high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Theano: Deep Learning on GPUs with Python

James Bergstra, Frederic Bastien, Olivier Breuleux, Pascal Lamblin, Razvan Pascanu, Olivier Delalleau, Guillaume Desjardins, David Warde-Farley, Ian Goodfellow, Arnaud Bergeron, Yoshua Bengio

View

Download (PDF)

Source codes

Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Package, Python

January 16, 2012 by hgpu

BarraCUDA – a fast short read sequence aligner using graphics processing units

Petr Klus, Simon Lam, Dag Lyberg, Ming Sin Cheung, Graham Pullan, Ian McFarlane, Giles S. H. Yeo, Brian Y. H. Lam

View

Download (PDF)

Source codes

Tags: Bioinformatics, Biology, CUDA, nVidia, Package, Sequence alignment, Tesla M2050, Tesla M2090

January 13, 2012 by hgpu

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

Haixiang Shi, Bertil Schmidt, Weiguo Liu, Wolfgang Muller-Wittig

View

Download (PDF)

Source codes

Tags: Algorithms, Biology, Computational biology, CUDA, Image processing, Machine learning, nVidia, Package, Tesla C2050

January 13, 2012 by hgpu

MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification

Peng Jia, Liming Xuan, Lei Liu, Chaochun Wei

View

Download (PDF)

Source codes

Tags: Biology, Computational biology, CUDA, Genetics, nVidia, Package, Tesla C1060

January 11, 2012 by hgpu

Report on the Feasibility of Implementing PIC Codes on a GPU

Joshua Payne

View

Download (PDF)

Source codes

Tags: CUDA, nVidia, nVidia GeForce GTX 470, Package, Physics, Plasma physics

January 7, 2012 by hgpu

CodePy

Martin Kempf

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, CUDA, nVidia, Package, Python

January 6, 2012 by hgpu

A GPU Implementation of Inclusion-based Points-to Analysis

Mario Mendez-Lojo, Martin Burtscher, Keshav Pingali

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Package, Performance, Programming techniques, Tesla C2070

January 5, 2012 by hgpu

Implementation of Keccak hash function in Tree hashing mode on Nvidia GPU

Guillaume Sevestre

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTS 250, nVidia Quadro FX 370 M, Optimization, Package, Security, Stream Ciphers

January 5, 2012 by hgpu

Thermal and Athermal Swarms of Self-Propelled Particles

Nguyen Nguyen, Eric Jankowski, Sharon C. Glotzer

View

Download (PDF)

Source codes

Tags: Computational Physics, Condensed matter, CUDA, nVidia, Package, Physics, Probability, Soft Condensed Matter, Tesla S1070

January 4, 2012 by hgpu

Augmenting Operating Systems With the GPU

Weibin Sun, Robert Ricci

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Operating systems, Package

January 2, 2012 by hgpu

Efficient Triangle and Quadrilateral Clipping within Shaders

M. McGuire

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, GLSL, nVidia, nVidia GeForce GTX 580, OpenGL, Optimization, Package, Rasterization

December 31, 2011 by hgpu

Fast Speaker Diarization Using a Specialization Framework for Gaussian Mixture Model Training

Ekaterina Gonina

View

Download (PDF)

Source codes

Tags: Acoustics, Algorithms, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Package, Python, Thesis

December 31, 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

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Theano: Deep Learning on GPUs with Python

BarraCUDA – a fast short read sequence aligner using graphics processing units

Parallel mutual information estimation for inferring gene regulatory networks on GPUs

MetaBinG: Using GPUs to Accelerate Metagenomic Sequence Classification

Report on the Feasibility of Implementing PIC Codes on a GPU

CodePy

A GPU Implementation of Inclusion-based Points-to Analysis

Implementation of Keccak hash function in Tree hashing mode on Nvidia GPU

Thermal and Athermal Swarms of Self-Propelled Particles

Augmenting Operating Systems With the GPU

Efficient Triangle and Quadrilateral Clipping within Shaders

Fast Speaker Diarization Using a Specialization Framework for Gaussian Mixture Model Training

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

Most viewed papers (last 30 days)