high performance computing on graphics processing units: hgpu.org

hgpu.org » Package

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

Ilya Loshchilov, Frank Hutter

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan, Package, Python

April 26, 2016 by hgpu

LightScan: Faster Scan Primitive on CUDA Compatible Manycore Processors

Yongchao Liu, Srinivas Aluru

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Intel Xeon Phi, nVidia, Package, Performance, PTX, Tesla K40

April 19, 2016 by hgpu

Efficiency of general Krylov methods on GPUs – An experimental study

Hartwig Anzt, Jack Dongarra, Moritz Kreutzer, Gerhard Wellein, Martin Kohler

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Intel Xeon Phi, Linear Algebra, nVidia, OpenCL, Package, Sparse matrix, Tesla K40

April 16, 2016 by hgpu

GPU-FV: Realtime Fisher Vector and Its Applications in Video Monitoring

Wenying Ma, Liangliang Cao, Lei Yu, Guoping Long, Yucheng Li

View

Download (PDF)

Source codes

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

April 14, 2016 by hgpu

CUED-RNNLM – An Open-Source Toolkit for Efficient Training and Evaluation of Recurrent Neural Network Language Models

X. Chen, X. Liu, Y. Qian, M.J.F. Gales, P.C. Woodland

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, NLP, nVidia, nVidia GeForce GTX Titan, Package, RNN, Speech recognition

April 12, 2016 by hgpu

Algorithmic and Software System Support to Accelerate Data Processing in CPU-GPU Hybrid Computing Environments

Kaibo Wang

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Databases, Hybrid computing, nVidia, nVidia GeForce GTX 580, Package, Tesla M2050, Thesis

April 12, 2016 by hgpu

Optimizing Performance of Recurrent Neural Networks on GPUs

Jeremy Appleyard, Tomas Kocisky, Phil Blunsom

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Lua, Neural networks, nVidia, Package, RNN, Tesla M40

April 9, 2016 by hgpu

Implementation of the SYCL Heterogeneous Computing Library

Peter Zuzek

View

Download (PDF)

Source codes

Tags: Code generation, Computer science, Heterogeneous systems, OpenCL, Package, SYCL, Thesis

April 3, 2016 by hgpu

sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors

Kenichi W. Okamoto, Priyanga Amarasekare

View

Download (PDF)

Source codes

Tags: Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 690, Package

April 3, 2016 by hgpu

Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets

Pascal Vincent, Alexandre de Brebisson, Xavier Bouthillier

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan Black, Package

March 25, 2016 by hgpu

Wanted: Floating-Point Add Round-off Error instruction

Marat Dukhan, Richard Vuduc, Jason Riedy

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Matrix multiplication, OpenCL, Package

March 25, 2016 by hgpu

Recurrent neural networks for language modeling

Emil Sauer Lynge

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, LSTM, Neural networks, NLP, nVidia, nVidia GeForce GTX Titan X, Package, Python, RNN, Thesis

March 22, 2016 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

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

LightScan: Faster Scan Primitive on CUDA Compatible Manycore Processors

Efficiency of general Krylov methods on GPUs – An experimental study

GPU-FV: Realtime Fisher Vector and Its Applications in Video Monitoring

CUED-RNNLM – An Open-Source Toolkit for Efficient Training and Evaluation of Recurrent Neural Network Language Models

Algorithmic and Software System Support to Accelerate Data Processing in CPU-GPU Hybrid Computing Environments

Optimizing Performance of Recurrent Neural Networks on GPUs

Implementation of the SYCL Heterogeneous Computing Library

sPEGG: high throughput eco-evolutionary simulations on commodity graphics processors

Efficient Exact Gradient Update for training Deep Networks with Very Large Sparse Targets

Wanted: Floating-Point Add Round-off Error instruction

Recurrent neural networks for language modeling

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)