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Publications associées (321)
The 2024 Magnonics Roadmap
Dirk Grundler, Thomas Yu, Ping Che, Qi Wang, Wei Zhang, Benedetta Flebus
Magnonics is a research field that has gained an increasing interest in both the fundamental and applied sciences in recent years. This field aims to explore and functionalize collective spin excitations in magnetically ordered materials for modern informa ...
2024DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD
Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Pengbo Yu, Flavio Ponzina
Machine learning algorithms such as Convolutional Neural Networks (CNNs) are characterized by high robustness towards quantization, supporting small-bitwidth fixed-point arithmetic at inference time with little to no degradation in accuracy. In turn, small ...
2024Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications
Joshua Alexander Harrison Klein
The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...
EPFL2024Highly Parallel RTL Simulation
Verification and testing of hardware heavily relies on cycle-accurate simulation of RTL.As single-processor performance is growing only slowly, conventional, single-threaded RTL simulation is becoming impractical for increasingly complex chip designs and s ...
EPFL2024Assessment framework for deepfake detection in real-world situations
Detecting digital face manipulation in images and video has attracted extensive attention due to the potential risk to public trust. To counteract the malicious usage of such techniques, deep learning-based deepfake detection methods have been employed and ...
2024Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms
Aurélien François Gilbert Bloch
Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...
EPFL2023On the Fusion Strategies for Federated Decision Making
Ali H. Sayed, Emre Telatar, Mert Kayaalp, Yunus Inan
We consider the problem of information aggregation in federated decision making, where a group of agents collaborate to infer the underlying state of nature without sharing their private data with the central processor or each other. We analyze the non-Bay ...
2023Post-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 ...
2023Design Space Exploration for Partitioning Dataflow Program on CPU-GPU Heterogeneous System
Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch
Dataflow programming is a methodology that enables the development of high-level, parametric programs that are independent of the underlying platform. This approach is particularly useful for heterogeneous platforms, as it eliminates the need to rewrite ap ...
SPRINGER2023Automatic and high-precision microseismic monitoring of progressive failure prior, during, and after tunnel excavation
Brice Tanguy Alphonse Lecampion, Seyyedmaalek Momeni, Christophe Nussbaum
Acoustic emission (AE) monitoring is commonly used to inspect the health of a structure continuously. During fracture processes elastic waves of AE are created and emitted, and sensors can capture these waves. The acquired signals can be processed to track ...
2023