Silviu-Ioan Filip
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View article: Probabilistic Error Analysis of Limited-Precision Stochastic Rounding
Probabilistic Error Analysis of Limited-Precision Stochastic Rounding Open
Classical 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 alg…
View article: Mixed precision accumulation for neural network inference guided by componentwise forward error analysis
Mixed precision accumulation for neural network inference guided by componentwise forward error analysis Open
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 analysis that explains the propagation of errors in the forw…
View article: SWAPPER: Dynamic Operand Swapping in Non-commutative Approximate Circuits for Online Error Reduction
SWAPPER: Dynamic Operand Swapping in Non-commutative Approximate Circuits for Online Error Reduction Open
Error-tolerant applications, such as multimedia processing, machine learning, signal processing, and scientific computing, can produce satisfactory outputs even when approximate computations are performed. Approximate computing (AxC) is no…
View article: AdaQAT: Adaptive Bit-Width Quantization-Aware Training
AdaQAT: Adaptive Bit-Width Quantization-Aware Training Open
Large-scale deep neural networks (DNNs) have achieved remarkable success in many application scenarios. However, high computational complexity and energy costs of modern DNNs make their deployment on edge devices challenging. Model quantiz…
View article: A Stochastic Rounding-Enabled Low-Precision Floating-Point MAC for DNN Training
A Stochastic Rounding-Enabled Low-Precision Floating-Point MAC for DNN Training Open
Training Deep Neural Networks (DNNs) can be computationally demanding, particularly when dealing with large models. Recent work has aimed to mitigate this computational challenge by introducing 8-bit floating-point (FP8) formats for multip…
View article: Towards Machine-Efficient Rational L ∞ -Approximations of Mathematical Functions
Towards Machine-Efficient Rational L ∞ -Approximations of Mathematical Functions Open
View article: Design of Optimal Multiplierless FIR Filters With Minimal Number of Adders
Design of Optimal Multiplierless FIR Filters With Minimal Number of Adders Open
This work presents two novel methods that simultaneously optimize both the design of a finite impulse response (FIR) filter and its multiplierless hardware implementation. We use integer linear programming (ILP) to minimize the number of a…
View article: Towards Arithmetic-Centered Filter Design
Towards Arithmetic-Centered Filter Design Open
International audience
View article: Design of Optimal Multiplierless FIR Filters
Design of Optimal Multiplierless FIR Filters Open
This work presents two novel optimization methods based on integer linear programming (ILP) that minimize the number of adders used to implement a direct/transposed finite impulse response (FIR) filter adhering to a given frequency specifi…
View article: Table-Based versus Shift-And-Add constant multipliers for FPGAs
Table-Based versus Shift-And-Add constant multipliers for FPGAs Open
International audience
View article: Smooth Random Functions, Random ODEs, and Gaussian Processes
Smooth Random Functions, Random ODEs, and Gaussian Processes Open
International audience
View article: A High Throughput Polynomial and Rational Function Approximations Evaluator
A High Throughput Polynomial and Rational Function Approximations Evaluator Open
We present an automatic method for the evaluation of functions via polynomial or rational approximations and its hardware implementation, on FPGAs. These approximations are evaluated using Ercegovac's iterative E-method adapted for FPGA im…
View article: A Lattice Basis Reduction Approach for the Design of Finite Wordlength FIR Filters
A Lattice Basis Reduction Approach for the Design of Finite Wordlength FIR Filters Open
International audience
View article: Rational Minimax Approximation via Adaptive Barycentric Representations
Rational Minimax Approximation via Adaptive Barycentric Representations Open
Computing rational minimax approximations can be very challenging when there are singularities on or near the interval of approximation - precisely the case where rational functions outperform polynomials by a landslide. We show that far m…
View article: Automatic generation of hardware FIR filters from a frequency domain specification
Automatic generation of hardware FIR filters from a frequency domain specification Open
This article presents an open-source tool for the automatic design of reliable finite impulse response (FIR) filters, targeting FPGAs. It shows that user intervention can be limited to a very small number of relevant input parameters: a hi…
View article: Outils robustes pour l’approximation de Chebyshev pondérée et applications à la synthèse de filtres numériques
Outils robustes pour l’approximation de Chebyshev pondérée et applications à la synthèse de filtres numériques Open
The field of signal processing methods and applications frequentlyrelies on powerful results from numerical approximation. One suchexample, at the core of this thesis, is the use of Chebyshev approximationmethods for designing digital filt…