Publications associées à Multiplication

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

David Atienza Alonso, Giovanni Ansaloni, Alireza Amirshahi

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 ...

2024

EdgeAI-Aware Design of In-Memory Computing Architectures

Marco Antonio Rios

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

EPFL2024

Computational Imaging SPAD Cameras

Andrei Ardelean

Vision systems built around conventional image sensors have to read, encode and transmit large quantities of pixel information, a majority of which is redundant. As a result, new computational imaging sensor architectures were developed to preprocess the r ...

EPFL2023

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

Fabrication and Characterization of High Aspect Ratio Amorphous Silicon Based Microchannel Plates

Christophe Ballif, Nicolas Würsch, Janina Christine Isabelle Löffler, Samira Alexandra Frey, Mohammad Beygi

This contribution focuses on the fabrication and characterization of microchannel plates made of hydrogenated amorphous silicon (AMCPs). Flexible fabrication processes and the semi-conducting nature of amorphous silicon could give these detectors the advan ...

2021

Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)

Rachid Guerraoui, Sadegh Farhadkhani, El Mahdi El Mhamdi, Le Nguyen Hoang, Sébastien Louis Alexandre Rouault, Arsany Hany Abdelmessih Guirguis

We study Byzantine collaborative learning, where n nodes seek to collectively learn from each others' local data. The data distribution may vary from one node to another. No node is trusted, and f < n nodes can behave arbitrarily. We prove that collaborati ...

2021

Characterization of Amorphous Silicon Based Microchannel Plates with High Aspect Ratio

Christophe Ballif, Nicolas Würsch, Janina Christine Isabelle Löffler, Samira Alexandra Frey

Microchannel plates (MCPs) fabricated out of hydrogenated amorphous silicon offer a promising alternative to conventional lead glass ones. Progress in the fabrication process has allowed for detectors with higher aspect ratios, which significantly increase ...

IEEE2019

Reducing the Multiplicative Complexity in Logic Networks for Cryptography and Security Applications

Giovanni De Micheli, Mathias Soeken, Luca Gaetano Amarù, Eleonora Testa

Reducing the number of AND gates plays a central role in many cryptography and security applications. We propose a logic synthesis algorithm and tool to minimize the number of AND gates in a logic network composed of AND, XOR, and inverter gates. Our appro ...

ASSOC COMPUTING MACHINERY2019

The Role of Multiplicative Complexity in Compiling Low T-count Oracle Circuits

Giovanni De Micheli, Mathias Soeken, Giulia Meuli

We present a constructive method to create quantum circuits that implement oracles vertical bar x vertical bar y |0 (k) -> vertical bar x vertical bar y circle plus f(x)vertical bar 0 (k) for n-variable Boolean functions f with low T-count. In our method f ...

IEEE2019

Sur quelques équations aux dérivées partielles en lien avec le lemme de Poincaré

David Valentin Strütt

In this thesis, we study two distinct problems. The first problem consists of studying the linear system of partial differential equations which consists of taking a k-form, and applying the exterior derivative 'd' to it and add the wedge product with a 1- ...

EPFL2018