high performance computing on graphics processing units: hgpu.org

hgpu.org » Tesla K40

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

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

An algebraic parallel treecode in arbitrary dimensions

William B. March, Bo Xiao, Chenhan D. Yu, George Biros

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, GPU cluster, Linear Algebra, MPI, nVidia, Tesla K40

July 22, 2015 by hgpu

Generating Binary Optimal Codes Using Heterogeneous Parallel Computing

Srajan Paliwal, Saurabh Tiwary, Bhaskar Chaudhury, Manish K. Gupta

View

Download (PDF)

Tags: Algorithms, Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K40

July 22, 2015 by hgpu

GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

Mark James Abraham, Teemu Murtola, Roland Schulz, Szilard Pall, Jeremy C. Smith, Berk Hess, Erik Lindahl

View

Download (PDF)

Source codes

Tags: Algorithms, Biomolecules, Chemistry, CUDA, Heterogeneous systems, Molecular simulation, nVidia, nVidia GeForce GTX 980, OpenCL, Package, Tesla K40

July 20, 2015 by hgpu

Many-Core Compiler Fuzzing

Christopher Lidbury, Andrei Lascu, Nathan Chong, Alastair F. Donaldson

View

Download (PDF)

Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Compilers, Computer science, FPGA, Intel HD 4600, Intel Xeon Phi, nVidia, nVidia GeForce GTX 770, nVidia GeForce GTX Titan, OpenCL, Tesla K40, Tesla M2050

July 10, 2015 by hgpu

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations

Carsten Kutzner, Szilard Pall, Martin Fechner, Ansgar Esztermann, Bert L. de Groot, Helmut Grubmuller

View

Download (PDF)

Source codes

Tags: Benchmarking, Biological Physics, Biomolecules, Computational Physics, Computer science, Molecular dynamics, Molecular simulation, MPI, nVidia, Package, Performance, Tesla K20, Tesla K40

July 6, 2015 by hgpu

Heterogeneous Network Embedding via Deep Architectures

Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang

View

Download (PDF)

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

July 1, 2015 by hgpu

Alpha-Beta Divergences Discover Micro and Macro Structures in Data

Karthik Narayan, Ali Punjani, Pieter Abbeel

View

Download (PDF)

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

June 24, 2015 by hgpu

GPU-Friendly Local Regression for Voice Conversion

Taylor Berg-Kirkpatrick, Dan Klein

View

Download (PDF)

Tags: Acoustics, CUDA, nVidia, Signal processing, Tesla K40

June 24, 2015 by hgpu

GPU accelerated spectral finite elements on all-hex meshes

J.-F. Remacle, R. Gandham, T. Warburton

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Numerical Analysis, nVidia, nVidia GeForce GTX 980, OpenCL, Spectral elements, Tesla K40

June 22, 2015 by hgpu

Study of Sparse-Matrix Vector Multiplication (SpMV) on Different Architectures and Libraries

Naveen Anand Subramaniam, Omkar Deshmukh, Vennila Megavannan, Dan Negrut

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 770, OpenCL, Performance, Sparse matrix, Tesla K20, Tesla K40

June 19, 2015 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

OKL: A Unified Language for Parallel Architectures

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

An algebraic parallel treecode in arbitrary dimensions

Generating Binary Optimal Codes Using Heterogeneous Parallel Computing

GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers

Many-Core Compiler Fuzzing

Best bang for your buck: GPU nodes for GROMACS biomolecular simulations

Heterogeneous Network Embedding via Deep Architectures

Alpha-Beta Divergences Discover Micro and Macro Structures in Data

GPU-Friendly Local Regression for Voice Conversion

GPU accelerated spectral finite elements on all-hex meshes

Study of Sparse-Matrix Vector Multiplication (SpMV) on Different Architectures and Libraries

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)