high performance computing on graphics processing units: hgpu.org

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A master-slave robotic simulator based on GPUDirect

Jianying. Li, Yu. Guo, Heye. Zhang, Yongming. Xie

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Tags: CUDA, Medicine, nVidia, Tesla S1070, Virtual reality

January 13, 2013 by hgpu

Distributed Massive Model Rendering

Revanth N R, P. J. Narayanan

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia Quadro FX 3700 M, Rendering, Tesla C2050, Tesla C2070, Tesla S1070

January 8, 2013 by hgpu

Accelerating Haskell Array Codes with Algorithmic Skeletons on GPUs

Sean Youngsung Lee

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Tags: Algorithms, Computer science, CUDA, nVidia, Tesla S1070, Thesis

December 18, 2012 by hgpu

Multi-level Parallelism for Incompressible Flow Computations on GPU Clusters

Dana A. Jacobsen, Inanc Senocak

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Tags: Computer science, CUDA, Fluid dynamics, GPU cluster, MPI, nVidia, Tesla C1060, Tesla S1070

December 12, 2012 by hgpu

A Framework for Automated Generation of Specialized Function Variants

Nicholas Chaimov

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Tags: Cloud, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, Optimization, Tesla C2070, Tesla S1070, Thesis

November 6, 2012 by hgpu

An Environment to Support GPU and Multicore Programming for Rapid, High Performance, Application Deployment

James Laurence Brock

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Tags: ATI, ATI Radeon HD 5870, Computer science, CUDA, Heterogeneous systems, Image reconstruction, Monte Carlo simulation, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 560 Ti, OpenCL, Tesla C1060, Tesla S1070, Thesis

October 26, 2012 by hgpu

GPU-Based Asynchronous Global Optimization with Particle Swarm

M. P. Wachowiak, A. E. Lambe Foster

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Tags: Biological Physics, Computational Physics, CUDA, nVidia, Particle swarm optimization, Physics, Tesla S1070

October 25, 2012 by hgpu

Programming NVIDIA cards by means of transitive closure based parallelization algorithms

Marek Palkowski, Wlodzimierz Bielecki

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Tags: Computer science, CUDA, nVidia, Performance, Tesla S1070

October 13, 2012 by hgpu

Dense Matrix Computation on a Heterogenous Architecture: A Block Synchronous Approach

Kyungjoo Kim, Victor Eijkhout, Robert A. van de Geijn

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Source codes

Tags: Computer science, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Package, Tesla M2070, Tesla S1070

August 13, 2012 by hgpu

Optimising Cosmological N-body Simulations in GPU Clusters

Santanu T

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Tags: Astrophysics, Cosmology, CUDA, GPU cluster, MPI, N-body simulation, nVidia, Tesla S1070, Thesis

July 25, 2012 by hgpu

Efficient Parallel RSA Decryption Algorithm for Many-core GPUs with CUDA

Yu-Shiang Lin, Chun-Yuan Lin, Der-Chyuan Lou

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Security, Tesla C2050, Tesla S1070

July 7, 2012 by hgpu

An Adaptative Multi-GPU based Branch-and-Bound. A Case Study: the Flow-Shop Scheduling Problem

Imen Chakroun, Nouredine Melab

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Tags: Computer science, CUDA, GPU cluster, nVidia, Optimization, Tesla S1070

June 25, 2012 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

A master-slave robotic simulator based on GPUDirect

Distributed Massive Model Rendering

Accelerating Haskell Array Codes with Algorithmic Skeletons on GPUs

Multi-level Parallelism for Incompressible Flow Computations on GPU Clusters

An Environment to Support GPU and Multicore Programming for Rapid, High Performance, Application Deployment

GPU-Based Asynchronous Global Optimization with Particle Swarm

Programming NVIDIA cards by means of transitive closure based parallelization algorithms

Dense Matrix Computation on a Heterogenous Architecture: A Block Synchronous Approach

Optimising Cosmological N-body Simulations in GPU Clusters

Efficient Parallel RSA Decryption Algorithm for Many-core GPUs with CUDA

An Adaptative Multi-GPU based Branch-and-Bound. A Case Study: the Flow-Shop Scheduling Problem

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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