high performance computing on graphics processing units: hgpu.org

Programming

A Haptic Device Interface for Medical Simulations using OpenCL

Mattias Machwirth

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Tags: Algorithms, ATI, ATI Radeon HD 5750, ATI Radeon HD 7610 M, ATI Radeon HD 7970, Medicine, OpenCL, Thesis, Ultrasound, Visualization

August 14, 2013 by hgpu

Speech Recognition on Multi-Core Processors and GPUs

Patrick Cardinal

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Tags: Algorithms, CUDA, nVidia, nVidia GeForce GTX 295, Signal processing, Speech recognition, Thesis

August 13, 2013 by hgpu

Barrier Invariants: A Shared State Abstraction for the Analysis of Data-Dependent GPU Kernels

Nathan Chong, Alastair F. Donaldson, Paul H.J. Kelly, Jeroen Ketema, Shaz Qadeer

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Tags: Algorithms, Computer science, CUDA, OpenCL, Package, Performance

August 13, 2013 by hgpu

Achieving Speedup in Aggregate Risk Analysis using Multiple GPUs

A. K. Bahl, O. Baltzer, A. Rau-Chaplin, B. Varghese, A. Whiteway

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Tags: Algorithms, Computer science, CUDA, Finance, nVidia, Risk Management, Stochastic simulation, Tesla C2075, Tesla M2090

August 13, 2013 by hgpu

GPU Computing in Discrete Optimization. Part II: Survey Focused on Routing Problems

Christian Schulz, Geir Hasle, Andre R. Brodtkorb, Trond R. Hagen

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Optimization, Tutorial

August 12, 2013 by hgpu

GPU Computing in Discrete Optimization. Part I: Introduction to the GPU

Andre R. Brodtkorb, Trond R. Hagen, Christian Schulz, Geir Hasley

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Optimization, Tutorial

August 12, 2013 by hgpu

Parallel Simulations for Analysing Portfolios of Catastrophic Event Risk

Aman Bahl, Oliver Baltzer, Andrew Rau-Chaplin, Blesson Varghese

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Tags: Algorithms, Computational Engineering, Computer science, CUDA, Finance, Monte Carlo simulation, nVidia, Stochastic simulation, Tesla C2075

August 12, 2013 by hgpu

A Memory Efficient Algorithm for Adaptive Multidimensional Integration with Multiple GPUs

Kamesh Arumugam, Alexander Godunov, Desh Ranjan, Balsa Terzic, Mohammad Zubair

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Tags: Algorithms, Computer science, CUDA, Mathematics, MPI, nVidia, Optimization, Package, Tesla M2090

August 12, 2013 by hgpu

A Parallel Algorithm for Calculation of Large Determinants with High Accuracy for GPUs and MPI clusters

Gleb Beliakov, Yuri Matiyasevich

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Tags: Algorithms, Computer science, CUDA, Mathematical Software, MPI, Number Theory, Numerical Analysis, nVidia, Tesla C2070

August 12, 2013 by hgpu

Heterogeneous Computing for Real-Time Stereo Matching

A. AL-Marakeby, M. Zaki

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GT 610 M, Stereo vision

August 10, 2013 by hgpu

Analyzing Optimization Techniques for Power Efficiency on Heterogeneous Platforms

Yash Ukidave, David Kaeli

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Tags: Algorithms, ATI, ATI Radeon HD 7770, Computer science, FFT, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL, Power-efficient computing

August 10, 2013 by hgpu

PixelPie: Maximal Poisson-disk Sampling with Rasterization

Cheuk Yiu Ip, M. Adil Yalcin, David Luebke, Amitabh Varshney

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Tags: Algorithms, Computer science, CUDA, Image generation, nVidia, nVidia GeForce GTX 580, OpenGL, Rasterization

August 10, 2013 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

A Haptic Device Interface for Medical Simulations using OpenCL

Speech Recognition on Multi-Core Processors and GPUs

Barrier Invariants: A Shared State Abstraction for the Analysis of Data-Dependent GPU Kernels

Achieving Speedup in Aggregate Risk Analysis using Multiple GPUs

GPU Computing in Discrete Optimization. Part II: Survey Focused on Routing Problems

GPU Computing in Discrete Optimization. Part I: Introduction to the GPU

Parallel Simulations for Analysing Portfolios of Catastrophic Event Risk

A Memory Efficient Algorithm for Adaptive Multidimensional Integration with Multiple GPUs

A Parallel Algorithm for Calculation of Large Determinants with High Accuracy for GPUs and MPI clusters

Heterogeneous Computing for Real-Time Stereo Matching

Analyzing Optimization Techniques for Power Efficiency on Heterogeneous Platforms

PixelPie: Maximal Poisson-disk Sampling with Rasterization

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

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

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

Most viewed papers (last 30 days)