Publications related to Tegra | EPFL Graph Search

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

Anastasia Ailamaki, Periklis Chrysogelos, Hamish Mcniece Hill Nicholson, Syed Mohammad Aunn Raza

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

2023

HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration

David Atienza Alonso, Tomas Teijeiro Campo, William Andrew Simon, Una Pale

The HyperDimensional Computing (HDC) Machine Learning (ML) paradigm is highly interesting for applications involving continuous, semi-supervised learning for long-term monitoring. However, its accuracy is not yet on par with other ML approaches, necessitat ...

Association for Computing MachineryNew YorkNYUnited States2022

Gem5-X : A Many-Core Heterogeneous Simulation Platform for Architectural Exploration and Optimization

David Atienza Alonso, Marina Zapater Sancho, William Andrew Simon, Yasir Mahmood Qureshi

The increasing adoption of smart systems in our daily life has led to the development of new applications with varying performance and energy constraints, and suitable computing architectures need to be developed for these new applications. In this paper, ...

2021

Programming Heterogeneous CPU-GPU Systems by High-Level Dataflow Synthesis

Marco Mattavelli, Endri Bezati, Aurélien François Gilbert Bloch

Heterogeneous processing platforms combining in various architectures CPUs, GPUs, and programmable logic, are continuously evolving providing at each generation higher theoretical levels of computing performance. However, the challenge of how efficiently s ...

IEEE2020

BLADE: A BitLine Accelerator for Devices on the Edge

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, William Andrew Simon, Yasir Mahmood Qureshi

The increasing ubiquity of edge devices in the consumer market, along with their ever more computationally expensive workloads, necessitate corresponding increases in computing power to support such workloads. In-memory computing is attractive in edge devi ...

2019

Porting a Legacy Global Lagrangian PIC Code on Many-Core and GPU-Accelerated Architectures

Laurent Villard, Stephan Brunner, Emmanuel Lanti, Noé Thomas Elie Ohana, Claudio Gheller, Aaron Lewis Scheinberg

Modern supercomputer architectures are evolving towards embedding more and more cores per compute node, often making use of accelerators such as GPUs, in which thousands of threads can be executed concurrently. To make legacy codes profit efficiently from ...

2018

Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography

Theo Lasser, Paul James Marchand, Daniel Pawel Szlag, Marcin Antoni Sylwestrzak

We present an application of massively parallel processing of quantitative flow measurements data acquired using spectral optical coherence microscopy (SOCM). The need for massive signal processing of these particular datasets has been a major hurdle for m ...

Elsevier2017

A Single-chip 2048x1080 Resolution 32fps 380mW Trinocular Disparity Estimation Processor in 28nm CMOS Technology

Yusuf Leblebici, Abdulkadir Akin, Tugba Demirci, Jonathan Emmanuel D Narinx

This paper presents a single-chip trinocular disparity estimation processor, capable of computing in real-time up to 2048×1080 resolution depth maps at 32fps with up to 256-pixel disparity range using two/three CMOS camera sensors. The most important featu ...

2017

A portable platform for accelerated PIC codes and its application to GPUs using OpenACC

Laurent Villard, Stephan Brunner, Emmanuel Lanti, Trach-Minh Tran, Claudio Gheller

We present a portable platform, called PIC_ENGINE, for accelerating Particle-In-Cell (PIC) codes on heterogeneous many-core architectures such as Graphic Processing Units (GPUs). The aim of this development is efficient simulations on future exascale syste ...

Elsevier Science Bv2016

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Tegra

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration

Gem5-X : A Many-Core Heterogeneous Simulation Platform for Architectural Exploration and Optimization

Programming Heterogeneous CPU-GPU Systems by High-Level Dataflow Synthesis

BLADE: A BitLine Accelerator for Devices on the Edge

Porting a Legacy Global Lagrangian PIC Code on Many-Core and GPU-Accelerated Architectures

Exploring the interoperability of remote GPGPU virtualization using rCUDA and directive-based programming models

Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography

A Single-chip 2048x1080 Resolution 32fps 380mW Trinocular Disparity Estimation Processor in 28nm CMOS Technology

A portable platform for accelerated PIC codes and its application to GPUs using OpenACC

Graph Chatbot

Chat with Graph Search

Gem5-X : A Many-Core Heterogeneous Simulation Platform for Architectural Exploration and Optimization

Exploring the interoperability of remote GPGPU virtualization using rCUDA and directive-based programming models

A Single-chip 2048x1080 Resolution 32fps 380mW Trinocular Disparity Estimation Processor in 28nm CMOS Technology

HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration

A portable platform for accelerated PIC codes and its application to GPUs using OpenACC

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

BLADE: A BitLine Accelerator for Devices on the Edge

Programming Heterogeneous CPU-GPU Systems by High-Level Dataflow Synthesis

Porting a Legacy Global Lagrangian PIC Code on Many-Core and GPU-Accelerated Architectures

Massively parallel data processing for quantitative total flow imaging with optical coherence microscopy and tomography