high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming » Algorithms

Parallel GPU algorithms for alternate-triangular finite difference schemes

V.O. Bohaienko

View

Download (PDF)

Tags: Algorithms, Computer science, Diffusion equation, Finite difference, nVidia, OpenCL, OpenMPI, Tesla M2075

October 24, 2013 by hgpu

Towards a Unified Sentiment Lexicon (USL) based on Graphics Processing Units (GPUs)

Liliana Ibeth Barbosa-Santillan, Inmaculada Alvarez-de-Mon-y-Rego

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, Tesla C2075, Tesla K20

October 24, 2013 by hgpu

gEMpicker: A Highly Parallel GPU-Accelerated Particle Picking Tool for Cryo-Electron Microscopy

Thai V. Hoang, Xavier Cavin, Patrick Schultz, David W. Ritchie

View

Download (PDF)

Tags: Algorithms, Biology, Cryo-EM, CUDA, Electron microscopy, FFT, Macromolecule, Microscopy, nVidia, Tesla C1060, Tesla C2075

October 24, 2013 by hgpu

Analysis of Genetic Expression with Microarrays using GPU Implemented Algorithms

Eduardo Romero-Vivas, Fernando D. Von Borstel, Isaac Villa-Medina

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9800 GT

October 24, 2013 by hgpu

A Parallel PSO Algorithm for a Watermarking Application on a GPU

Edgar Garcia Cano, Katya Rodriguez

View

Download (PDF)

Tags: Algorithms, CUDA, Image processing, nVidia, Particle swarm optimization, Security, Tesla C1060

October 24, 2013 by hgpu

2HOT: An Improved Parallel Hashed Oct-Tree N-Body Algorithm for Cosmological Simulation

Michael S. Warren

View

Download (PDF)

Tags: Algorithms, Astrophysics, Cosmology, CUDA, Fast multipole method, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, Tesla K20, Tesla M2090

October 22, 2013 by hgpu

Fingerprint Local Invariant Feature Extraction on GPU with CUDA

Ali Ismail Awad

View

Download (PDF)

Tags: Algorithms, Biometrics, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GT 430, SIFT

October 22, 2013 by hgpu

Solving Multiple Queries through a Permutation Index in GPU

Mariela Lopresti, Natalia Miranda, Fabiana Piccoli, Nora Reyes

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GT 520 M, nVidia GeForce GTX 330 M, nVidia GeForce GTX 550 Ti, Search

October 21, 2013 by hgpu

Optimization of the HEFT algorithm for a CPU-GPU environment

Karan R. Shetti, Suhaib A. Fahmy, Timo Bretschneider

View

Download (PDF)

Tags: Algorithms, Computer science, Heterogeneous systems, Task scheduling

October 21, 2013 by hgpu

Work Efficient Parallel Algorithms for Large Graph Exploration

Dip Sankar Banerjee, Shashank Sharma, Kishore Kothapalli

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 580

October 21, 2013 by hgpu

Architecture-and Workload-Aware Heterogeneous Algorithms for Sparse Matrix Vector Multiplication

Sivaramakrishna Bharadwaj Indarapu, Manoj Maramreddy, Kishore Kothapalli

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, Sparse matrix

October 21, 2013 by hgpu

Multi-Scale Scheduling Techniques for Signal Processing Systems

Zheng Zhou

View

Download (PDF)

Tags: Algorithms, CUDA, DSP, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Particle swarm optimization, Signal processing, Thesis

October 19, 2013 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

* * *

high performance computing on graphics processing units: hgpu.org

Programming

Parallel GPU algorithms for alternate-triangular finite difference schemes

Towards a Unified Sentiment Lexicon (USL) based on Graphics Processing Units (GPUs)

gEMpicker: A Highly Parallel GPU-Accelerated Particle Picking Tool for Cryo-Electron Microscopy

Analysis of Genetic Expression with Microarrays using GPU Implemented Algorithms

A Parallel PSO Algorithm for a Watermarking Application on a GPU

2HOT: An Improved Parallel Hashed Oct-Tree N-Body Algorithm for Cosmological Simulation

Fingerprint Local Invariant Feature Extraction on GPU with CUDA

Solving Multiple Queries through a Permutation Index in GPU

Optimization of the HEFT algorithm for a CPU-GPU environment

Work Efficient Parallel Algorithms for Large Graph Exploration

Architecture-and Workload-Aware Heterogeneous Algorithms for Sparse Matrix Vector Multiplication

Multi-Scale Scheduling Techniques for Signal Processing Systems

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)