high performance computing on graphics processing units: hgpu.org

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Supercomputing and stellar dynamics

R. Capuzzo-Dolcetta

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Tags: Astrophysics, Celestial mechanics, Galaxy Astrophysics, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, OpenMP, Stellar dynamics, Tesla C1060

November 13, 2010 by hgpu

QYMSYM: A GPU-Accelerated Hybrid Symplectic Integrator That Permits Close Encounters

Alexander Moore, Alice C. Quillen

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Tags: Astrophysics, Celestial mechanics, CUDA, Earth and Planetary Astrophysics, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Package

November 10, 2010 by hgpu

EASYPAP: a Framework for Learning Parallel Programming

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

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

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high performance computing on graphics processing units: hgpu.org

Supercomputing and stellar dynamics

QYMSYM: A GPU-Accelerated Hybrid Symplectic Integrator That Permits Close Encounters

Recent source codes

EASYPAP: a Framework for Learning Parallel Programming

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

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

FLAMEGPU: a high performance GPU extension to the FLAME framework

CommAnalyzer

elevate: implementation of the Elevate language

reproducibility of TensorFlow with ResNet

SCHNAPS

Interoperable GPU Kernels as Latency Improver for MEC

MNN: a lightweight deep neural network inference engine

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Featured events

8th International Workshop on OpenCL, including SYCLCon, 2019

7th International Workshop on OpenCL, 2019

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

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

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