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The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing

Blesson Varghese

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Tags: Computational Engineering, Computer science, CUDA, Finance, Intel Xeon Phi, nVidia, Performance, Tesla C2075

January 28, 2015 by hgpu

GPU concurrency: Weak behaviours and programming assumptions

Jade Alglave, Mark Batty, Alastair F. Donaldson, Ganesh Gopalakrishnan, Jeroen Ketema, Daniel Poetzl, Tyler Sorensen, John Wickerson

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Tags: ATI, ATI Radeon HD 6570, ATI Radeon HD 7970, Computer science, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 540 M, nVidia GeForce GTX 660, nVidia GeForce GTX 750, nVidia GeForce GTX Titan, OpenCL, Performance, PTX, Tesla C2075

January 21, 2015 by hgpu

A fast marching method based back projection algorithm for photoacoustic tomography in heterogeneous media

Tianren Wang, Yun Jing

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Tags: CUDA, Heterogeneous systems, Image reconstruction, Medical Physics, Medicine, nVidia, Physics, Tesla C2075, Tomography

January 19, 2015 by hgpu

Indexing of Spatiotemporal Trajectories for Efficient Distance Threshold Similarity Searches on the GPU

Michael Gowanlock, Henri Casanova

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Tags: Astrophysics, Computer science, Databases, nVidia, OpenCL, Tesla C2075

January 19, 2015 by hgpu

Parallel Implementation of the Finite Element Method on Graphics Processors for the Solution of Incompressible Flows

Mahmut Murat Gocmen

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Source codes

Tags: Algorithms, CUBLAS, CUDA, FEM, Finite element method, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 280, Package, Tesla C2075, Thesis

January 16, 2015 by hgpu

Accelerating Correlation Power Analysis Using Graphics Processing Units

Hasindu Gamaarachchi, Roshan Ragel, Darshana Jayasinghe

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Tags: AES, Algorithms, Computer science, CUDA, nVidia, Performance, Security, Tesla C2075

December 26, 2014 by hgpu

Towards an automatic generation of dense linear algebra solvers on parallel architectures

Marc Baboulin, Joel Falcou, Ian Masliah

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Tags: Computer science, CUDA, Linear Algebra, Mixed precision, nVidia, Tesla C2075

December 20, 2014 by hgpu

Improving GPU Performance by Regrouping CPU-Memory Data

Deepthi Gummadi

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Tags: ARM, Computer science, CUDA, nVidia, Performance, Tesla C2075, Tesla K20, Thesis

November 25, 2014 by hgpu

Semi-Analytic Solutions to the Radiative Transfer Equations via Hetergeneous Computing

Daniel Alphin Holladay

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Tags: Astrophysics, Heterogeneous systems, nVidia, OpenCL, Physics, Tesla C2050, Tesla C2075, Thesis

November 13, 2014 by hgpu

Testing and Exposing Weak Graphics Processing Unit Memory Models

Tyler Rey Sorensen

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 750, nVidia GeForce GTX Titan, PTX, Tesla C2075, Thesis

October 27, 2014 by hgpu

Towards Efficient Indexing of Spatiotemporal Trajectories on the GPU for Distance Threshold Similarity Searches

Michael Gowanlock, Henri Casanova

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Tags: Algorithms, Astrophysics, Computer science, nVidia, OpenCL, Tesla C2075

October 13, 2014 by hgpu

Accelerating Protein Coordinate Conversion using GPUs

Mahsa Bayati, Jaydeep P. Bardhan, David M. King, Miriam Leeser

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Tesla C2075

October 10, 2014 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

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high performance computing on graphics processing units: hgpu.org

The GPU vs Phi Debate: Risk Analytics Using Many-Core Computing

GPU concurrency: Weak behaviours and programming assumptions

A fast marching method based back projection algorithm for photoacoustic tomography in heterogeneous media

Indexing of Spatiotemporal Trajectories for Efficient Distance Threshold Similarity Searches on the GPU

Parallel Implementation of the Finite Element Method on Graphics Processors for the Solution of Incompressible Flows

Accelerating Correlation Power Analysis Using Graphics Processing Units

Towards an automatic generation of dense linear algebra solvers on parallel architectures

Improving GPU Performance by Regrouping CPU-Memory Data

Semi-Analytic Solutions to the Radiative Transfer Equations via Hetergeneous Computing

Testing and Exposing Weak Graphics Processing Unit Memory Models

Towards Efficient Indexing of Spatiotemporal Trajectories on the GPU for Distance Threshold Similarity Searches

Accelerating Protein Coordinate Conversion using GPUs

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

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