high performance computing on graphics processing units: hgpu.org

Heiko Burau, Renee Widera, Wolfgang Honig, Guido Juckeland, Ale Debus, Thomas Kluge, Ulrich Schramm, Tomas E. Cowan, Roland Sauerbrey, Michael Bussmann

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Tags: CUDA, GPU cluster, nVidia, OpenCL, Particle-in-cell methods, Physics, Plasma physics, Tesla S1070

November 7, 2010 by hgpu

Parallel implementation of a spatio-temporal visual saliency model

A. Rahman, D. Houzet, D. Pellerin, S. Marat, N. Guyader

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 480

November 7, 2010 by hgpu

Real-time multi-agent path planning on arbitrary surfaces

Rafael P. Torchelsen, Luiz F. Scheidegger, Guilherme N. Oliveira, Rui Bastos, Joao L. D. Comba

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Tags: Computer science, CUDA, Games, Geodesic Distances, nVidia, nVidia GeForce GTX 260, Path problems

November 7, 2010 by hgpu

Real-time path-based surface detail

Carles Bosch, Gustavo Patow

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Tags: 3D Graphics and Realism, Cg, Computer science, nVidia, nVidia GeForce 8800 GTX, OpenGL, Raytracing, Rendering

November 7, 2010 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Theory of square, rectangular, and microband electrodes through explicit GPU simulation

Towards Dense Linear Algebra for Hybrid GPU Accelerated Manycore Systems

Bayesian real-time perception algorithms on GPU

Large-scale mixer simulations using massively parallel GPU architectures

Parallel Banding Algorithm to compute exact distance transform with the GPU

COMPASS: a programmable data prefetcher using idle GPU shaders

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS

Parallel hyperbolic PDE simulation on clusters: Cell versus GPU

PIConGPU: A Fully Relativistic Particle-in-Cell Code for a GPU Cluster

Parallel implementation of a spatio-temporal visual saliency model

Real-time multi-agent path planning on arbitrary surfaces

Real-time path-based surface detail

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

Most viewed papers (last 30 days)