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Dynamical simulations of extrasolar planetary systems with debris disks using a GPU accelerated N-body code

Alexander Moore

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Tags: Astrophysics, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia Quadro FX 5800, Package, Thesis

October 27, 2013 by hgpu

Architecture-and Workload-Aware Heterogeneous Algorithms for Sparse Matrix Vector Multiplication

Sivaramakrishna Bharadwaj Indarapu, Manoj Maramreddy, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, Sparse matrix

October 21, 2013 by hgpu

Progressive Photon Mapping on GPUs

Stian Aaraas Pedersen

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Overview, Package, Raytracing, Rendering, Thesis

October 18, 2013 by hgpu

OpenACC-based Snow Simulation

Magnus Alvestad Mikalsen

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenACC, OpenCL, Performance, Tesla C2070, Tesla K20, Thesis

October 18, 2013 by hgpu

Heterogeneous FTDT for Seismic Processing

Andreas Berg Skomedal

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Tags: CUDA, Earth and Space Sciences, FDTD, Finite-difference time-domain, Geoscience, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Package, Seismology, Tesla K20, Thesis

October 18, 2013 by hgpu

Massively Parallel Lossless Compression of Medical Images Using Least-Squares Prediction and Arithmetic Coding

Andreas Weinlich, Johannes Rehm, Peter Amon, Andreas Hutter, Andre Kaup

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Tags: Compression, CUDA, Image processing, Medicine, nVidia, nVidia GeForce GTX 480

October 15, 2013 by hgpu

Power Control for GPU Clusters in processing large-scale streams

Qingkui Chen, Haifeng Wang, Bocheng Liu

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Tags: Computer science, CUDA, Energy-efficient computing, GPU cluster, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480

October 13, 2013 by hgpu

Characterizing the Challenges and Evaluating the Efficacy of a CUDA-to-OpenCL Translator

Mark Gardner, Paul Sathre, Wu-chun Feng, Gabriel Martinez

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL

October 13, 2013 by hgpu

Coupling a Generalized DEM and an SPH Models Under a Heterogeneous Massively Parallel Framework

Ricardo Canelas, Jose M. Dominguez, Rui M. L. Ferreira

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, MPI, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia GeForce GTX 680

October 12, 2013 by hgpu

Advanced Optimization Techniques for Sparse Grids on Modern Heterogeneous Systems

Alin Florindor Murarasu

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, nVidia Quadro 6000, Thesis

October 4, 2013 by hgpu

Optimizing Urban Environmental Simulations using Boinc

Aditya Vegesna

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Tags: Computer science, CUDA, Earth and Space Sciences, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 645, Thesis

September 29, 2013 by hgpu

Optimization solutions for the segmented sum algorithmic function

Alexandru Pirjan

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

September 21, 2013 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

Dynamical simulations of extrasolar planetary systems with debris disks using a GPU accelerated N-body code

Architecture-and Workload-Aware Heterogeneous Algorithms for Sparse Matrix Vector Multiplication

Progressive Photon Mapping on GPUs

OpenACC-based Snow Simulation

Heterogeneous FTDT for Seismic Processing

Massively Parallel Lossless Compression of Medical Images Using Least-Squares Prediction and Arithmetic Coding

Power Control for GPU Clusters in processing large-scale streams

Characterizing the Challenges and Evaluating the Efficacy of a CUDA-to-OpenCL Translator

Coupling a Generalized DEM and an SPH Models Under a Heterogeneous Massively Parallel Framework

Advanced Optimization Techniques for Sparse Grids on Modern Heterogeneous Systems

Optimizing Urban Environmental Simulations using Boinc

Optimization solutions for the segmented sum algorithmic function

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)