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Efficient Target and Application Specific Selection and Ordering of Compiler Passes

Ricardo Jorge Ferreira Nobre

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Tags: Code generation, Compilers, Computer science, CUDA, Design space exploration, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX 460, nVidia GeForce GTX 480, OpenCL, PTX, Thesis

November 26, 2017 by hgpu

GPU-Accelerated Parallel Finite-Difference Time-Domain Method for Electromagnetic Waves Propagation in Unmagnetized Plasma Media

Xi-min Wang, Lang-lang Xiong, Song Liu, Zhi-yun Peng, Shuang-ying Zhong

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Tags: Computational Physics, CUDA, FDTD, Finite-difference time-domain, nVidia, nVidia GeForce GT 650 M, Physics, Plasma physics

September 12, 2017 by hgpu

An Adaptive Multi-Spline Refinement Algorithm in Simulation Based Sailboat Trajectory Optimization Using Onboard Multi-Core Computer Systems

Roman Debski

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Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GT 650 M, OpenCL

July 5, 2016 by hgpu

OpenCL Cryptographic Library

Martin Preisler

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Tags: AES, Algorithms, Computer science, Intel HD Graphics 4000, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX 460, nVidia GeForce GTX 580, OpenCL, Security, Thesis

March 20, 2016 by hgpu

GPU Robot Motion Planning using Semi-Infinite Nonlinear Programming

Benjamin Chretien, Adrien Escande, Abderrahmane Kheddar

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Tags: Computer science, CUDA, Nonlinear optimization, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX Titan Black, Robotics, Tesla C2070

February 25, 2016 by hgpu

A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

Rahul Garg

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Tags: AMD Radeon HD 8650, ATI, ATI Radeon HD 7970, Benchmarking, Code generation, Computer science, Intel HD Graphics 4000, Matlab, Matrix multiplication, nVidia, nVidia GeForce GT 650 M, OpenCL, Package, Python, Tesla C2050, Thesis

October 6, 2015 by hgpu

A Parallel Cellular Automaton Simulation Framework using CUDA

Ryno Fourie

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Tags: Algorithms, Cellular automata, Computer science, CUDA, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX 780, Thesis

June 1, 2015 by hgpu

Extending the Gotran framework: LATEX and GPU acceleration

George Bahijevitch Bahij

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Tags: Computational modelling, Computer science, CUDA, Differential equations, nVidia, nVidia GeForce GT 650 M, nVidia GeForce GTX Titan, ODEs, Ordinary differential equations, Python, Thesis

February 6, 2015 by hgpu

Parallel Hierarchical Clustering on the GPU

Ursula Reiterer

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Tags: Algorithms, Clustering, Computer science, nVidia, nVidia GeForce GT 650 M, OpenCL, PTX, Thesis

September 20, 2014 by hgpu

Transparent Checkpoint-Restart for Hardware-Accelerated 3D Graphics

Samaneh Kazemi, Rohan Garg, Gene Cooperman

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Tags: Computer science, nVidia, nVidia GeForce GT 650 M, OpenGL, Operating systems

December 24, 2013 by hgpu

Real-time Building Airflow Simulation Aided by GPU and FFD

Pu Yang

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Tags: Algorithms, CUDA, Flow analysis, Fluid dynamics, nVidia, nVidia GeForce GT 650 M, Thesis

November 24, 2013 by hgpu

GooFit: A library for massively parallelising maximum-likelihood fits

R. Andreassen, B. T. Meadows, M. de Silva, M. D. Sokoloff, K. Tomko

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Tags: Computer science, CUDA, Mathematical Software, nVidia, nVidia GeForce GT 650 M, Package, Probability, Tesla C2050, Tesla C2070

November 8, 2013 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

IterApp: Iterative Application Skeleton

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

See all packages

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high performance computing on graphics processing units: hgpu.org

Efficient Target and Application Specific Selection and Ordering of Compiler Passes

GPU-Accelerated Parallel Finite-Difference Time-Domain Method for Electromagnetic Waves Propagation in Unmagnetized Plasma Media

An Adaptive Multi-Spline Refinement Algorithm in Simulation Based Sailboat Trajectory Optimization Using Onboard Multi-Core Computer Systems

OpenCL Cryptographic Library

GPU Robot Motion Planning using Semi-Infinite Nonlinear Programming

A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

A Parallel Cellular Automaton Simulation Framework using CUDA

Extending the Gotran framework: LATEX and GPU acceleration

Parallel Hierarchical Clustering on the GPU

Transparent Checkpoint-Restart for Hardware-Accelerated 3D Graphics

Real-time Building Airflow Simulation Aided by GPU and FFD

GooFit: A library for massively parallelising maximum-likelihood fits

Recent source codes

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

KSig: GPU-accelerated computation of popular time series kernels

IterApp: Iterative Application Skeleton

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

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