“…In this regard, we propose a method to evaluate the gradient of spike function viewed as a Boolean function for fixed- and floating-point data formats. For both formats, the gradient is considerably similar to a delta function that peaks at the threshold for spiking, which justifies the approximation of the spike function to the Heaviside step function. …”
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Image Super-Resolution Reconstruction Based on the Lightweight Hybrid Attention Network by Chu Yuezhong, Wang Kang, Zhang Xuefeng, Liu Heng

“…In addition, the parameter amount and calculation amount (floating point operations (FLOPs)) of our method are reduced by 315K and 16.4 G, respectively. …”
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Revisiting a Cutting-Plane Method for Perfect Matchings by Chen, Amber Q., Cheung, Kevin K. H., Kielstra, P. Michael, Winn, Avery D.

“…On large graphs (roughly $m>100$), these perturbations lead to cost values that exceed the precision of floating-point formats used by typical linear programming solvers for numerical calculations. …”
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A lightweight power quality disturbance recognition model based on CNN and Transformer by ZHANG Bide, QIU Jie, LOU Guangxin, ZHOU Can, LUO Qingqing, LI Tianqian

“…Simulation experiments demonstrate that the CaT model effectively recognizes PQDs with fewer parameters and floating point operations, achieving high accuracy and strong noise robustness. …”
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Enhanced Neural Architecture for Real-Time Deep Learning Wavefront Sensing by Jianyi Li, Qingfeng Liu, Liying Tan, Jing Ma, Nanxing Chen

“…We introduce a novel multi-objective neural architecture search (MNAS) method designed to attain Pareto optimality in terms of error and floating-point operations (FLOPs) for the WFSNet. Utilizing EfficientNet-B0 prototypes, we propose a WFSNet with enhanced neural architecture which significantly reduces computational costs by 80% while improving wavefront sensing accuracy by 22%. …”
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