high performance computing on graphics processing units: hgpu.org

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Efficiently Using a CUDA-enabled GPU as Shared Resource

Hagen Peters, Martin Koper, Norbert Luttenberge

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 280, Programming techniques

April 17, 2011 by hgpu

Exact and complete short read alignment to microbial genomes using GPU programming

Jochen Blom, Tobias Jakobi, Daniel Doppmeier, Sebastian Jaenicke, Jorn Kalinowski, Jens Stoye, Alexander Goesmann

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Tags: Bioinformatics, Biology, CUDA, Next-Generation sequencing, nVidia, nVidia GeForce GTX 280, Package

April 11, 2011 by hgpu

Data-parallel algorithms for large-scale real-time simulation of the cellular potts model on graphics processing units

Jose Juan Tapia, Roshan D'Souza

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Tags: Biophysics, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 280, OpenGL, Physics, Programming techniques

April 9, 2011 by hgpu

Parallel Dense Gauss-Seidel Algorithm on Many-Core Processors

H. Courtecuisse, J. Allard

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Tags: Algorithms, Computer science, CUDA, Medicine, nVidia, nVidia GeForce GTX 280, Package, Physics-based simulation, Surgical simulation

April 8, 2011 by hgpu

Parallelizing Simulated Annealing-Based Placement Using GPGPU

Alexander Choong, Rami Beidas, Jianwen Zhu

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Tags: Numerical simulation, nVidia, nVidia GeForce GTX 280, Physics

April 5, 2011 by hgpu

A Light-weight API for Portable Multicore Programming

Christopher G. Baker, Michael A. Heroux, H. Carter Edwards, Alan B. Williams

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, OpenCL, RapidMind

April 3, 2011 by hgpu

Throughput-Effective On-Chip Networks for Manycore Accelerators

Ali Bakhoda, John Kim, Tor M. Aamodt

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance

April 2, 2011 by hgpu

A characterization and analysis of PTX kernels

Andrew Kerr, Gregory Diamos, Sudhakar Yalamanchili

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Performance, PTX

April 2, 2011 by hgpu

OpenCL – An effective programming model for data parallel computations at the Cell Broadband Engine

J. Breitbart, C. Fohry

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Tags: Cell processor, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, OpenCL

March 31, 2011 by hgpu

Parallel data mining on graphics processors

Wenbin Fang, Ka Keung Lau, Mian Lu, Xiangye Xiao, Chi Kit Lam, Philip Yang Yang, Bingsheng He, Qiong Luo, Pedro V. Sander, Ke Yang

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Tags: Computer science, CUDA, Data mining, nVidia, nVidia GeForce GTX 280, Package

March 28, 2011 by hgpu

Data structure design for GPU based heterogeneous systems

Jens Breitbart

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Tags: Computer science, CUDA, Data Structures and Algorithms, Games, Heterogeneous systems, Nearest neighbour, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 280, OpenMP

March 27, 2011 by hgpu

Fast in-place sorting with CUDA based on bitonic sort

Hagen Peters, Ole Schulz-Hildebrandt, and Norbert Luttenberger

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Sorting

March 24, 2011 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

Efficiently Using a CUDA-enabled GPU as Shared Resource

Exact and complete short read alignment to microbial genomes using GPU programming

Data-parallel algorithms for large-scale real-time simulation of the cellular potts model on graphics processing units

Parallel Dense Gauss-Seidel Algorithm on Many-Core Processors

Parallelizing Simulated Annealing-Based Placement Using GPGPU

A Light-weight API for Portable Multicore Programming

Throughput-Effective On-Chip Networks for Manycore Accelerators

A characterization and analysis of PTX kernels

OpenCL – An effective programming model for data parallel computations at the Cell Broadband Engine

Parallel data mining on graphics processors

Data structure design for GPU based heterogeneous systems

Fast in-place sorting with CUDA based on bitonic sort

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

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