Publications associées à OpenCL

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

WR2A: A Very-Wide-Register Reconfigurable-Array Architecture for Low-Power Embedded Devices

David Atienza Alonso, Miguel Peon Quiros, Benoît Walter Denkinger

Edge-computing requires high-performance energy-efficient embedded systems. Fixed-function or custom accelerators, such as FFT or FIR filter engines, are very efficient at implementing a particular functionality for a given set of constraints. However, the ...

2022

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

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

ExG Signal Feature Selection Using Hyperdimensional Computing Encoding

David Atienza Alonso, Tomas Teijeiro Campo, Una Pale

Wearable IoT devices and novel continuous monitoring algorithms are essential components of the healthcare transition from reactive interventions focused on symptom treatment to more proactive prevention, from one-size-fits-all to personalized medicine, an ...

IEEE2022

On the Efficiency of OpenACC-aided GPU-Based FDTD Approach: Application to Lightning Electromagnetic Fields

Mohammad Azadifar, Hamidreza Karami

An open accelerator (OpenACC)-aided graphics processing unit (GPU)-based finite difference time domain (FDTD) method is presented for the first time for the 3D evaluation of lightning radiated electromagnetic fields along a complex terrain with arbitrary t ...

MDPI2020

AdaptHD: Adaptive Efficient Training for Brain-Inspired Hyperdimensional Computing

Giovanni De Micheli, Samuel Bosch, Mohsen Imani

Brain-inspired Hyperdimensional (HD) computing is a promising solution for energy-efficient classification. However, the existing HD computing algorithms have a lack of controllability on the training iterations which often results in slow training or dive ...

2019

Object-Oriented Recovery for Non-volatile Memory

James Richard Larus, David Teksen Aksun, Nachshon Cohen

New non-volatile memory (NVM) technologies enable direct, durable storage of data in an application's heap. Durable, randomly accessible memory facilitates the construction of applications that do not lose data at system shutdown or power failure. Existing ...

ACM2018

LTRF: Enabling High-Capacity Register Files for GPUs via Hardware/Software Cooperative Register Prefetching

Babak Falsafi, Mario Paulo Drumond Lages De Oliveira, Hamid Sarbazi-Azad, Seyed Borna Ehsani

Graphics Processing Units (GPUs) employ large register files to accommodate all active threads and accelerate context switching. Unfortunately, register files are a scalability bottleneck for future GPUs due to long access latency, high power consumption, ...

2018

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OpenCL

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

WR2A: A Very-Wide-Register Reconfigurable-Array Architecture for Low-Power Embedded Devices

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

SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

ExG Signal Feature Selection Using Hyperdimensional Computing Encoding

A review of CUDA optimization techniques and tools for structured grid computing

On the Efficiency of OpenACC-aided GPU-Based FDTD Approach: Application to Lightning Electromagnetic Fields

AdaptHD: Adaptive Efficient Training for Brain-Inspired Hyperdimensional Computing

Object-Oriented Recovery for Non-volatile Memory

LTRF: Enabling High-Capacity Register Files for GPUs via Hardware/Software Cooperative Register Prefetching

Graph Chatbot

Chattez avec Graph Search

ExG Signal Feature Selection Using Hyperdimensional Computing Encoding

AdaptHD: Adaptive Efficient Training for Brain-Inspired Hyperdimensional Computing

On the Efficiency of OpenACC-aided GPU-Based FDTD Approach: Application to Lightning Electromagnetic Fields

A review of CUDA optimization techniques and tools for structured grid computing

Object-Oriented Recovery for Non-volatile Memory

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

WR2A: A Very-Wide-Register Reconfigurable-Array Architecture for Low-Power Embedded Devices

LTRF: Enabling High-Capacity Register Files for GPUs via Hardware/Software Cooperative Register Prefetching

SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

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