high performance computing on graphics processing units: hgpu.org

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Accelerating a Novel Particle-based Fluid Simulation on the GPU

Zhilu Chen, James Kingsley, Xinming Huang, Erkan Tuzel

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Tags: CUDA, Fluid dynamics, Fluid simulation, nVidia, Tesla C2050

November 8, 2013 by hgpu

GooFit: A library for massively parallelising maximum-likelihood fits

R. Andreassen, B. T. Meadows, M. de Silva, M. D. Sokoloff, K. Tomko

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Tags: Computer science, CUDA, Mathematical Software, nVidia, nVidia GeForce GT 650 M, Package, Probability, Tesla C2050, Tesla C2070

November 8, 2013 by hgpu

Batch Method for Efficient Resource Sharing in Real-time Multi-GPU Systems

Uri Verner, Avi Mendelson, Assaf Schuster

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Tags: Computer science, CUDA, nVidia, OpenCL, Performance, Task scheduling, Tesla C2050, Tesla K10

November 4, 2013 by hgpu

Fast 3D Salient Region Detection in Medical Images using GPUs

Rahul Thota, Sharan Vaswani, Amit Kale, Nagavijayalakshmi Vydyanathan

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Tesla C2050

November 3, 2013 by hgpu

Tridiagonalization of a dense symmetric matrix on multiple GPUs and its application to symmetric eigenvalue problems

Ichitaro Yamazaki, Tingxing Dong, Raffaele Solca, Stanimire Tomov, Jack Dongarra, Thomas Schulthess

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, Tesla C2050, Tesla M2090

November 2, 2013 by hgpu

Online Performance Projection for Clusters with Heterogeneous GPUs

Lokendra S. Panwar, Ashwin M. Aji, Jiayuan Mengz, Pavan Balajiy, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Computer science, GPGPU-sim, GPU cluster, Heterogeneous systems, nVidia, OpenCL, Performance, Tesla C1060, Tesla C2050

October 25, 2013 by hgpu

A Framework for Management of Distributed Data Processing and Event Selection for the Icecube Neutrino Observatory

Juan Carlos Diaz Velez

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Tags: CUDA, High Energy Physics - Experiment, nVidia, Physics, Python, Tesla C1060, Tesla C2050, Tesla M2070, Thesis

October 24, 2013 by hgpu

Efficient fine grained shared buffer management for multiple OpenCL devices

Chang-qing Xun, Dong Chen, Qiang Lan, Chun-yuan Zhang

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Tags: Computer science, Heterogeneous systems, Memory model, nVidia, OpenCL, Tesla C2050

October 19, 2013 by hgpu

Construction of a Virtual Cluster by Integrating PCI Pass-Through for GPU and InfiniBand Virtualization in Cloud

Chao-Tung Yang, Wei-Shen Ou

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Tags: Cloud, Cluster computing, Computer science, CUDA, GPU cluster, nVidia, Tesla C2050, Tesla C2070, Tesla C2075, Tesla K20, Virtualization

October 19, 2013 by hgpu

Efficient SVM Training Using Parallel Primal-Dual Interior Point Method on GPU

Jing Jin, Xianggao Cai, Xiaola Lin

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, Tesla C2050

October 18, 2013 by hgpu

Empirical performance modeling of GPU kernels using active learning

Prasanna Balaprakash, Karl Rupp, Azamat Mametjanov, Robert B. Gramacy, Paul D. Hovland, Stefan M. Wild

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 470, OpenCL, Performance, Tesla C2050, Tesla K20

October 17, 2013 by hgpu

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Darragh G McArt, Peter Bankhead, Philip D Dunne, Manuel Salto-Tellez, Peter Hamilton, Shu-Dong Zhang

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Tags: Bioinformatics, Biology, CUDA, nVidia, Package, Tesla C2050

October 17, 2013 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

Accelerating a Novel Particle-based Fluid Simulation on the GPU

GooFit: A library for massively parallelising maximum-likelihood fits

Batch Method for Efficient Resource Sharing in Real-time Multi-GPU Systems

Fast 3D Salient Region Detection in Medical Images using GPUs

Tridiagonalization of a dense symmetric matrix on multiple GPUs and its application to symmetric eigenvalue problems

Online Performance Projection for Clusters with Heterogeneous GPUs

A Framework for Management of Distributed Data Processing and Event Selection for the Icecube Neutrino Observatory

Efficient fine grained shared buffer management for multiple OpenCL devices

Efficient SVM Training Using Parallel Primal-Dual Interior Point Method on GPU

Empirical performance modeling of GPU kernels using active learning

cudaMap: a GPU accelerated program for gene expression connectivity mapping

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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