Near-Optimal Finite-Length Scaling for Polar Codes Over Large Alphabets

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The increasing complexity of transformer models in artificial intelligence expands their computational costs, memory usage, and energy consumption. Hardware acceleration tackles the ensuing challenges by designing processors and accelerators tailored for t ...

Information theory has allowed us to determine the fundamental limit of various communication and algorithmic problems, e.g., the channel coding problem, the compression problem, and the hypothesis testing problem. In this work, we revisit the assumptions ...

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov ...

5G New Radio (NR) has stringent demands on both performance and complexity for the design of low-density parity-check (LDPC) decoding algorithms and corresponding VLSI implementations. Furthermore, decoders must fully support the wide range of all 5G NR bl ...

Spectral algorithms are some of the main tools in optimization and inference problems on graphs. Typically, the graph is encoded as a matrix and eigenvectors and eigenvalues of the matrix are then used to solve the given graph problem. Spectral algorithms ...

We discuss how the combination of experimental observations and rapid modeling has enabled to improve understanding of the tokamak ramp-down phase in ASDEX Upgrade. A series of dedicated experiments has been performed, to disentangle the effect of individu ...

In this thesis we will present and analyze randomized algorithms for numerical linear algebra problems. An important theme in this thesis is randomized low-rank approximation. In particular, we will study randomized low-rank approximation of matrix functio ...

In this thesis, we propose to formally derive amplitude equations governing the weakly nonlinear evolution of non-normal dynamical systems, when they respond to harmonic or stochastic forcing, or to an initial condition. This approach reconciles the non-mo ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

Rapid inter-discharge simulation and optimization using the RAPTOR code have allowed the development of a reliable and reproducible early heating strategy for an advanced tokamak (AT) scenario on ASDEX Upgrade. Solving for electron heat and current diffusi ...

The finite element method is a well-established method for the numerical solution of partial differential equations (PDEs), both linear and nonlinear. However, the repeated re -assemblage of finite element matrices for nonlinear PDEs is frequently pointed ...

Modern data management systems aim to provide both cutting-edge functionality and hardware efficiency. With the advent of AI-driven data processing and the post-Moore Law era, traditional memory-bound scale-up data management operations face scalability ch ...

Low-Density Parity-Check (LDPC) decoder is among the power hungry building blocks of wireless communication systems. Voltage scaling down to Near-Threshold (NT) voltages substantially improves energy efficiency, in theory up 10x. However, tuning the voltag ...

A new model is proposed for the consolidation of hybrid textiles, in which air entrapment and dissolution are considered. One of the key parameters is tow permeability, which is described by the analytical model of Gebart and validated at very high fibre v ...

Single-photon 3D cameras can record the time-of-arrival of billions of photons per second with picosecond accuracy. One common approach to summarize the photon data stream is to build a per-pixel timestamp histogram, resulting in a 3D histogram tensor that ...

Sylvester matrix equations are ubiquitous in scientific computing. However, few solution techniques exist for their generalized multiterm version, as they now arise in an increasingly large number of applications. In this work, we consider algebraic parame ...

State-of-the-art Artificial Intelligence (AI) algorithms, such as graph neural networks and recommendation systems, require floating-point computation of very large matrix multiplications over sparse data. Their execution in resource-constrained scenarios, ...

We present a nonperturbative recipe for directly computing the S-matrix in strongly-coupled QFTs. The method makes use of spectral data obtained in a Hamiltonian framework and can be applied to a wide range of theories, including potentially QCD. We demons ...

In this paper, we study the rank-one convex hull of a differential inclusion associated to entropy solutions of a hyperbolic system of conservation laws. This was introduced in [B. Kirchheim, S. Muller and V. S(sic)ver & aacute;k, Studying Nonlinear PDE by ...

We expand Hilbert series technologies in effective field theory for the inclusion of massive particles, enabling, among other things, the enumeration of operator bases for non-linearly realized gauge theories. We find that the Higgs mechanism is manifest a ...

Near-Optimal Finite-Length Scaling for Polar Codes Over Large Alphabets

Chattez avec Graph Search

Accelerator-driven Data Arrangement to Minimize Transformers Run-time on Multi-core Architectures

On Speed and Advantage : Results in Information Velocity and Monitoring Problems

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

A Generalized Adjusted Min-Sum Decoder for 5G LDPC Codes: Algorithm and Implementation

The Power of Two Matrices in Spectral Algorithms for Community Recovery

Scenario optimization for the tokamak ramp-down phase in RAPTOR: A. Analysis and model validation on ASDEX Upgrade

Randomized low-rank approximation and its applications

Non-normal forms

Spectral Estimators for High-Dimensional Matrix Inference

Inter-discharge optimization for fast, reliable access to ASDEX Upgrade advanced tokamak scenario

On the fast assemblage of finite element matrices with application to nonlinear heat transfer problems

Post-Moore's Law Fusion: High-Bandwidth Memory, Accelerators, and Native Half-Precision Processing for CPU-Local Analytics

Low Power LDPC Decoding by Reliable Voltage Down-Scaling

A model for the consolidation of hybrid textiles considering air entrapment, dissolution and diffusion

Learned Compressive Representations for Single-Photon 3D Imaging

Preconditioning techniques for generalized Sylvester matrix equations

A 16-bit Floating-Point Near-SRAM Architecture for Low-power Sparse Matrix-Vector Multiplication

Towards a nonperturbative construction of the S-matrix

T-5 configurations and hyperbolic systems

Hilbert series, the Higgs mechanism, and HEFT