high performance computing on graphics processing units: hgpu.org

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CudaChain: A Practical GPU-accelerated 2D Convex Hull Algorithm

Gang Mei

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Tags: Computational Geometry, Computer science, CUDA, nVidia, nVidia GeForce GT 640, nVidia GeForce GTX 660 M, Sorting

August 27, 2015 by hgpu

gScan: Accelerating Graham Scan on the GPU

Gang Mei

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Tags: Algorithms, Computational Geometry, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GT 640, nVidia GeForce GTX 660 M, Sorting

August 27, 2015 by hgpu

Comparison between GPU and parallel CPU optimizations in viewshed analysis

Tobias Axell, Mattias Friden

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 660 M, OpenCL, Thesis

July 24, 2015 by hgpu

Unsupervised Asset Cluster Analysis Implemented with Parallel Genetic Algorithms on the NVIDIA CUDA Platform

Dariusz Cieslakiewicz

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Tags: Algorithms, Cluster analysis, Clustering, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 660 M, Thesis

July 18, 2014 by hgpu

The Use of GPUs for Solving the Computed Tomography Problem

A.E. Kovtanyuk

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Tags: Computed tomography, CT, CUDA, Image processing, nVidia, nVidia GeForce GTX 660 M, nVidia GeForce GTX 690, Tomography

July 17, 2014 by hgpu

An unsupervised parallel genetic cluster algorithm for graphics processing units

D. Hendricks, D. Cieslakiewicz, D. Wilcox, T. Gebbie

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Tags: Clustering, Computational finance, CUDA, Genetic programming, nVidia, nVidia GeForce 560 Ti, nVidia GeForce 660 Ti, nVidia GeForce GTX 660 M

March 23, 2014 by hgpu

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

M.G.B. Johnson, D. P. Playne, K.A. Hawick

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 660 M, nVidia GeForce GTX 680, Performance, Tesla M2050, Tesla M2070, Tesla M2075, Tesla M2090

March 6, 2014 by hgpu

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

CudaChain: A Practical GPU-accelerated 2D Convex Hull Algorithm

gScan: Accelerating Graham Scan on the GPU

Comparison between GPU and parallel CPU optimizations in viewshed analysis

Unsupervised Asset Cluster Analysis Implemented with Parallel Genetic Algorithms on the NVIDIA CUDA Platform

The Use of GPUs for Solving the Computed Tomography Problem

An unsupervised parallel genetic cluster algorithm for graphics processing units

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

Recent source codes

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

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

Most viewed papers (last 30 days)