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Publications associées (30)

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Analysis system and method for analysing the movement of a portion of the body and/or of a human prosthesis

Silvestro Micera, Fiorenzo Artoni, Andrea Crema

An analysis method (200) for analysing the pressure exerted by a portion of the body and/or of a human prosthesis comprises the following steps: sampling data generated by the portion of the body and/or the human prosthesis during a threshold calibration p ...

2021

Rebooting Virtual Memory with Midgard

Babak Falsafi, Mathias Josef Payer, Siddharth Gupta, Atri Bhattacharyya, Yunho Oh, Abhishek Bhattacharjee

Computer systems designers are building cache hierarchies with higher capacity to capture the ever-increasing working sets of modern workloads. Cache hierarchies with higher capacity improve system performance but shift the performance bottleneck to addres ...

2021

Large-Scale Graph Processing on FPGAs with Caches for Thousands of Simultaneous Misses

Paolo Ienne, Mikhail Asiatici

Efficient large-scale graph processing is crucial to many disciplines. Yet, while graph algorithms naturally expose massive parallelism opportunities, their performance is limited by the memory system because of irregular memory accesses. State-of-the-art ...

IEEE COMPUTER SOC2021

Leaderless Consensus

Rachid Guerraoui, Vincent Gramoli, Mihail Igor Zablotchi, Karolos Antoniadis

Classical synchronous consensus algorithms are leaderless: processes exchange their proposals, retain the maximum value and decide when they see the same choice across a couple of rounds. Indulgent consensus algorithms are more robust in that they only req ...

IEEE COMPUTER SOC2021

Micro-architectural analysis of in-memory OLTP: Revisited

Anastasia Ailamaki, Danica Porobic, Utku Sirin

Micro-architectural behavior of traditional disk-based online transaction processing (OLTP) systems has been investigated extensively over the past couple of decades. Results show that traditional OLTP systems mostly under-utilize the available micro-archi ...

2021

A Flexible In-Memory Computing Architecture for Heterogeneously Quantized CNNs

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

Inferences using Convolutional Neural Networks (CNNs) are resource and energy intensive. Therefore, their execution on highly constrained edge devices demands the careful co-optimization of algorithms and hardware. Addressing this challenge, in this paper ...

2021

Preventing Use-After-Free Attacks with Fast Forward Allocation

Sanidhya Kashyap

Memory-unsafe languages are widely used to implement critical systems like kernels and browsers, leading to thousands of memory safety issues every year. A use-after-free bug is a temporal memory error where the program accidentally visits a freed memory l ...

USENIX ASSOC2021

Optimization Methods for Control: From Embedded Programmable Hardware to Data-Driven Process Optimization

Harsh Ambarishkumar Shukla

The research community has been making significant progress in hardware implementation, numerical computing and algorithm development for optimization-based control. However, there are two key challenges that still have to be overcome for optimization-base ...

EPFL2021

Learning continuous-time working memory tasks with on-policy neural reinforcement learning

Davide Zambrano

An animals' ability to learn how to make decisions based on sensory evidence is often well described by Reinforcement Learning (RL) frameworks. These frameworks, however, typically apply to event-based representations and lack the explicit and fine-grained ...

2021

Serial dependence under memory load

Michael Herzog, David Pascucci, Gizay Ceylan, Natalia Tiurina, Ayberk Ozkirli, Yury Markov

Perceptual decisions are biased towards previous stimuli, a phenomenon known as serial dependence. However, the mechanisms of this bias are unknown. For example, it is debated whether serial dependence reflects a perceptual bias or interference of prior st ...

SAGE Publishing2021