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A note on precision-preserving compression of scientific data [PDF]
Geoscientific Model Development, 2021 Lossy compression of scientific data arrays is a powerful tool to save network bandwidth and storage space. Properly applied lossy compression can reduce the size of a dataset by orders of magnitude while keeping all essential information, whereas a ...
R. Kouznetsov, R. Kouznetsov
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Online Signature Verification Systems on a Low-Cost FPGA
Applied Sciences, 2021 This paper describes three different approaches for the implementation of an online signature verification system on a low-cost FPGA. The system is based on an algorithm, which operates on real numbers using the double-precision floating-point IEEE 754 ...
Enrique Cantó Navarro +2 more
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DPF-ECC: A Framework for Efficient ECC With Double Precision Floating-Point Computing Power
IEEE Transactions on Information Forensics and Security, 2021 Used ubiquitously in a huge amount of security protocols or applications, elliptic curve cryptography (ECC) is one of the most important cryptographic primitives, featuring efficiency and short key size compared with other public-key cryptosystems such ...
Lili Gao +7 more
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Computation, 2021 Many low-cost platforms that support floating-point arithmetic, such as microcontrollers and field-programmable gate arrays, do not include fast hardware or software methods for calculating the square root and/or reciprocal square root.
Leonid V. Moroz +2 more
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Scaling up and down of 3-D floating-point data in quantum computation
Scientific Reports, 2022 In the past few decades, quantum computation has become increasingly attractive due to its remarkable performance. Quantum image scaling is considered a common geometric transformation in quantum image processing, however, the quantum floating-point data
Meiyu Xu, Dayong Lu, Xiaoyun Sun
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Applied Sciences, 2023 Computing-in-Memory (CIM) is a novel computing architecture that enormously improves energy efficiency and reduces computing latency by avoiding frequent data movement between the computation and memory units.
Liang Liu +5 more
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All-Digital Computing-in-Memory Macro Supporting FP64-Based Fused Multiply-Add Operation
Applied Sciences, 2023 Recently, frequent data movement between computing units and memory during floating-point arithmetic has become a major problem for scientific computing.
Dejian Li +6 more
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Quantitative study of floating-point precision on modern FPGAs
Heart, 2023 Modern computer systems perform computations on real numbers through approximate representation that is often based on a specific floating-point format.
Riadh Ben Abdelhamid +2 more
semanticscholar +1 more source
Journal of Advances in Modeling Earth Systems, 2022 Most Earth‐system simulations run on conventional central processing units in 64‐bit double precision floating‐point numbers Float64, although the need for high‐precision calculations in the presence of large uncertainties has been questioned.
Milan Klöwer +4 more
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Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations [PDF]
, 2020 Although double-precision floating-point arithmetic currently dominates high-performance computing, there is increasing interest in smaller and simpler arithmetic types.
Furber, Steve +3 more
core +2 more sources