high performance computing on graphics processing units: hgpu.org

Kenji Ogawa, Tatsumi Aoyama, Hiroaki Ikeda, Etsuko Itou, Masafumi Kurachi, C.-J. David Lin, Hideo Matsufuru, Hiroshi Ohki, Tetsuya Onogi, Eigo Shintani, Takeshi Yamazaki

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, nVidia, Physics, QCD, Tesla C1060

November 8, 2011 by hgpu

Speculative Parallel Evaluation Of Classification Trees On GPGPU Compute Engines

Jason Spencer

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia Quadro FX 2000, Optimization, Pattern recognition

November 8, 2011 by hgpu

Functional Programming for High-Performance Computing on Heterogeneous Architectures

Sylvain Henry

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Optimization, Performance, Programming Languages, Programming techniques

November 7, 2011 by hgpu

Fast Computation of Dipole Radiation in Stratified Background Using Graphics Processing Unit

M. Quinto, S. Boutami, J. Hazart

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Tags: Algorithms, CUDA, Electrodynamics, nVidia, nVidia GeForce 8800 GTX

November 7, 2011 by hgpu

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

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

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

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Parallel Implementation of Niblack’s Binarization Approach on CUDA

GPU-based Signal Processing Scheme for Bioinspired Optical Flow

PATUS: A Code Generation and Auto-Tuning Framework For Parallel Stencil Computations

GPU Cluster with MATLAB

Acceleration of Hessenberg Reduction for Nonsymmetric Eigenvalue Problems in a Hybrid CPU-GPU Computing Environment

Graphics Processing Unit Utilization in Circuit Simulation

Performance analysis of a hybrid MPI/CUDA implementation of the NASLU benchmark

High performance massively parallel direct N-body simulations on large GPU clusters

The Infrared behavior of SU(3) Nf=12 gauge theory -about the existence of conformal fixed point-

Speculative Parallel Evaluation Of Classification Trees On GPGPU Compute Engines

Functional Programming for High-Performance Computing on Heterogeneous Architectures

Fast Computation of Dipole Radiation in Stratified Background Using Graphics Processing Unit

Recent source codes

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

ROCm's implementation of Gromacs

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

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