Publications associées à Compute kernel

Overflow-free compute memories for edge AI acceleration

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

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can ...

2023

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

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Edoardo Charbon, Andrei Ardelean, Mohit Gupta

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon ...

Ieee Computer Soc2023

Training Efficient Controllers via Analytic Policy Gradient

Dario Floreano, Valentin Wüest, Davide Scaramuzza

Control design for robotic systems is complex and often requires solving an optimization to follow a trajectory accurately. Online optimization approaches like Model Predictive Control (MPC) have been shown to achieve great tracking performance, but requir ...

2023

Dynamic SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Developing and fine-tuning software programs for heterogeneous hardware such as CPU/GPU processing platforms comprise a highly complex endeavor that demands considerable time and effort of software engineers and requires evaluating various fundamental comp ...

MDPI2022

System Support for Robust Distributed Learning

Arsany Hany Abdelmessih Guirguis

Machine learning (ML) applications are ubiquitous. They run in different environments such as datacenters, the cloud, and even on edge devices. Despite where they run, distributing ML training seems the only way to attain scalable, high-quality learning. B ...

EPFL2022

Neural Joint Space Implicit Signed Distance Functions for Reactive Robot Manipulator Control

Aude Billard, Mikhail Koptev, Nadia Barbara Figueroa Fernandez

In this paper, we present an approach for learning a neural implicit signed distance function expressed in joint space coordinates, that efficiently computes distance-to-collisions for arbitrary robotic manipulator configurations. Computing such distances ...

2022

DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks

Mirjana Stojilovic, Dina Gamaleldin Ahmed Shawky Mahmoud, David Dervishi

Field-programmable gate arrays (FPGAs) combine hardware reconfigurability with a high degree of parallelism. Consequently, FPGAs offer performance gains and power savings for many applications. A recent trend has been to leverage the hardware versatility o ...

2022

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

The performance of programs written in languages following the dataflow model of computation (MoC) largely depends on the configuration (partitioning, mapping, scheduling, buffer dimensioning) chosen during the synthesis stages. Furthermore, this programmi ...

2022

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Compute kernel

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Overflow-free compute memories for edge AI acceleration

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

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Training Efficient Controllers via Analytic Policy Gradient

Dynamic SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

System Support for Robust Distributed Learning

Neural Joint Space Implicit Signed Distance Functions for Reactive Robot Manipulator Control

DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms

Graph Chatbot

Chattez avec Graph Search

Overflow-free compute memories for edge AI acceleration

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms

Neural Joint Space Implicit Signed Distance Functions for Reactive Robot Manipulator Control

Dynamic SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

System Support for Robust Distributed Learning

SoDaCam: Software-defined Cameras via Single-Photon Imaging

DFAulted: Analyzing and Exploiting CPU Software Faults Caused by FPGA-Driven Undervolting Attacks

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Training Efficient Controllers via Analytic Policy Gradient

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