high performance computing on graphics processing units: hgpu.org

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GPU Versus FPGA for High Productivity Computing

David H. Jones, Adam Powell, Christos-Savvas Bouganis, Peter Y. K. Cheung

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Tags: Benchmarking, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285

September 2, 2011 by hgpu

Acceleration of TM cylinder EFIE with CUDA

Tyler Killian, Daniel L. Faircloth, Sadasiva M. Rao

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Tags: Conjugate gradient solver, CUDA, Electrodynamics, Field equations, nVidia, nVidia GeForce 8800 GT, nVidia Quadro FX 770 M, nVidia Quadro NVS 140 M, Physics

September 1, 2011 by hgpu

Implementation of Sequential Importance Sampling in GPGPU

Keisuke Hayashi, Masaya M. Saito, Ryo Yoshida, Tomoyuki Higuchi

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Tags: Algorithms, CUDA, Mathematics, Monte Carlo simulation, nVidia, Tesla C870

September 1, 2011 by hgpu

Parallel hierarchical cross entropy optimization for on-chip decap budgeting

Xueqian Zhao, Yonghe Guo, Zhuo Feng, Shiyan Hu

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Tags: Algorithms, Benchmarking, CAD, Computer science, CUDA, Nonlinear optimization, nVidia, nVidia GeForce GTX 285, Optimization, Probability

September 1, 2011 by hgpu

Reliability modeling of MEMS devices on CUDA based HPC setup

Rohit Pathak, Satyadhar Joshi

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Tags: Computer science, CUDA, Data parallelism, nVidia, Performance

August 31, 2011 by hgpu

Multicore bundle adjustment

Changchang Wu, Sameer Agarwal, Brian Curless, Steven M. Seitz

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Source codes

Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, Image reconstruction, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 8800 Ultra, nVidia GeForce GTX 295, Package, Tesla C1060

August 31, 2011 by hgpu

FastMag: Fast micromagnetic simulator for complex magnetic structures

R. Chang, S. Li, M. V. Lubarda, B. Livshitz, V. Lomakin

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Tags: CUDA, Electromagnetics simulation, nVidia, nVidia GeForce GTX 480, ODEs, Ordinary differential equations, Physics, Tesla C1060, Tesla C2070

August 31, 2011 by hgpu

An FPGA-specific algorithm for direct generation of multi-variate Gaussian random numbers

David B. Thomas, Wayne Luk

Tags: Algorithms, Computer science, CUDA, DSP, FPGA, Numerical simulation, nVidia, Pseudo-random number generators

August 30, 2011 by hgpu

CUDA accelerated iris template matching on Graphics Processing Units (GPUs)

N.A. Vandal, M. Savvides

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Tags: Computer science, Computer vision, CUDA, FPGA, nVidia, nVidia GeForce GTX 470, Security

August 28, 2011 by hgpu

Real-time task reconfiguration support applied to an UAV-based surveillance system

Alecio Pedro Delazari Binotto, Edison Pignaton de Freitas, Carlos Eduardo Pereira, Andre Stork, Tony Larsson

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Image processing, nVidia, nVidia GeForce 8800 GT

August 28, 2011 by hgpu

Collaborative execution environment for heterogeneous parallel systems

Aleksandar Ilic, Leonel Sousa

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Tags: Computer science, CUBLAS, CUDA, Data parallelism, FFT, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Presentation

August 28, 2011 by hgpu

Real-time photo style transfer

Hanli Zhao, Xiaogang Jin, Jianbing Shen, Feifei Wei

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Tags: CUDA, DirectX, Image processing, nVidia, nVidia GeForce 8800 GTS, Real-time graphics

August 28, 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

GPU Versus FPGA for High Productivity Computing

Acceleration of TM cylinder EFIE with CUDA

Implementation of Sequential Importance Sampling in GPGPU

Parallel hierarchical cross entropy optimization for on-chip decap budgeting

Reliability modeling of MEMS devices on CUDA based HPC setup

Multicore bundle adjustment

FastMag: Fast micromagnetic simulator for complex magnetic structures

An FPGA-specific algorithm for direct generation of multi-variate Gaussian random numbers

CUDA accelerated iris template matching on Graphics Processing Units (GPUs)

Real-time task reconfiguration support applied to an UAV-based surveillance system

Collaborative execution environment for heterogeneous parallel systems

Real-time photo style transfer

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)