high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia GeForce GTX Titan Black

DeepBE: Learning Deep Binary Encoding for Multi-Label Classification

Chenghua Li, Qi Kang, Guojing Ge, Qiang Song, Hanqing Lu, Jian Cheng

View

Tags: Computer science, Computer vision, CUDA, Deep learning, Image recognition, Neural networks, nVidia, nVidia GeForce GTX Titan Black, nVidia GeForce GTX Titan X

June 30, 2016 by hgpu

A GPU Accelerated Continuous and Discontinuous Galerkin Non-hydrostatic Atmospheric Model

Daniel S. Abdi, Lucas C. Wilcox, Timothy Warburton, Francis X. Giraldo

View

Download (PDF)

Tags: Algorithms, CUDA, Earth and Space Sciences, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan Black, OCCA, OpenCL, Tesla K20

May 30, 2016 by hgpu

Polly-ACC: Transparent compilation to heterogeneous hardware

Tobias Grosser, Torsten Hoefler

View

Download (PDF)

Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, LLVM, nVidia, nVidia GeForce GT 730 M, nVidia GeForce GTX Titan Black

May 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

GPU Robot Motion Planning using Semi-Infinite Nonlinear Programming

Benjamin Chretien, Adrien Escande, Abderrahmane Kheddar

View

Download (PDF)

Tags: Computer science, CUDA, Nonlinear optimization, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX Titan Black, Robotics, Tesla C2070

February 25, 2016 by hgpu

Parallel and Scalable Sparse Basic Linear Algebra Subprograms

Weifeng Liu

View

Download (PDF)

Tags: Algorithms, AMD Radeon R9 290X, ATI, Benchmarking, Computer science, Heterogeneous systems, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan Black, OpenCL, Sparse matrix, Thesis

February 16, 2016 by hgpu

Performance Portable GPU Code Generation for Matrix Multiplication

Toomas Remmelg, Thibaut Lutz, Michel Steuwer, Christophe Dubach

View

Download (PDF)

Tags: ATI, ATI Radeon HD 7970, Code generation, Compilers, Computer science, Matrix multiplication, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX Titan Black, OpenCL

February 10, 2016 by hgpu

FPGA Based Implementation of Deep Neural Networks Using On-chip Memory Only

Jinhwan Park, Wonyong Sung

View

Download (PDF)

Tags: Computer science, Deep learning, FPGA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan Black

February 6, 2016 by hgpu

Semantic Segmentation of Colon Glands with Deep Convolutional Neural Networks and Total Variation Segmentation

Philipp Kainz, Michael Pfeiffer, Martin Urschler

View

Download (PDF)

Tags: Algorithms, CUDA, Deep learning, Image processing, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan Black

November 29, 2015 by hgpu

GPU-accelerated adjoint algorithmic differentiation

Felix Gremse, Andreas Hofter, Lukas Razik, Fabian Kiessling, Uwe Naumann

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX Titan Black, Tomography

November 20, 2015 by hgpu

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

Vlad Olaru, Mihai Florea, Cristian Sminchisescu

View

Download (PDF)

Source codes

Tags: Algorithms, Computer science, Computer vision, CUDA, Matlab, nVidia, nVidia GeForce GTX Titan Black, Package, Tesla K40

September 24, 2015 by hgpu

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

Andrea Miele

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan Black, Security

July 1, 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

DeepBE: Learning Deep Binary Encoding for Multi-Label Classification

A GPU Accelerated Continuous and Discontinuous Galerkin Non-hydrostatic Atmospheric Model

Polly-ACC: Transparent compilation to heterogeneous hardware

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

GPU Robot Motion Planning using Semi-Infinite Nonlinear Programming

Parallel and Scalable Sparse Basic Linear Algebra Subprograms

Performance Portable GPU Code Generation for Matrix Multiplication

FPGA Based Implementation of Deep Neural Networks Using On-chip Memory Only

Semantic Segmentation of Colon Glands with Deep Convolutional Neural Networks and Total Variation Segmentation

GPU-accelerated adjoint algorithmic differentiation

A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation

Buffer overflow vulnerabilities in CUDA: a preliminary analysis

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)