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Assessing the feasibility of OpenCL CPU implementations for agent-based simulations

Nuno Fachada, Agostinho C. Rosa

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Tags: Agent-based modeling, AMD, cpu, Intel, OpenCL, simulation

July 24, 2019 by fakenmc

APUNet: Revitalizing GPU as Packet Processing Accelerator

Younghwan Go, Muhammad Jamshed, YoungGyoun Moon, Changho Hwang, KyoungSoo Park

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Tags: Algorithms, AMD, APU, ATI, Computer science, nVidia, nVidia GeForce GTX 980, OpenCL, Performance

March 28, 2017 by hgpu

TREES: A CPU/GPU Task-Parallel Runtime with Explicit Epoch Synchronization

Blake A. Hechtman, Andrew D. Hilton, Daniel J. Sorin

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Tags: AMD, APU, Computer science, OpenCL, Operating systems, Programming Languages

August 4, 2016 by hgpu

Fast reconstruction of 3D volumes from 2D CT projection data with GPUs

M. Leeser, S. Mukherjee, J. Brock

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Tags: AMD, AMD Radeon HD 7970, Computed tomography, CT, CUDA, Heterogeneous systems, Medicine, nVidia, OpenCL, Tesla C2075

September 1, 2014 by hgpu

Implementation of Just In Time Value Specialization for the Optimization of Data Parallel Kernels

N. Tuck

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Tags: AMD, ATI Radeon 5830, High-level Languages, nVidia, nVidia GeForce GTX 650 Ti, OpenCL, Programming techniques, Thesis

March 28, 2014 by hgpu

Multi-tier Dynamic Vectorization for Translating GPU Optimizations into CPU Performance

Hee-Seok Kim, Izzat El Hajj, John A. Stratton, Wen-Mei W. Hwu

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Tags: AMD, Computer science, nVidia, OpenCL, Performance

February 12, 2014 by hgpu

Hybrid strategy for stencil computations on the APU

Pacome Eberhart, Issam Said, Pierre Fortin

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Tags: AMD, APU, Computer science, Numerical Analysis, OpenCL, Partial differential equations

January 26, 2014 by hgpu

OmniDB: Towards Portable and Efficient Query Processing on Parallel CPU/GPU Architectures

Shuhao Zhang, Jiong He, Bingsheng He, Mian Lu

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Tags: AMD, APU, ATI, ATI FirePro V7800, Computer science, Databases, nVidia Quadro K5000, OpenCL

July 12, 2013 by hgpu

A Computing Kernel for Network Binarization on PyTorch

A Computing Kernel for Network Binarization on PyTorch

Deep Learning Based FPGA-CPU Acceleration

Deep Learning Based FPGA-CPU Acceleration

KTT: Kernel Tuning Toolkit

Framework for Parallel Kernels Auto-tuning

SHA512AOCLStudy

Study of OpenCL Processing Models for FPGA Devices

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

KLARAPTOR: A Tool for Dynamically Finding Optimal Kernel Launch Parameters Targeting CUDA Programs

JSDoop

JSDoop and TensorFlow.js: Volunteer Distributed Web Browser-Based Neural Network Training

FPGA CNN Acceleration

Research on OpenCL optimization for FPGA deep learning application

PyTorchPipe: a framework for rapid prototyping of pipelines combining language and vision

PyTorchPipe: a framework for rapid prototyping of pipelines combining language and vision

Performance Evaluation of Advanced Features in CUDA Unified Memory

Performance Evaluation of Advanced Features in CUDA Unified Memory

SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs

SneakySnake: A Fast and Accurate Universal Genome Pre-Alignment Filter for CPUs, GPUs, and FPGAs

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2020

April

27-29

Munich, Germany

8th International Workshop on OpenCL, including SYCLCon, 2019

2019

May

13-15

Boston, USA

7th International Workshop on OpenCL, 2019

2019

May

13

Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

May

14

Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

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