Publications associées à Peephole optimization

Mesh-based topology, shape and sizing optimization of ribbed plates

In this paper, we present a new parameterization and optimization procedure for minimizing the weight of ribbed plates. The primary goal is to reduce embodied CO2 in concrete floors as part of the effort to diminish the carbon footprint of the construction ...

Springer2024

Scalable constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

MOD2IR: High-Performance Code Generation for a Biophysically Detailed Neuronal Simulation DSL

Felix Schürmann, Pramod Shivaji Kumbhar, Omar Awile, Snehal Pramod Kumbhar, Ioannis Magkanaris

Advances in computational capabilities and large volumes of experimental data have established computer simulations of brain tissue models as an important pillar in modern neuroscience. Alongside, a variety of domain specific languages (DSLs) have been dev ...

ACM2023

WarpAttack: Bypassing CFI through Compiler-Introduced Double-Fetches

Mathias Josef Payer, Flavio Toffalini, Luca Di Bartolomeo, Jianhao Xu

Code-reuse attacks are dangerous threats that attracted the attention of the security community for years. These attacks aim at corrupting important control-flow transfers for taking control of a process without injecting code. Nowadays, the combinations o ...

IEEE COMPUTER SOC2023

Stable Nonconvex-Nonconcave Training via Linear Interpolation

Volkan Cevher, Thomas Michaelsen Pethick, Wanyun Xie

This paper presents a theoretical analysis of linear interpolation as a principled method for stabilizing (large-scale) neural network training. We argue that instabilities in the optimization process are often caused by the nonmonotonicity of the loss lan ...

2023

Beyond Spectral Gap: The Role of the Topology in Decentralized Learning

Martin Jaggi, Thijs Vogels, Hadrien Hendrikx

In data-parallel optimization of machine learning models, workers collaborate to improve their estimates of the model: more accurate gradients allow them to use larger learning rates and optimize faster. In the decentralized setting, in which workers commu ...

Microtome Publishing2023

Silent Bugs Matter: A Study of Compiler-Introduced Security Bugs

Mathias Josef Payer, Jianhao Xu

Compilers assure that any produced optimized code is semantically equivalent to the original code. However, even "correct" compilers may introduce security bugs as security properties go beyond translation correctness. Security bugs introduced by such corr ...

Usenix Assoc2023

Modeling and Design Optimization of Loosely Coupled PCB Spiral Coils in Inductive Power Transfer Systems

Drazen Dujic, Xiaotong Du

There are various possibilities to realize coil winding designs for an inductive power transfer system. In order to achieve high power transfer efficiency and power density and explore trade-offs between the two, design optimization around the coil link is ...

2023

Power Transformer Fault Diagnosis Using Neural Network Optimization Techniques

Dimitrios Kaminaris

Artificial Intelligence (AI) techniques are considered the most advanced approaches for diagnosing faults in power transformers. Dissolved Gas Analysis (DGA) is the conventional approach widely adopted for diagnosing incipient faults in power transformers. ...

MDPI2023

Structural topology exploration through policy-based generation of equilibrium representations

Corentin Jean Dominique Fivet, Ioannis Mirtsopoulos

Mainstream approaches to design spatial architectural forms that are structurally relevant consist either in adapting well-known and catalogued conventional types or in searching for close-to-optimum solutions of well-defined problems. Few means exist to e ...

2023

The importance of young professionals for dam engineering in Switzerland

Samuel Luke Vorlet, Valentina Favero

In Switzerland, hydropower is the main energy source and contributes to about 58.3% of the total production. The 2050 energy strategy aims to increase this share in the coming decades. This increase is a challenge for hydropower plants. The maintenance and ...

CRC Press/Balkema2023

Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations

Zilu Tian

Agent-based simulations have been widely applied in many disciplines, by scientists and engineers alike. Scientists use agent-based simulations to tackle global problems, including alleviating poverty, reducing violence, and predicting the impact of pandem ...

EPFL2023

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Panagiotis Sioulas

Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...

EPFL2023

Scaffolding protein functional sites using deep learning

Bruno Emanuel Ferreira De Sousa Correia, Wayne Yang Wen Wei, Karla Montserrat Castro Gilabert, Basile Isidore Martin Wicky, Jue Wang

The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without needing ...

American Association for the Advancement of Science2022

An Optimized Low-Power Band-Tuning TX for Short-Range FMCW Radar in 22-nm FDSOI CMOS

Christian Enz, Francesco Chicco, Sammy Cerida Rengifo

The paper presents a low-power transmitter (TX) as a part of a fully integrated 57-66 GHz FMCW radar system. The TX path includes a BPSK modulator and it is optimized for short-range operation with 0 dBm output power. A band-tuning technique is used for co ...

IEEE2021

A Rosetta-based protein design protocol converging to natural sequences

Bruno Emanuel Ferreira De Sousa Correia, Stéphane Rosset, Zander Harteveld, Giulia Sormani

Computational protein design has emerged as a powerful tool capable of identifying sequences compatible with pre-defined protein structures. The sequence design protocols, implemented in the Rosetta suite, have become widely used in the protein engineering ...

AMER INST PHYSICS2021

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

Geometric optimization of dielectric elastomer electrodes for dynamic applications

Herbert Shea, Bekir Aksoy, Emil Yan Garnell

Dielectric elastomers are soft actuators, made of an elastomer membrane sandwiched by compliant electrodes. Because of their high energy density and quick response, they are well suited for dynamic applications such as loudspeakers. Thanks to progress in t ...

ELSEVIER SCI LTD2021

Sensory modulation of gait characteristics in human locomotion: A neuromusculoskeletal modeling study

Auke Ijspeert, Andrea Di Russo, Dimitar Yuriev Stanev, Stéphane Armand

The central nervous system of humans and other animals modulates spinal cord activity to achieve several locomotion behaviors. Previous neuromechanical models investigated the modulation of human gait changing selected parameters belonging to CPGs (Central ...

2021

Innovative Renewable Technology Integration for Nearly Zero-Energy Buildings within the Re-COGNITION Project

Alessandro Francesco Aldo Virtuani

With the 2010/31/EU directive, all new buildings shall be nearly zero-energy buildings (nZEB) from 2020 onward, with the aim of strongly reducing the energy consumption related to the building sector. To achieve this goal, it is not sufficient to focus on ...

MDPI2021