high performance computing on graphics processing units: hgpu.org

Clemens Grelck, Kevin Hammond, Heinz Hertlein, Philip Holzenspies, Chris Jesshope, Raimund Kirner, Bernd Scheuermann, Alex Shafarenko, Iraneus Te Boekhorst, Volkmar Wieser

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 425 M, Performance, Visualization

December 29, 2011 by hgpu

Parallel computing system for the efficient calculation of molecular similarity based on negative electrostatic potential

Raul Ernesto Torres Carvajal

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Tags: Algorithms, Chemistry, Cluster analysis, CUDA, Electrostatic potential, Electrostatics, nVidia, nVidia GeForce GT 240, Pattern recognition, Thesis

December 29, 2011 by hgpu

Parallel Quadtree Coding of Large-Scale Raster Geospatial Data on Multicore CPUs and GPGPUs

Jianting Zhang, Simin You, Le Gruenwald

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Tags: CUDA, Data parallelism, Earth and Space Sciences, Geoscience, nVidia, Optimization, Sensing, Tesla C2050

December 29, 2011 by hgpu

Accelerating NBODY6 with Graphics Processing Units

Keigo Nitadori, Sverre J. Aarseth

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Tags: Astrophysics, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 560 Ti, Package

December 29, 2011 by hgpu

Improving the speed of neural networks on CPUs

Vincent Vanhoucke, Andrew Senior, Mark Z. Mao

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Tags: Computer science, CUDA, Neural networks, nVidia, Speech recognition, Tesla C2070, Tutorial

December 28, 2011 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

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high performance computing on graphics processing units: hgpu.org

Torch7: A Matlab-like Environment for Machine Learning

A 3D Convex Hull Algorithm for Graphics Hardware

Faster Dark Matter Calculations Using the GPU

Building Human Brain Network in 3D Coefficient Map Determined by X-ray Microtomography

Acceleration of PIC Simulation with GPU

Scalable Fast Multipole Methods on Distributed Heterogeneous Architectures

Parallelism, Patterns, and Performance in Iterative MRI Reconstruction

Engineering Concurrent Software Guided by Statistical Performance Analysis

Parallel computing system for the efficient calculation of molecular similarity based on negative electrostatic potential

Parallel Quadtree Coding of Large-Scale Raster Geospatial Data on Multicore CPUs and GPGPUs

Accelerating NBODY6 with Graphics Processing Units

Improving the speed of neural networks on CPUs

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)