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Concept

SIMT

Publications associées (29)

SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Writing and optimizing application software for heterogeneous platforms including GPU units is a very difficult task that requires designer efforts and resources to consider several key elements to obtain good performance. Dataflow programming has shown to ...

2022

Practical Byzantine-resilient Stochastic Gradient Descent

Sébastien Louis Alexandre Rouault

Algorithms are everywhere. The recipe for the frangipane cake is an algorithm. If all the listed ingredients are available and the cook is sufficiently deft, after a finite number of small, well-defined steps a delicious dessert will exit the oven. Now, wh ...

EPFL2022

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

POSEIDON: Privacy-Preserving Federated Neural Network Learning

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis, Joao André Gomes de Sá e Sousa, David Jules Froelicher, Jean-Philippe Léonard Bossuat, Sinem Sav

In this paper, we address the problem of privacy-preserving training and evaluation of neural networks in an N-party, federated learning setting. We propose a novel system, POSEIDON, the first of its kind in the regime of privacy-preserving neural network ...

INTERNET SOC2021

Exploiting Flow Graph of System of ODEs to Accelerate the Simulation of Biologically-Detailed Neural Networks

Felix Schürmann, Bruno Ricardo Da Cunha Magalhães

Exposing parallelism in scientific applications has become a core requirement for efficiently running on modern distributed multicore SIMD compute architectures. The granularity of parallelism that can be attained is a key determinant for the achievable ac ...

IEEE2019

Improving Main-memory Database System Performance through Cooperative Multitasking

Georgios Psaropoulos

Database systems access memory either sequentially or randomly. Contrary to sequential access and despite the extensive efforts of computer architects, compiler writers, and system builders, random access to data larger than the processor cache has been s ...

EPFL2019

Asynchronous Simulation of Neuronal Activity

Bruno Ricardo Da Cunha Magalhães

Simulations of the electrical activity of networks of morphologically-detailed neuron models allow for a better understanding of the brain. Short time to solution is critical in order to study long biological processes such as synaptic plasticity and learn ...

EPFL2019

Asynchronous Branch-Paralle Simulation of Detailed Neuron Models

Felix Schürmann

Simulations of electrical activity of networks of morphologically detailed neuron models allow for a better understanding of the brain. State-of-the-art simulations describe the dynamics of ionic currents and biochemical processes within branching topologi ...

2019

Extreme Scalability of DFT-Based QM/MM MD Simulations Using MiMiC

Ursula Röthlisberger, Simone Meloni, Martin Peter Bircher, Viacheslav Bolnykh

We present a highly scalable DFT-based QM/MM implementation developed within MiMiC, a recently introduced multiscale modeling framework that uses a loose-coupling strategy in conjunction with a multiple-program multiple-data (MPMD) approach. The computatio ...

2019

Real-Time 3D Hand Pose Estimation with 3D Convolutional Neural Networks

Daniel Thalmann, Hui Liang

In this paper, we present a novel method for real-time 3D hand pose estimation from single depth images using 3D Convolutional Neural Networks (CNNs). Image-based features extracted by 2D CNNs are not directly suitable for 3D hand pose estimation due to th ...

IEEE COMPUTER SOC2019

Stretch: Balancing QoS and Throughput for Colocated Server Workloads on SMT Cores

Boris Robert Grot, Siddharth Gupta

In a drive to maximize resource utilization, today's datacenters are moving to colocation of latency-sensitive and batch workloads on the same server. State-of-the-art deployments, such as those at Google, colocate such diverse workloads even on a single S ...

IEEE2019

MiMiC: A Novel Framework for Multiscale Modeling in Computational Chemistry

Ursula Röthlisberger, Simone Meloni, Martin Peter Bircher, Viacheslav Bolnykh

We present a flexible and efficient framework for multiscale modeling in computational chemistry (MiMiC). It is based on a multiple-program multiple-data (MPMD) model with loosely coupled programs. Fast data exchange between programs is achieved through th ...

AMER CHEMICAL SOC2019

Heterogeneous and Inexact: Maximizing Power Efficiency of Edge Computing Sensors for Health Monitoring Applications

David Atienza Alonso, Giovanni Ansaloni, Miguel Peon Quiros, Soumya Subhra Basu, Loris Gérard Duch

In the Internet-of-Things (IoT) era, there is an increasing trend to enable intelligent behavior in edge computing sensors. Thus, a new generation of smart wearable devices for health monitoring is being developed, able to perform complex Digital Signal Pr ...

IEEE2018

Multi-Arm Self-Collision Avoidance: A Sparse Solution for a Big Data Problem

Aude Billard, Seyed Sina Mirrazavi Salehian, Nadia Barbara Figueroa Fernandez

In this work, we propose a data-driven approach for real-time self-collision avoidance in multi-arm systems. The approach consists of modeling the regions in joint-space that lead to collisions via a Self-Collision Avoidance (SCA) boundary and use it as a ...

2018

Network-Compute Co-Design for Distributed In-Memory Computing

Alexandros Daglis

The booming popularity of online services is rapidly raising the demands for modern datacenters. In order to cope with data deluge, growing user bases, and tight quality of service constraints, service providers deploy massive datacenters with tens to hund ...

EPFL2018

A Dynamically Reconfigurable Platform for High-Performance and Low-Power On-Board Processing

Paolo Ienne, Andrea Guerrieri, Sahand Kashani

FPGAs (Field Programmable Gate Array) are an attractive technology for high-speed data processing in space missions due to their unbeatable flexibility and best performance-to-power ratio in comparison to software. However FPGAs suffer from 3 major drawbac ...

IEEE2018

Parallel Inverse Kinematics for Multithreaded Architectures

Ronan Boulic, Benoît Le Callennec, Mentar Mahmudi, Pawan Kumar Harish

In this article, we present a parallel prioritized Jacobian-based inverse kinematics algorithm for multithreaded architectures. We solve damped least squares inverse kinematics using a parallel line search by identifying and sampling critical input paramet ...

Association for Computing Machinery2016

Characterization of the Impact of Hardware Islands on OLTP

Anastasia Ailamaki, Pinar Tözün, Ippokratis Pandis, Danica Porobic, Miguel Sérgio De Oliveira Branco

Modern hardware is abundantly parallel and increasingly heterogeneous. The numerous processing cores have non-uniform access latencies to the main memory and processor caches, which causes variability in the communication costs. Unfortunately, database sys ...

Springer Verlag2016

Unlocking Energy

Rachid Guerraoui, Babak Falsafi, Javier Picorel Obando, Vasileios Trigonakis

Locks are a natural place for improving the energy efficiency of software systems. First, concurrent systems are mainstream and when their threads synchronize, they typically do it with locks. Second, locks are well-defined abstractions, hence changing the ...

Usenix Assoc2016

Incorporating Perception Uncertainty in Human-Aware Navigation: A Comparative Study

Alcherio Martinoli, Zeynab Talebpour

In this work, we present a novel approach to human-aware navigation by probabilistically modelling the uncertainty of perception for a social robotic system and investigating its effect on the overall social navigation performance. The model of the social ...

Ieee2016