high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming » Algorithms

HIPAcc: A Domain-Specific Language and Compiler for Image Processing

Richard Membarth, Oliver Reiche, Frank Hannig, Jurgen Teich, Mario Korner, Wieland Eckert

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Tags: Algorithms, AMD Radeon R9 290X, ARM, ATI, Compilers, Computer science, CUDA, Heterogeneous systems, Image processing, Intel Xeon Phi, nVidia, OpenCL, Package, Tesla K20

November 19, 2016 by hgpu

Performance Analysis of Parallel Sorting Algorithms using GPU Computing

Neetu Faujdar, SP Ghrera

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 460, Performance, Sorting

November 19, 2016 by hgpu

Automatic code generation methods applied to numerical linear algebra in high performance computing

M. Ian Masliah

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Tags: Algorithms, Code generation, Computer science, CUDA, Heterogeneous systems, Linear Algebra, Mixed precision, nVidia, nVidia Tegra TX1, Programming techniques, Tesla C2075, Tesla K40, Thesis

November 16, 2016 by hgpu

OpenCL-based optimizations for acceleration of object tracking on FPGAs and GPUs

Amir Momeni, Hamed Tabkhi, Gunar Schirner, David Kaeli

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Tags: Algorithms, Computer science, FPGA, Heterogeneous systems, nVidia, OpenCL, Tesla K20

November 13, 2016 by hgpu

Hadoopcl2: Motivating the design of a distributed, heterogeneous programming system with machine-learning applications

Max Grossman, Mauricio Breternitz, Vivek Sarkar

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Tags: Algorithms, Computer science, Hadoop, Heterogeneous systems, Machine learning, MapReduce, nVidia, OpenCL, Spark, Tesla M2050

November 13, 2016 by hgpu

Fractal Art Generation using GPUs

Will.D. Mayfield, Justin.C. Eiland, Taylor.J. Hutyra, Matt.C. Paulsen, Bryant.M. Wyatt

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Tags: Algorithms, Computer science, CUDA, Graphics, Image generation, nVidia, nVidia GeForce GTX Titan

November 13, 2016 by hgpu

Shuffle Reduction Based Sparse Matrix-Vector Multiplication on Kepler GPU

Yuan Tao, Huang Zhi-Bin

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Tags: Algorithms, Computer science, CUDA, nVidia, Sparse matrix, Tesla K20

November 10, 2016 by hgpu

Using multiple GPUs to accelerate string searching for digital forensic analysis

Ethan Bayne, R. Ian Ferguson, Adam T. Sampson, John Isaacs

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 970 M, nVidia GeForce GTX 980, OpenCL, String matching

November 10, 2016 by hgpu

Balancing locality and concurrency: solving sparse triangular systems on GPUs

Andrea Picciau, Gordon E. Inggs, John Wickerson, Eric C. Kerrigan, George A. Constantinides

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Tags: Algorithms, AMD FirePro W5000, ATI, Computer science, Linear Algebra, nVidia, nVidia Quadro K4000, OpenCL, Sparse matrix

November 8, 2016 by hgpu

A Memory Bandwidth-Efficient Hybrid Radix Sort on GPUs

Elias Stehle, Hans-Arno Jacobsen

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan X, Sorting

November 5, 2016 by hgpu

Extensions and Limitations of the Neural GPU

Eric Price, Wojciech Zaremba, Ilya Sutskever

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Tags: Algorithms, Computer science, CUDA, Deep learning, nVidia, Package, Python

November 3, 2016 by hgpu

LightRNN: Memory and Computation-Efficient Recurrent Neural Networks

Xiang Li, Tao Qin, Jian Yang, Tie-Yan Liu

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Tags: Algorithms, Computer science, Deep learning, Neural networks, NLP, nVidia, RNN, Tesla K20

November 1, 2016 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

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high performance computing on graphics processing units: hgpu.org

Programming

HIPAcc: A Domain-Specific Language and Compiler for Image Processing

Performance Analysis of Parallel Sorting Algorithms using GPU Computing

Automatic code generation methods applied to numerical linear algebra in high performance computing

OpenCL-based optimizations for acceleration of object tracking on FPGAs and GPUs

Hadoopcl2: Motivating the design of a distributed, heterogeneous programming system with machine-learning applications

Fractal Art Generation using GPUs

Shuffle Reduction Based Sparse Matrix-Vector Multiplication on Kepler GPU

Using multiple GPUs to accelerate string searching for digital forensic analysis

Balancing locality and concurrency: solving sparse triangular systems on GPUs

A Memory Bandwidth-Efficient Hybrid Radix Sort on GPUs

Extensions and Limitations of the Neural GPU

LightRNN: Memory and Computation-Efficient Recurrent Neural Networks

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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