6 papers
What is New in Stochastic Rounding: a Survey on Theory, Hardware, and Applications
El-Mehdi El Arar, Massimiliano Fasi, Silviu-Ioan Filip +1
Stochastic rounding (SR) is a probabilistic method used to round numbers to floating-point and fixed-point representations. In length summation, the worst-case error of SR grow…
Probabilistic Error Analysis of Limited-Precision Stochastic Rounding: Horner's Algorithm and Pairwise Summation
El-Mehdi El Arar, Massimiliano Fasi, Silviu-Ioan Filip +1
Stochastic rounding (SR) is a probabilistic rounding mode that mitigates errors in large-scale numerical computations, especially when prone to stagnation effects. Beyond numerical…
Mixed precision accumulation for neural network inference guided by componentwise forward error analysis
El-Mehdi El Arar, Silviu-Ioan Filip, Theo Mary +1
This work proposes a mathematically founded mixed precision accumulation strategy for the inference of neural networks. Our strategy is based on a new componentwise forward error a…
Error Analysis of Sum-Product Algorithms under Stochastic Rounding
Pablo de Oliveira Castro, El-Mehdi El Arar, Eric Petit +1
The 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 s…
Probabilistic error analysis of limited-precision stochastic rounding
El-Mehdi El Arar, Massimiliano Fasi, Silviu-Ioan Filip +1
Classical probabilistic rounding error analysis is particularly well suited to stochastic rounding (SR), and it yields strong results when dealing with floating-point algorithms th…
SwiftSketch: A Diffusion Model for Image-to-Vector Sketch Generation
Ellie Arar, Yarden Frenkel, Daniel Cohen-Or +2
Recent advancements in large vision-language models have enabled highly expressive and diverse vector sketch generation. However, state-of-the-art methods rely on a time-consuming…