high performance computing on graphics processing units: hgpu.org

Gallagher Pryor, Brett Lucey, Sandeep Maddipatla, Chris McClanahan, John Melonakos, Vishwanath Venugopalakrishnan, Krunal Patel, Pavan Yalamanchili, James Malcolm

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Tags: Computer science, CUDA, FFT, Image processing, Linear Algebra, nVidia, nVidia GeForce 9600, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenGL, Package, PTX, Tesla C1060, Tesla C2070

September 26, 2011 by hgpu

Auto-tuning of fast fourier transform on graphics processors

Yuri Dotsenko, Sara S. Baghsorkhi, Brandon Lloyd, Naga K. Govindaraju

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Tags: Computer science, CUDA, FFT, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 260, nVidia GeForce GTX 280, Performance, Software Engineering

September 14, 2011 by hgpu

GPU-based simulation of side-looking sonar images

E. Coiras, A. Ramirez-Montesinos, J. Groen

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Tags: CUDA, FFT, nVidia, nVidia GeForce 8800 GT, Signal processing

September 2, 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

Auto-tuning 3-D FFT library for CUDA GPUs

Akira Nukada, Satoshi Matsuoka

Tags: Algorithms, Computer science, CUDA, FFT, Mathematical Software, nVidia, Performance

August 22, 2011 by hgpu

High Throughput Variable Size Non-square Gabor Engine with Feature Pooling Based on GPU

Ali Emami, Abbas Bigdeli, Adam Postula

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Tags: Computer science, Computer vision, CUDA, FFT, nVidia, nVidia GeForce GTX 285, OpenCL

August 17, 2011 by hgpu

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Characterization of FPGA-based High Performance Computers

Fast Multipole Method vs. Spectral Method for the Simulation of Isotropic Turbulence on GPUs

Computitional intensive Tasks in Multimedia Signal Processing

An OpenCL Fast Fourier Transformation

CHPS: An Environment for Collaborative Execution on Heterogeneous Desktop Systems

A Polyphase Filter For GPUs And Multi-Core Processors

High-level GPU computing with jacket for MATLAB and C/C++

Auto-tuning of fast fourier transform on graphics processors

GPU-based simulation of side-looking sonar images

Collaborative execution environment for heterogeneous parallel systems

Auto-tuning 3-D FFT library for CUDA GPUs

High Throughput Variable Size Non-square Gabor Engine with Feature Pooling Based on GPU

Recent source codes

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

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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