high performance computing on graphics processing units: hgpu.org

Daniel L. Ayres, Aaron Darling, Derrick J. Zwickl, Peter Beerli, Mark T. Holder, Paul O. Lewis, John P. Huelsenbeck, Fredrik Ronquist, David L. Swofford, Michael P. Cummings, Andrew Rambaut, Marc A. Suchard

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Tags: Bayesian, Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 580

October 25, 2011 by hgpu

An Evolutionary Optimization Strategy Using Graphics Processing Units to Efficiently Investigate Gene-Gene Interactions in Genetic Association Studies

Joel B. Fontanarosa, Yang Dai

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Tags: Algorithms, Biology, CUDA, Evolutionary Computations, Genetics, nVidia, nVidia GeForce GTX 470, Optimization

October 25, 2011 by hgpu

Development of a Flow Solver with Complex Kinetics on the Graphic Processing Units

Hai P. Le, Jean-Luc Cambier

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Tags: Chemistry, Computational Physics, CUDA, Finite volume method, Fluid dynamics, nVidia, Tesla C2050, Tesla C2070

October 25, 2011 by hgpu

Parallel Implementation of Devanagari Text Line and Word Segmentation Approach on GPU

Brijmohan Singh, Nitin Gupta, Rashi Tyagi, Ankush Mitta, Debashish Ghosh

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 9500 GT, Pattern recognition

October 24, 2011 by hgpu

Breaking DVB-CSA

Erik Tews, Julian Walde, Michael Weiner

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, OpenCL, Security

October 24, 2011 by hgpu

APTCC: Auto Parallelizing Translator From C To CUDA

Takehiko Nawataa, Reiji Suda

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 580, Tesla C2050

October 24, 2011 by hgpu

Using OpenCL for Implementing Simple Parallel Graph Algorithms

Michael J. Dinneen, Masoud Khosravani, Andrew Probert

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, OpenCL, Tesla C2050

October 24, 2011 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

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high performance computing on graphics processing units: hgpu.org

Flexible neuronal network simulation framework using code generation for NVidia CUDA

Scalability of Incompressible Flow Computations on Multi-GPU Clusters Using Dual-Level and Tri-Level Parallelism

Design and Implementation of GPU-Based Prim’s Algorithm

Parallel Execution of AES-CTR Algorithm Using Extended Block Size

The Model of Computation of CUDA and its Formal Semantics

BEAGLE: an Application Programming Interface and High-Performance Computing Library for Statistical Phylogenetics

An Evolutionary Optimization Strategy Using Graphics Processing Units to Efficiently Investigate Gene-Gene Interactions in Genetic Association Studies

Development of a Flow Solver with Complex Kinetics on the Graphic Processing Units

Parallel Implementation of Devanagari Text Line and Word Segmentation Approach on GPU

Breaking DVB-CSA

APTCC: Auto Parallelizing Translator From C To CUDA

Using OpenCL for Implementing Simple Parallel Graph Algorithms

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)