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GPU-accelerated HMM for Speech Recognition

Leiming Yu, Yash Ukidave, David Kaeli

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Package, Speech recognition

February 10, 2015 by hgpu

Fine-Tuning Vectorization and Memory Traffic on Intel Xeon Phi Coprocessors: LU Decomposition of Small Matrices

Andrey Vladimirov

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Tags: cache, Intel Xeon Phi, Ivy Bridge, Package

February 9, 2015 by Andrey Vladimirov

Montblanc: GPU accelerated Radio Interferometer Measurement Equations in support of Bayesian Inference for Radio Observations

Simon Perkins, Patrick Maraism, Jonathan Zwart, Iniyan Natarajan, Oleg Smirnov

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Tags: Astrophysics, Bayesian, Computer science, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Package, Python, Tesla K40

February 2, 2015 by hgpu

On Vectorization of Deep Convolutional Neural Networks for Vision Tasks

Jimmy SJ. Ren, Li Xu

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Tags: CNN, Computer science, Computer vision, CUDA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 780 Ti, Package

January 30, 2015 by hgpu

Accelerate micromagnetic simulations with GPU programming in MATLAB

Ru Zhu

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 650 Ti, Package

January 30, 2015 by hgpu

maxDNN: An Efficient Convolution Kernel for Deep Learning with Maxwell GPUs

Andrew Lavin

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Tags: Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 980, Package

January 28, 2015 by hgpu

Accelerating Polynomial Homotopy Continuation on a Graphics Processing Unit with Double Double and Quad Double Arithmetic

Jan Verschelde, Xiangcheng Yu

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Tags: Algorithms, Computer science, CUDA, Extended precision, Linear Algebra, Mathematical Software, Numerical Analysis, nVidia, Package, Tesla K20

January 28, 2015 by hgpu

Taming the complexities of the C11 and OpenCL memory models

John Wickerson, Mark Batty

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Tags: Computer science, Heterogeneous systems, Memory model, OpenCL, Package

January 23, 2015 by hgpu

Gunrock: A High-Performance Graph Processing Library on the GPU

Yangzihao Wang, Andrew Davidson, Yuechao Pan, Yuduo Wu, Andy Riffel, John D. Owens

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Tags: Computer science, CUDA, Graph theory, nVidia, Package, Tesla K40

January 23, 2015 by hgpu

CURFIL: Random Forests for Image Labeling on GPU

Hannes Schulz, Benedikt Waldvogel, Rasha Sheikh, Sven Behnke

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 675 M, nVidia GeForce GTX Titan, Package, Tesla K20

January 16, 2015 by hgpu

SW#db: GPU-accelerated exact sequence similarity database search

Matija Korpar, Martin Sosic, Dino Blazeka, Mile Sikic

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Tags: Algorithms, Biology, CUDA, Databases, Next-Generation sequencing, nVidia, nVidia GeForce GTX 690, nVidia GeForce GTX 780, Package, Smith-Waterman algorithm

January 16, 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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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

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

See all packages

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high performance computing on graphics processing units: hgpu.org

GPU-accelerated HMM for Speech Recognition

Fine-Tuning Vectorization and Memory Traffic on Intel Xeon Phi Coprocessors: LU Decomposition of Small Matrices

Montblanc: GPU accelerated Radio Interferometer Measurement Equations in support of Bayesian Inference for Radio Observations

On Vectorization of Deep Convolutional Neural Networks for Vision Tasks

Accelerate micromagnetic simulations with GPU programming in MATLAB

maxDNN: An Efficient Convolution Kernel for Deep Learning with Maxwell GPUs

Accelerating Polynomial Homotopy Continuation on a Graphics Processing Unit with Double Double and Quad Double Arithmetic

Taming the complexities of the C11 and OpenCL memory models

Gunrock: A High-Performance Graph Processing Library on the GPU

CURFIL: Random Forests for Image Labeling on GPU

SW#db: GPU-accelerated exact sequence similarity database search

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

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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