high performance computing on graphics processing units: hgpu.org

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Concurrent GPU Programming

Lesley Northam

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 M GTX, Programming techniques, Review

February 26, 2011 by hgpu

Probing biomolecular machines with graphics processors

James C. Phillips, John E. Stone

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Tags: Biology, Biomolecules, CUDA, GPU cluster, Molecular simulation, nVidia, OpenCL, Review, Tesla S1070

February 23, 2011 by hgpu

Architecting graphics processors for non-graphics compute acceleration

Tor M. Aamodt

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Tags: Computer science, Hardware Architecture, nVidia, Review

February 20, 2011 by hgpu

Design Space Exploration for GPU-Based Architecture

Zhenyu Ye

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Tags: Computer science, CUDA, Factorization, Hardware Architecture, Memory model, nVidia, nVidia GeForce 8800 GTX, Review, Thesis

February 20, 2011 by hgpu

Programmability: Design Costs and Payoffs using AMD GPU Streaming Languages and Traditional Multi-Core Libraries

Rick Weber, Robert J. Harrison, Gregory D. Peterson

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Tags: ATI CAL, ATI Radeon HD 4870, ATI Stream, Brook, Computer science, Review

February 19, 2011 by hgpu

Graphics Processing Units and Genetic Programming: An overview

W. B. Langdon

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Tags: Bioinformatics, Computer science, CUDA, Genetic programming, nVidia, Review

February 15, 2011 by hgpu

GPU-powered tools boost molecular visualization

Matthieu Chavent, Bruno Levy, Michael Krone, Katrin Bidmon, Jean-Philippe P. Nomine, Thomas Ertl, Marc Baaden

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Tags: Bioinformatics, Biology, Molecular modeling, nVidia, Review, Visualization

February 12, 2011 by hgpu

Energy-efficient algorithms

Susanne Albers

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Tags: Algorithms, Computer science, Energy-efficient computing, Green, Review

February 11, 2011 by hgpu

Comparing FPGAs to Graphics Accelerators and the Playstation 2 Using a Unified Source Description

Lee W. Howes, Paul Price, Oskar Mencer, Olav Beckmann, Oliver Pell

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Tags: Cg, Computer science, FPGA, nVidia, nVidia GeForce 6800 Ultra, Playstation, Review

February 10, 2011 by hgpu

Cg: a system for programming graphics hardware in a C-like language

William R. Mark, R. Steven Glanville, Kurt Akeley, Mark J. Kilgard

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Tags: 3D Graphics and Realism, Cg, Code generation, Compilers, Computer science, High-level Languages, nVidia, Package, Review

February 10, 2011 by hgpu

QP: A Heterogeneous Multi-Accelerator Cluster

Michael Showerman, Jeremy Enos, Avneesh Pant, Volodymyr Kindratenko, Craig Steffen, Robert Pennington, Wen-mei Hwu

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Tags: Computer science, CUDA, FPGA, GPU cluster, nVidia, nVidia Quadro FX 5600, Review

February 4, 2011 by hgpu

Introduction to GPU programming for EDA

John F. Croix, Sunil P. Khatri

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Tags: Computational Engineering, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, nVidia Quadro FX 5800, OpenCL, Presentation, Review

February 1, 2011 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

Concurrent GPU Programming

Probing biomolecular machines with graphics processors

Architecting graphics processors for non-graphics compute acceleration

Design Space Exploration for GPU-Based Architecture

Programmability: Design Costs and Payoffs using AMD GPU Streaming Languages and Traditional Multi-Core Libraries

Graphics Processing Units and Genetic Programming: An overview

GPU-powered tools boost molecular visualization

Energy-efficient algorithms

Comparing FPGAs to Graphics Accelerators and the Playstation 2 Using a Unified Source Description

Cg: a system for programming graphics hardware in a C-like language

QP: A Heterogeneous Multi-Accelerator Cluster

Introduction to GPU programming for EDA

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)