high performance computing on graphics processing units: hgpu.org

hgpu.org » AMD

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

Nuno Fachada, Agostinho C. Rosa

View

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

View

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

View

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

View

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

View

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

View

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

View

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

View

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

July 12, 2013 by hgpu

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures

Learnergy: a Python library for energy-based machine learning models

Learnergy: Energy-based Machine Learners

Towards automated kernel selection in machine learning systems: A SYCL case study

Towards automated kernel selection in machine learning systems: A SYCL case study

CLFuzz

Automated test generation for OpenCL kernels using fuzzing and constraint solving

High-Performance Graph Primitives on GPUs

Fast Gunrock Subgraph Matching (GSM) on GPUs

Inline Vector Compression for Computational Physics

Inline Vector Compression for Computational Physics

AvA: Automatic virtualization of (general) accelerators

AvA: Accelerated Virtualization of Accelerators

GPGPU Verification of Radix Sort

Let’s sort this out: GPGPU Verification of Radix Sort

See all packages

* * *

* * *

* * *

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

+

HGPU group © 2010-2020 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: