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CUDArray: CUDA-based NumPy

Anders Boesen Lindbo Larsen

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Tags: Computer science, CUDA, Neural networks, nVidia, Package, Python

November 16, 2014 by hgpu

Whippletree: Task-based Scheduling of Dynamic Workloads on the GPU

Markus Steinberger, Michael Kenzel, Pedro Boechat, Bernhard Kerbl, Mark Dokter, Dieter Schmalstieg

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Package, Rendering

November 13, 2014 by hgpu

A GPU-Based Wide-Band Radio Spectrometer

Jayanth Chennamangalam, Simon Scott, Glenn Jones, Hong Chen, John Ford, Amanda Kepley, D. R. Lorimer, Jun Nie, Richard Prestage, D. Anish Roshi, Mark Wagner, Dan Werthimer

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Tags: Astrophysics, CUDA, FFT, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX Titan, Package, Signal processing

November 5, 2014 by hgpu

Bounds on the Energy Consumption of Computational Kernels

Andrew Gearhart

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Tags: Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, Package, Tesla K20, Thesis

November 3, 2014 by hgpu

Contract-Based General-Purpose GPU Programming

Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro K 2000 M, Package, Software Engineering

October 27, 2014 by hgpu

cufftShift: High Performance CUDA-accelerated FFT-shift Library

Marwan Abdellah

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Tags: Algorithms, CUDA, FFT, Image processing, nVidia, nVidia GeForce GTX 580, Package

October 24, 2014 by hgpu

Introducing CURRENNT – the Munich open-source CUDA RecurREnt Neural Network Toolkit

Felix Weninger, Johannes Bergmann, Bjorn Schuller

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Tags: Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 560, Package, Speech recognition

October 22, 2014 by hgpu

A Performance Comparison of Sort and Scan Libraries for GPUs

Bruce Merry

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Tags: Algorithms, AMD Radeon R9 270, ATI, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sorting, Tesla K40

October 20, 2014 by hgpu

Multi-GPU Based Lattice Boltzmann Method for Hemodynamic Simulation in Patient-Specific Cerebral Aneurysm

Changsheng Huang, Baochang Shi, Zhaoli Guo, Zhenhua Chai

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Tags: Algorithms, CUDA, Fluid dynamics, Lattice Boltzmann model, MPI, nVidia, Package, Tesla C1060, Tesla K20

October 16, 2014 by hgpu

KBLAS: An Optimized Library for Dense Matrix-Vector Multiplication on GPU Accelerators

Ahmad Abdelfattah, David Keyes, Hatem Ltaief

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Mathematical Software, nVidia, Package, Tesla K20

October 8, 2014 by hgpu

Deep Dynamic Neural Networks for Gesture Segmentation and Recognition

Di Wu, Ling Shao

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Tags: CNN, Computer science, CUDA, Neural networks, nVidia, Package, Python, Rendering

October 4, 2014 by hgpu

Fast Estimation of Gaussian Mixture Model Parameters on GPU using CUDA

Lukas Machlica, Jan Vanek, Zbynek Zajıc

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 280, Package, Statistics and Probability

October 2, 2014 by Vanekyj

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

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high performance computing on graphics processing units: hgpu.org

CUDArray: CUDA-based NumPy

Whippletree: Task-based Scheduling of Dynamic Workloads on the GPU

A GPU-Based Wide-Band Radio Spectrometer

Bounds on the Energy Consumption of Computational Kernels

Contract-Based General-Purpose GPU Programming

cufftShift: High Performance CUDA-accelerated FFT-shift Library

Introducing CURRENNT – the Munich open-source CUDA RecurREnt Neural Network Toolkit

A Performance Comparison of Sort and Scan Libraries for GPUs

Multi-GPU Based Lattice Boltzmann Method for Hemodynamic Simulation in Patient-Specific Cerebral Aneurysm

KBLAS: An Optimized Library for Dense Matrix-Vector Multiplication on GPU Accelerators

Deep Dynamic Neural Networks for Gesture Segmentation and Recognition

Fast Estimation of Gaussian Mixture Model Parameters on GPU using CUDA

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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