high performance computing on graphics processing units: hgpu.org

hgpu.org » CUDA

A Data-oriented Method for Scheduling Dependent Tasks on High-density Multi-GPU Systems

Peng Zhang, Yuxiang Gao, Meikang Qiu

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Matrix inversion, Matrix multiplication, nVidia, Task scheduling, Tesla K40

August 3, 2015 by hgpu

Parallel Surface Reconstruction on GPU

Heng Gao, Jie Tang, Gangshan Wu

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 660

August 1, 2015 by hgpu

Investigating SRAM PUFs in large CPUs and GPUs

Pol Van Aubel, Daniel J. Bernstein, Ruben Niederhagen

View

Download (PDF)

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

August 1, 2015 by hgpu

GHOST: Building blocks for high performance sparse linear algebra on heterogeneous systems

Moritz Kreutzer, Jonas Thies, Melven Rohrig-Zollner, Andreas Pieper, Faisal Shahzad, Martin Galgon, Achim Basermann, Holger Fehske, Georg Hager, Gerhard Wellein

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, Linear Algebra, MPI, nVidia, OpenMP, Package, Sparse matrix, Tesla K20

July 30, 2015 by hgpu

Prospects of GPGPU in the Auger Offline Software Framework

Tobias Winchen, Marvin Gottowik, Julian Rautenberg

View

Download (PDF)

Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 750 Ti, Tesla M2090

July 29, 2015 by hgpu

Reverberant speech recognition combining deep neural networks and deep autoencoders augmented with a phone-class feature

Masato Mimura, Shinsuke Sakai, Tatsuya Kawahara

View

Download (PDF)

Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, Speech recognition

July 29, 2015 by hgpu

OKL: A Unified Language for Parallel Architectures

David Medina

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7990, Computer science, CUDA, High-level Languages, nVidia, OpenCL, Tesla K40, Thesis

July 29, 2015 by hgpu

Processing Large-scale XML Files on GPGPU Cluster

Ping Liu

View

Download (PDF)

Tags: Computer science, CUDA, GPU cluster, nVidia, OpenMPI, Performance, Tesla M2075

July 27, 2015 by hgpu

Accelerating Protein Structure Prediction using Particle Swarm Optimization on GPU

Hamed Khakzad, Yasaman Karami, Seyed Shahriar Arab

View

Download (PDF)

Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Particle swarm optimization, Sequence alignment, Tesla C1060

July 24, 2015 by hgpu

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

Baoguang Shi, Xiang Bai, Cong Yao

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, Tesla K40

July 24, 2015 by hgpu

Massively Deep Artificial Neural Networks for Handwritten Digit Recognition

Keiron O'Shea

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 580

July 24, 2015 by hgpu

On the use of deep Boltzmann machines for road signs classification

Carlo D'Eramo

View

Download (PDF)

Tags: Computer science, Computer vision, CUDA, Image recognition, Machine learning, nVidia, Python, Tesla C1060, Thesis

July 22, 2015 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

A Data-oriented Method for Scheduling Dependent Tasks on High-density Multi-GPU Systems

Parallel Surface Reconstruction on GPU

Investigating SRAM PUFs in large CPUs and GPUs

GHOST: Building blocks for high performance sparse linear algebra on heterogeneous systems

Prospects of GPGPU in the Auger Offline Software Framework

Reverberant speech recognition combining deep neural networks and deep autoencoders augmented with a phone-class feature

OKL: A Unified Language for Parallel Architectures

Processing Large-scale XML Files on GPGPU Cluster

Accelerating Protein Structure Prediction using Particle Swarm Optimization on GPU

An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition

Massively Deep Artificial Neural Networks for Handwritten Digit Recognition

On the use of deep Boltzmann machines for road signs classification

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)