Publications related to Branch predictor

Dynamic Voxels Based on Ego-Conditioned Prediction: An Integrated Spatio-Temporal Framework for Motion Planning

Prediction is a vital component of motion planning for autonomous vehicles (AVs). By reasoning about the possible behavior of other target agents, the ego vehicle (EV) can navigate safely, efficiently, and politely. However, most of the existing work overl ...

IEEE Institute of Electrical and Electronics Engineers2024

Flood, farms and credit: The role of branch banking in the era of climate change

Seyed Javad Kashizadeh, Pejman Abedifar

Using Iran's unexpected flood in April 2019 as a natural experiment, we show that local branches bridge the time gap between the disaster and governmental aids by immediately increasing their lending for two months following the flood. Analyzing proprietar ...

Elsevier2024

Parallel flows as a key component to interpret Super-X divertor experiments

Basil Duval, Holger Reimerdes, Christian Gabriel Theiler, Joaquim Loizu Cisquella, Artur Perek, Guang-Yu Sun, Luke Simons, Olivier Claude Martin Février, Garance Hélène Salomé Durr-Legoupil-Nicoud, Davide Galassi, Lorenzo Martinelli, Sophie Danielle Angelica Gorno, Claudia Colandrea, Curdin Tobias Wüthrich

The Super-X Divertor (SXD) is an alternative divertor configuration leveraging total flux expansion at the Outer Strike Point (OSP). While the extended 2-Point Model (2PM) predicts facilitated detachment access and control in the SXD configuration, these a ...

IOP Publishing Ltd2024

Data-driven modeling of beam loss in the LHC

Tatiana Pieloni, Michael Schenk, Ekaterina Krymova, Loïc Thomas Davies Coyle

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

FRONTIERS MEDIA SA2023

Dynamic Modeling of an Origami Prismatic Joint

Jamie Paik, Mustafa Mete, Jian-Lin Huang

Dynamic modeling of folding joints is critical for predicting dynamic behavior, optimizing design parameters, and developing control strategies for origami robots and machines. Although kinematics of the folded joints exists, little research describes thei ...

IEEE2023

Rebooting Virtual Memory with Midgard

Siddharth Gupta

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

EPFL2023

Micro BTB: A High Performance and Storage Efficient Last-Level Branch Target Buffer for Servers

Vishal Gupta

High-performance branch target buffers (BTBs) and the L1I cache are key to high-performance front-end. Modern branch predictors are highly accurate, but with an increase in code footprint in modern-day server workloads, BTB and L1I misses are still frequen ...

ASSOC COMPUTING MACHINERY2022

Lightweight HI source finding for next generation radio surveys

Jean-Paul Richard Kneib, Frédéric Courbin, Emma Elizabeth Tolley, Aymeric Alexandre Galan, Austin Chandler Peel, Mark Thomas Sargent

Future deep HI surveys will be essential for understanding the nature of galaxies and the content of the Universe. However, the large volume of these data will require distributed and automated processing techniques. We introduce LiSA, a set of python modu ...

ELSEVIER2022

Optimal Adversarial Policies in the Multiplicative Learning System With a Malicious Expert

Negar Kiyavash, Seyed Jalal Etesami

We consider a learning system based on the conventional multiplicative weight ( MW) rule that combines experts' advice to predict a sequence of true outcomes. It is assumed that one of the experts is malicious and aims to impose the maximum loss on the sys ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Micro-architectural Analysis of Database Workloads

Utku Sirin

Database workloads have significantly evolved in the past twenty years. Traditional database systems that are mainly used to serve Online Transactional Processing (OLTP) workloads evolved into specialized database systems that are optimized for particular ...

EPFL2021

On the assessment of arterial compliance from carotid pressure waveform

Nikolaos Stergiopoulos, Georgios Rovas, Vasiliki Bikia, Stamatia Zoi Pagoulatou, Patrick Segers

In a progressively aging population, it is of utmost importance to develop reliable, noninvasive, and cost-effective tools to estimate biomarkers that can be indicative of cardiovascular risk. Various pathophysiological conditions are associated to changes ...

AMER PHYSIOLOGICAL SOC2021

Admissibility of Uncertain Injections in Quadratic Algebraic Systems

Jean-Yves Le Boudec, Cong Wang, Eleni Stai

We study the admissibility problem in multivariate algebraic systems, such as ac electrical networks, where the power injection is quadratic in the state. The goal of such systems is to ensure that the state stays in some security set (e.g., magnitudes of ...

2021

A new empirical challenge for local theories of consciousness

Adrien Christophe Doerig

Local theories of consciousness state that one is conscious of a feature if it is adequately represented and processed in sensory brain areas, given some background conditions. We challenge the core prediction of local theories based on long-lasting postdi ...

2021

KPC: Learning-Based Model Predictive Control with Deterministic Guarantees

Colin Neil Jones, Yuning Jiang, Paul Scharnhorst, Emilio Maddalena

We propose Kernel Predictive Control (KPC), a learning-based predictive control strategy that enjoys deterministic guarantees of safety. Noise-corrupted samples of the unknown system dynamics are used to learn several models through the formalism of non-pa ...

2021

Analytical Computation of Power Grids’ Sensitivity Coefficients with Voltage-Dependent Injections

Mario Paolone, Sherif Alaa Salaheldin Fahmy

With the increasing need of real-time regulation in power systems, grid-aware-control-frameworks are relying more often on sensitivity coefficients (SCs) to formulate and efficiently solve optimal control problems. As known, SCs are the derivatives of cont ...

IEEE2021

OPF-driven Under Frequency Load Shedding in Low-Inertia Power Grids Hosting Large-scale Battery Energy Storage Systems

Mario Paolone, Asja Derviskadic, Yihui Zuo

The paper describes the formulation and application of an Optimal Power Flow (OPF)-driven Under Frequency Load Shedding (UFLS) scheme in low-inertia power grids hosting large-scale battery energy storage systems. Thanks to the accurate prediction of the sy ...

IEEE2021

Robust Learning-Augmented Caching: An Experimental Study

Adam Teodor Polak

Effective caching is crucial for performance of modern-day computing systems. A key optimization problem arising in caching – which item to evict to make room for a new item – cannot be optimally solved without knowing the future. There are many classical ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Pipeline Synthesis and Optimization from Branched Feedback Dataflow Programs

Marco Mattavelli, Simone Casale Brunet, Endri Bezati, Anatoly Prihozhy

Large dataflow designs are a result of behavioral specification of modern complex digital systems and/or a result of unfolding and transforming looped and branched programs. Since deep-submicron silicon technology provides large amounts of available resour ...

SPRINGER2020

SpecROP: Speculative Exploitation of ROP Chains

Mathias Josef Payer, Atri Bhattacharyya, Andrés Sánchez Marín

Speculative execution attacks, such as Spectre, reuse code from the victim’s binary to access and leak secret information during speculative execution. Every variant of the attack requires very particular code sequences, necessitating elaborate gadget-sear ...

2020

Invariant states in inclined layer convection. Part 2. Bifurcations and connections between branches of invariant states

Tobias Schneider, Florian Reetz

Convection in a layer inclined against gravity is a thermally driven non-equilibrium system, in which both buoyancy and shear forces drive spatio-temporally complex flows. As a function of the strength of thermal driving and the angle of inclination, a mul ...

Cambridge University Press2020