Publications related to Quadruple-precision floating-point format

Towards General-Purpose Decentralized Computing with Permissionless Extensibility

Smart contracts have emerged as the most promising foundations for applications of the blockchain technology. Even though smart contracts are expected to serve as the backbone of the next-generation web, they have several limitations that hinder their wide ...

EPFL2024

Functional-Basis Analysis of Non-Stationary Signals in Modern Power Grids: Theory and Implementation in Embedded Systems

Alexandra Cameron Karpilow

Situational awareness strategies are essential for the reliable and secure operation of the electric power grid which represents critical infrastructure in modern society. With the rise of converter-interfaced renewable generation and the consequent shift ...

EPFL2024

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

David Atienza Alonso, Giovanni Ansaloni, Grégoire Axel Eggermann, Marco Antonio Rios

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, ...

New York2023

Overflow-free compute memories for edge AI acceleration

David Atienza Alonso, Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Marco Antonio Rios, Flavio Ponzina

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can ...

2023

A mixed precision LOBPCG algorithm

Daniel Kressner, Meiyue Shao, Yuxin Ma

The locally optimal block preconditioned conjugate gradient (LOBPCG) algorithm is a popular approach for computing a few smallest eigenvalues and the corresponding eigenvectors of a large Hermitian positive definite matrix A. In this work, we propose a mix ...

SPRINGER2023

Efficient Lung Nodule Detection via 3D Deep Learning with Shifted Convolutions

Jiancheng Yang, Bo Du, Kang Yuan

The high computational costs of deep convolutional neural networks hinder their deployment in real-world applications, including pulmonary nodule detection from CT scans where large 3D image sizes amplify the issue. This paper presents a novel 3D method to ...

IEEE2023

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

Anastasia Ailamaki, Viktor Sanca

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 ...

2023

Measurement of the B+ -> rho0 mu+ nu differential branching fraction

Veronica Sølund Kirsebom

The tension between different determinations of the CKM matrix element Vub using measurements of either exclusive or inclusive semileptonic decays represents a long-standing puzzle in flavour physics. To resolve this, measurements of new exclusive channels ...

EPFL2023

Mixed-precision explicit stabilized Runge-Kutta methods for single- and multi-scale differential equations

Giacomo Rosilho De Souza, Matteo Croci

Mixed-precision algorithms combine low-and high-precision computations in order to benefit from the performance gains of reduced-precision without sacrificing accuracy. In this work, we design mixed-precision Runge-Kutta-Chebyshev (RKC) methods, where high ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

The Lang-Trotter conjecture for products of non-CM elliptic curves

Vlad Serban

Inspired by the work of Lang-Trotter on the densities of primes with fixed Frobenius traces for elliptic curves defined over Q and by the subsequent generalization of Cojocaru-Davis-Silverberg-Stange to generic abelian varieties, we study the analogous que ...

SPRINGER2022

Iterative refinement of Schur decompositions

Daniel Kressner, Zvonimir Bujanovic

The Schur decomposition of a square matrix A is an important intermediate step of state-of-the-art numerical algorithms for addressing eigenvalue problems, matrix functions, and matrix equations. This work is concerned with the following task: Compute a (m ...

SPRINGER2023

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

Aleksandra Radenovic, Andras Kis, Mukesh Kumar Tripathi, Guilherme Migliato Marega, Zhenyu Wang

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...

2022

Covariance Estimation for Random Surfaces beyond Separability

Tomas Masák

This thesis focuses on non-parametric covariance estimation for random surfaces, i.e.~functional data on a two-dimensional domain. Non-parametric covariance estimation lies at the heart of functional data analysis, and considerations of statistical and com ...

EPFL2022

Robust Binary Models by Pruning Randomly-initialized Networks

Sabine Süsstrunk, Mathieu Salzmann, Chen Liu, Ziqi Zhao

Robustness to adversarial attacks was shown to require a larger model capacity, and thus a larger memory footprint. In this paper, we introduce an approach to obtain robust yet compact models by pruning randomly-initialized binary networks. Unlike adversar ...

2022

Quadratic serendipity element shape functions on general planar polygons

Xiaodong Wei, Juan Cao

This paper proposes a method for the construction of quadratic serendipity element (QSE) shape functions on planar convex and concave polygons. Existing approaches for constructing QSE shape functions are linear combinations of the pair-wise products of ge ...

ELSEVIER SCIENCE SA2022

Bootstrapping for Approximate Homomorphic Encryption with Negligible Failure-Probability by Using Sparse-Secret Encapsulation

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Jean-Philippe Léonard Bossuat

Bootstrapping parameters for the approximate homomorphic-encryption scheme of Cheon et al., CKKS (Asiacrypt 17), are usually instantiated using sparse secrets to be efficient. However, using sparse secrets constrains the range of practical parameters withi ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Interlaboratory Test Program to Determine the Precision of the R3 Test Method (ASTM C1897-20) for Measuring Reactivity of Supplementary Cementitious Materials

Karen Scrivener, Ruben Anton Snellings, Diana Londoño Zuluaga

The substitution of portland clinker by supplementary cementitious materials (SCMs) is one of the main avenues for the further decarbonization of cement production. To secure future SCM supplies, generic and performance-related test methods for SCMs are re ...

AMER SOC TESTING MATERIALS2022

Parameter-free rendering of single-molecule localization microscopy data for parameter-free resolution estimation

Aleksandra Radenovic, Adrien Charles-François Raymond Descloux, Kristin Stefanie Grussmayer

Localization microscopy is a super-resolution imaging technique that relies on the spatial and temporal separation of blinking fluorescent emitters. These blinking events can be individually localized with a precision significantly smaller than the classic ...

2021

Serial Lightweight Implementation Techniques for Block Ciphers

Muhammed Fatih Balli

Most of the cryptographic protocols that we use frequently on the internet are designed in a fashion that they are not necessarily suitable to run in constrained environments. Applications that run on limited-battery, with low computational power, or area ...

EPFL2021

Equinox: Training (for Free) on a Custom Inference Accelerator

Babak Falsafi, Martin Jaggi, Ahmet Caner Yüzügüler, Louis Coulon, Mario Paulo Drumond Lages De Oliveira, Arash Pourhabibi Zarandi

DNN inference accelerators executing online services exhibit low average loads because of service demand variability, leading to poor resource utilization. Unfortunately, reclaiming idle inference cycles is difficult as other workloads can not execute on a ...

ACM2021