high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia Quadro P 5000

Cracks in the Sky: Abelian-Higgs Cosmic String Evolution with CUDA

J. R. C. C. C. Correia, C. J. A. P. Martins

View

Tags: Computational Physics, CUDA, High Energy Physics - Phenomenology, nVidia, nVidia Quadro P 5000, Physics

September 9, 2018 by hgpu

EASYPAP: a Framework for Learning Parallel Programming

EASYPAP: a Framework for Learning Parallel Programming

LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment

LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment

StarNEig: A Task-based Library for Solving Nonsymmetric Eigenvalue Problems

Task-based, GPU-accelerated and Robust Library for Solving Dense Nonsymmetric Eigenvalue Problems

FLAMEGPU: a high performance GPU extension to the FLAME framework

Working With Incremental Spatial Data During Parallel (GPU) Computation

CommAnalyzer

Automated Runtime Analysis and Adaptation for Scalable Heterogeneous Computing

elevate: implementation of the Elevate language

A Language for Describing Optimization Strategies

reproducibility of TensorFlow with ResNet

Non-Determinism in TensorFlow ResNets

SCHNAPS

Optimization of a discontinuous Galerkin solver with OpenCL and StarPU

Interoperable GPU Kernels as Latency Improver for MEC

Interoperable GPU Kernels as Latency Improver for MEC

MNN: a lightweight deep neural network inference engine

An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices

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: