high performance computing on graphics processing units: hgpu.org

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Comparing Many-Core Accelerator Frameworks

G. Haase, A. Kucher

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, OpenCL, Optimization

February 15, 2012 by hgpu

Advancing Large Scale Many-Body QMC Simulations on GPU Accelerated Multicore Systems

Andres Tomas, Chia-Chen Chang, Richard Scalettar, Zhaojun Bai

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Tags: Computer science, CUDA, Linear Algebra, Monte Carlo simulation, nVidia, QMC, Tesla C2050

February 15, 2012 by hgpu

Reflective Shadow Map Clustering for Real-Time Global Illumination

Roman Prutkin, Anton Kaplanyan, Carsten Dachsbacher

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Tags: 3D Graphics and Realism, Clustering, Computer science, DirectX, Image generation, nVidia, nVidia GeForce GTX 560 Ti

February 15, 2012 by hgpu

Graph Coarsening and Clustering on the GPU

B. O. Fagginger Auer, R. H. Bisseling

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Tags: Algorithms, Clustering, Computer science, CUDA, Graph theory, nVidia, Package, Tesla C2050

February 15, 2012 by hgpu

Robust Real-Time Multiprocessor Interrupt Handling Motivated by GPUs

Glenn A. Elliott, James H. Anderson

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 470, Package

February 14, 2012 by hgpu

Cross Teaching Parallelism and Ray Tracing: A Project-based Approach to Teaching Applied Parallel Computing

Chris Lupo, Zoe J. Wood, Christine Victorino

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Tags: Computer science, CUDA, Education, nVidia, nVidia GeForce GTX 470, Performance, Programming techniques, Raytracing, Rendering

February 14, 2012 by hgpu

Acceleration of information-theoretic data analysis with graphics processing units

Davor Sluga, Tomaz Curk, Blaz Zupan, Uros Lotric

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Tags: Algorithms, Computer science, CUDA, Data mining, nVidia, Tesla C2050

February 14, 2012 by hgpu

Accelerated People Tracking Using Texture in a Camera Network

Wasit Limprasert, Andrew Wallace, Greg Michaelson

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTS 250

February 14, 2012 by hgpu

A Scalable GPU-based Approach to Accelerate the Multiple-Choice Knapsack Problem

Bharath Suri, Unmesh D. Bordoloi, Petru Eles

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Tags: Computer science, CUDA, nVidia, Optimization, Tesla M2050

February 13, 2012 by hgpu

Using Graphical Processing Units in Scheduling Problems

K. Mihaly, O. Hornyak

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Tags: Algorithms, Computer science, CUDA, nVidia, Task scheduling, Tesla C1060

February 13, 2012 by hgpu

Work Stealing Inside GPUs

Julio Toss

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 280, Task scheduling, Tesla C2050, Thesis

February 13, 2012 by hgpu

Analytic Anti-Aliasing of Linear Functions on Polytopes

Thomas Auzinger, Michael Guthe, Stefan Jeschke

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

February 13, 2012 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

Comparing Many-Core Accelerator Frameworks

Advancing Large Scale Many-Body QMC Simulations on GPU Accelerated Multicore Systems

Reflective Shadow Map Clustering for Real-Time Global Illumination

Graph Coarsening and Clustering on the GPU

Robust Real-Time Multiprocessor Interrupt Handling Motivated by GPUs

Cross Teaching Parallelism and Ray Tracing: A Project-based Approach to Teaching Applied Parallel Computing

Acceleration of information-theoretic data analysis with graphics processing units

Accelerated People Tracking Using Texture in a Camera Network

A Scalable GPU-based Approach to Accelerate the Multiple-Choice Knapsack Problem

Using Graphical Processing Units in Scheduling Problems

Work Stealing Inside GPUs

Analytic Anti-Aliasing of Linear Functions on Polytopes

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)