high performance computing on graphics processing units: hgpu.org

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Toward Automatic Translation: From OpenACC to OpenMP 4

Nawrin Sultana

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Tags: Algorithms, Code generation, Compilers, Computer science, nVidia, OpenACC, OpenMP, Tesla K40, Thesis

December 17, 2016 by hgpu

Parallel Level set algorithm with MPI and accelerated on GPU

Zhenlin Wang

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Tags: Computational Physics, CUDA, Finite difference, MPI, nVidia, Package, PDEs, Physics

December 17, 2016 by hgpu

Speedup for quantum optimal control from GPU-based automatic differentiation

Nelson Leung, Mohamed Abdelhafez, Jens Koch, David I. Schuster

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Tags: Algorithms, CUDA, Deep learning, Mesoscale and Nanoscale Physics, Numerical simulation, nVidia, Package, Physics, Python, Quantum Physics, TensorFlow, Tesla K40

December 17, 2016 by hgpu

Translating OpenMP Device Constructs to OpenCL using Unnecessary Data Transfer Elimination

Junghyun Kim, Yong-Jun Lee, Jungho Park, Jaejin Lee

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Tags: AMD Radeon R9 390X, ATI, Benchmarking, Code generation, Computer science, nVidia, nVidia GeForce GTX Titan X, OpenACC, OpenCL, OpenMP

December 14, 2016 by hgpu

Towards Comprehensive Parametric Code Generation Targeting Graphics Processing Units in Support of Scientific Computation

Ning Xie

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Tags: Code generation, Computer science, CUDA, nVidia, OpenMP, Tesla M2050, Thesis

December 14, 2016 by hgpu

nmfgpu4R: GPU-Accelerated Computation of the Non-Negative Matrix Factorization (NMF) Using CUDA Capable Hardware

Sven Koitka, Christoph M. Friedrich

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Tags: Benchmarking, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX Titan X, Package, Tesla K80

December 14, 2016 by hgpu

GaDei: On Scale-up Training As A Service For Deep Learning

Wei Zhang, Minwei Feng, Yunhui Zheng, Yufei Ren, Yandong Wang, Ji Liu, Peng Liu, Bing Xiang, Li Zhang, Bowen Zhou

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Tags: Computer science, CUDA, Deep learning, nVidia, Tesla K20, Tesla K80

December 14, 2016 by hgpu

cusFFT: A High-Performance Sparse Fast Fourier Transform Algorithm on GPUs

Cheng Wang, Sunita Chandrasekaran, Barbara Chapman

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Tags: CUDA, FFT, Tesla K20

December 10, 2016 by hgpu

Implementing and Evaluating Candidate-Based Invariant Generation

Adam Betts, Nathan Chong, Pantazis Deligiannis, Alastair F. Donaldson, Jeroen Ketema

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Tags: Benchmarking, Computer science, CUDA, nVidia, OpenCL, Software Engineering

December 10, 2016 by hgpu

GPGPU Accelerated Deep Object Classification on a Heterogeneous Mobile Platform

Syed Tahir Hussain Rizvi, Gianpiero Cabodi, Denis Patti, Gianluca Francini

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Tags: CNN, Computer science, CUDA, Deep learning, Heterogeneous systems, Image processing, Matrix multiplication, Neural networks, nVidia, nVidia Jetson TK1

December 10, 2016 by hgpu

Parallelization and Performance of the NIM Weather Model for CPU, GPU and MIC Processors

Mark Govett, Jim Rosinski, Jacques Middlecoff, Tom Henderson, Jin Lee, Alexander MacDonald, Paul Madden, Julie Schramm, Antonio Duarte

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Tags: CUDA, Earth and Space Sciences, Fortran, Intel Xeon Phi, nVidia, OpenACC, Tesla K80, Weather prediction, Weather Prediction Model

December 6, 2016 by hgpu

Brownian Dynamics of Active Sphere Suspensions Confined Near a No-Slip Boundary

Florencio Balboa Usabiaga, Blaise Delmotte, Aleksandar Donev

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Tags: Condensed matter, CUDA, nVidia, Package, Physics, pyCUDA, Soft Condensed Matter

December 6, 2016 by hgpu

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Toward Automatic Translation: From OpenACC to OpenMP 4

Parallel Level set algorithm with MPI and accelerated on GPU

Speedup for quantum optimal control from GPU-based automatic differentiation

Translating OpenMP Device Constructs to OpenCL using Unnecessary Data Transfer Elimination

Towards Comprehensive Parametric Code Generation Targeting Graphics Processing Units in Support of Scientific Computation

nmfgpu4R: GPU-Accelerated Computation of the Non-Negative Matrix Factorization (NMF) Using CUDA Capable Hardware

GaDei: On Scale-up Training As A Service For Deep Learning

cusFFT: A High-Performance Sparse Fast Fourier Transform Algorithm on GPUs

Implementing and Evaluating Candidate-Based Invariant Generation

GPGPU Accelerated Deep Object Classification on a Heterogeneous Mobile Platform

Parallelization and Performance of the NIM Weather Model for CPU, GPU and MIC Processors

Brownian Dynamics of Active Sphere Suspensions Confined Near a No-Slip Boundary

Recent source codes

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

BoltzGen:Toward Universal Binder Design

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

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