Results 11 to 20 of about 2,749 (228)
The Positive Effects of Stochastic Rounding in Numerical Algorithms
2022 IEEE 29th Symposium on Computer Arithmetic (ARITH), 2022 Recently, stochastic rounding (SR) has been implemented in specialized hardware but most current computing nodes do not yet support this rounding mode. Several works empirically illustrate the benefit of stochastic rounding in various fields such as neural networks and ordinary differential equations.
El-Mehdi El Arar, Eric Petit
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A Numerical Comparison of Petri Net and Ordinary Differential Equation SIR Component Models [PDF]
IEEE AccessPetri nets are an increasingly used modeling framework for the spread of disease across populations or within an individual. For example, the Susceptible-Infectious-Recovered (SIR) compartment model is foundational for population epidemiological modeling
Trevor Reckell +4 more
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Periodic orbits in chaotic systems simulated at low precision [PDF]
Scientific Reports, 2023 Non-periodic solutions are an essential property of chaotic dynamical systems. Simulations with deterministic finite-precision numbers, however, always yield orbits that are eventually periodic.
Milan Klöwer +3 more
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On Stochastic Rounding with Few Random Bits
2025 IEEE 32nd Symposium on Computer Arithmetic (ARITH)Published at ARITH ...
Andrew W. Fitzgibbon, Stephen Felix
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Probabilistic Error Analysis of Limited-Precision Stochastic Rounding
SIAM Journal of Scientific ComputingClassical probabilistic rounding error analysis is particularly well suited to stochastic rounding (SR), and it yields strong results when dealing with floating-point algorithms that rely heavily on summation. For many numerical linear algebra algorithms, one can prove probabilistic error bounds that grow as O(nu), where n is the problem size and u is ...
Mantas Mikaitis +2 more
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Stochastic Rounding Implicitly Regularizes Tall-and-Thin Matrices
SIAM Journal on Matrix Analysis and ApplicationsMotivated by the popularity of stochastic rounding in the context of machine learning and the training of large-scale deep neural network models, we consider stochastic nearness rounding of real matrices $\mathbf{A}$ with many more rows than columns. We provide novel theoretical evidence, supported by extensive experimental evaluation that, with high ...
Ilse Ipsen, Christos Boutsikas
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Bounds on Nonlinear Errors for Variance Computation with Stochastic Rounding
SIAM Journal of Scientific ComputingSIAM Journal on Scientific Computing, In ...
El-Mehdi El Arar
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Error Analysis of Sum-Product Algorithms under Stochastic Rounding
SIAM Journal of Scientific ComputingThe quality of numerical computations can be measured through their forward error, for which finding good error bounds is challenging in general. For several algorithms and using stochastic rounding (SR), probabilistic analysis has been shown to be an effective alternative for obtaining tight error bounds.
El-Mehdi El Arar, Eric Petit
exaly +4 more sources
Competence region estimation for black-box surrogate models
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 With advances in edge applications for industry andhealthcare, machine learning models are increasinglytrained on the edge. However, storage and memory in-frastructure at the edge are often primitive, due to costand real-estate constraints.
Tapan Shah
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Learning from low precision samples
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 With advances in edge applications in industry and healthcare, machine learning models are increasingly trained on the edge. However, storage and memory infrastructure at the edge are often primitive, due to cost and real-estate constraints.
Ji In Choi +5 more
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