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Fermi GF100 GPU Architecture

Craig M. Wittenbrink, Emmett Kilgariff, Arjun Prabhu

Tags: Computer science, CUDA, Hardware Architecture, nVidia, Review

May 15, 2011 by hgpu

Why does PHM matter? – Nvidia’s GPU problems reviewed

P.K. Rundle

Tags: Medicine, nVidia, Review

May 13, 2011 by hgpu

Where is the data? Why you cannot debate CPU vs. GPU performance without the answer

Chris Gregg, Kim Hazelwood

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Tags: Computer science, nVidia, nVidia GeForce 9800 GT, nVidia GeForce GT 330 M, nVidia GeForce GTX 480, Performance, Review, Tesla C2050

May 11, 2011 by hgpu

Graphics hardware & GPU computing: past, present, and future

David Luebke

Tags: Computer science, CUDA, Games, nVidia, nVidia GeForce GTX 280, Review

May 4, 2011 by hgpu

Tutorial 3: Methodologies and Performance Impacts of General Purpose Computing on GPUs

Shinichi Yamagiwa

Tags: Computer science, Review, Tutorial

April 20, 2011 by hgpu

Rendering of 3D Dynamic Virtual Environments

Salvatore Catanese, Emilio Ferrara, Giacomo Fiumara, Francesco Pagano

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Tags: 3D Graphics and Realism, Computer science, DirectX, Games, OpenGL, Review, Virtual reality

March 29, 2011 by hgpu

General-purpose GPU computing: practice and experience

Bartlett S. H. (Scott) Michel

Tags: Computer science, Programming techniques, Review

March 24, 2011 by hgpu

Data Visualization and Mining using the GPU

Sudipto Guha

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Tags: Computer science, Data mining, Rendering, Review, Visualization

March 23, 2011 by hgpu

GPU-based password cracking

Marcus Bakker, Roel Van Der Jagt

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Review, Security

March 21, 2011 by hgpu

Hardware Acceleration of EDA Algorithms: GPU Architecture and the CUDA Programming Model

Kanupriya Gulati and Sunil P. Khatri

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Tags: Book, CAD, Computer science, CUDA, Electronic design automation, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 280, nVidia Quadro FX 5800, Review

March 18, 2011 by hgpu

Using Parallel Computing for the Display and Simulation of the Space Debris Environment

M. Mockel, C. Wiedemann, S. Flegel, J. Gelhaus, P. Vorsmann, H. Klinkrad, H. Krag

Tags: Earth and Space Sciences, OpenCL, Review, Visualization

March 18, 2011 by hgpu

Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs and GPUs

Kanupriya Gulati and Sunil P. Khatri

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Tags: Book, CAD, Computer science, CUDA, Electronic design automation, FPGA, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 280, nVidia Quadro FX 5800, Review

March 14, 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

Fermi GF100 GPU Architecture

Why does PHM matter? – Nvidia’s GPU problems reviewed

Where is the data? Why you cannot debate CPU vs. GPU performance without the answer

Graphics hardware & GPU computing: past, present, and future

Tutorial 3: Methodologies and Performance Impacts of General Purpose Computing on GPUs

Rendering of 3D Dynamic Virtual Environments

General-purpose GPU computing: practice and experience

Data Visualization and Mining using the GPU

GPU-based password cracking

Hardware Acceleration of EDA Algorithms: GPU Architecture and the CUDA Programming Model

Using Parallel Computing for the Display and Simulation of the Space Debris Environment

Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs and GPUs

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)