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Accelerated cryo-EM structure determination with parallelisation using GPUs in relion-2

Dari Kimanius, Bjorn O Forsberg, Sjors HW Scheres, Erik Lindahl

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Tags: Biology, Cryo-EM, CUDA, Image processing, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980 Ti

July 5, 2016 by hgpu

OpenCL Implementation of a Parallel Universal Kriging Algorithm for Massive Spatial Data Interpolation on Heterogeneous Systems

Fang Huang, Shuanshuan Bu, Jian Tao, Xicheng Tan

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Tags: Algorithms, Earth and Space Sciences, Geoscience, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Tesla K20

July 5, 2016 by hgpu

Time Predictability of GPU Kernel on an HSA Compliant Platform

Marcus Larsson, Nandinbaatar Tsog

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Tags: ATI, Computer science, Heterogeneous systems, HSA, OpenCL, Thesis

July 5, 2016 by hgpu

Compiler-Assisted Workload Consolidation For Efficient Dynamic Parallelism on GPU

Hancheng Wu, Da Li, Michela Becchi

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Tesla K20

June 30, 2016 by hgpu

Modified Levels of Parallel Odd-Even Transposition Sorting Network (OETSN) with GPU Computing using CUDA

Neetu Faujdar, SP Ghrera

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

June 30, 2016 by hgpu

DeepBE: Learning Deep Binary Encoding for Multi-Label Classification

Chenghua Li, Qi Kang, Guojing Ge, Qiang Song, Hanqing Lu, Jian Cheng

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Tags: Computer science, Computer vision, CUDA, Deep learning, Image recognition, Neural networks, nVidia, nVidia GeForce GTX Titan Black, nVidia GeForce GTX Titan X

June 30, 2016 by hgpu

Persistent RNNs: Stashing Recurrent Weights On-Chip

Gregory Diamos, Shubho Sengupta, Bryan Catanzaro, Mike Chrzanowski, Adam Coates, Erich Elsen, Jesse Engel, Awni Hannun, Sanjeev Satheesh

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Tags: Computer science, CUDA, Deep learning, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX Titan X, Package, RNN, Speech recognition

June 30, 2016 by hgpu

Parallel and Distributed Deep Learning

Vishakh Hegde, Sheema Usmani

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Tags: Caffe, CNN, Computer science, CUDA, Deep learning, nVidia, nVidia GRID K520

June 28, 2016 by hgpu

A Synchronization-Free Algorithm for Parallel Sparse Triangular Solves

Weifeng Liu, Ang Li, Jonathan Hogg, Iain S. Duff, Brian Vinter

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Tags: Algorithms, AMD Radeon R9 Fury X, ATI, Computer science, CUDA, Linear Algebra, nVidia GeForce GTX Titan X, OpenCL, Package, Sparse direct solvers, Tesla K40

June 28, 2016 by hgpu

Parallelizing Map Projection of Raster Data on Multi-core CPU and GPU Parallel Programming Frameworks

Daniel Chavez

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Tags: Computer science, CUDA, nVidia, nVidia Quadro 1000 M, OpenCL, Pthreads, Thesis

June 28, 2016 by hgpu

GPU Based Real-Time Welding Simulation with Smoothed-Particle Hydrodynamics

Qing Gu

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Tags: cfd, CUDA, Fluid dynamics, nVidia, OpenGL, Physics, Thesis

June 28, 2016 by hgpu

Accelerating High-Throughput Computing through OpenCL

Andrei Dafinoiu, Joshua Higgins, Violeta Holmes

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Tags: ATI, ATI Radeon HD 6570, Computer science, GPU cluster, nVidia, nVidia GeForce GTX 970, OpenCL, Tesla C2050

June 28, 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

Accelerated cryo-EM structure determination with parallelisation using GPUs in relion-2

OpenCL Implementation of a Parallel Universal Kriging Algorithm for Massive Spatial Data Interpolation on Heterogeneous Systems

Time Predictability of GPU Kernel on an HSA Compliant Platform

Compiler-Assisted Workload Consolidation For Efficient Dynamic Parallelism on GPU

Modified Levels of Parallel Odd-Even Transposition Sorting Network (OETSN) with GPU Computing using CUDA

DeepBE: Learning Deep Binary Encoding for Multi-Label Classification

Persistent RNNs: Stashing Recurrent Weights On-Chip

Parallel and Distributed Deep Learning

A Synchronization-Free Algorithm for Parallel Sparse Triangular Solves

Parallelizing Map Projection of Raster Data on Multi-core CPU and GPU Parallel Programming Frameworks

GPU Based Real-Time Welding Simulation with Smoothed-Particle Hydrodynamics

Accelerating High-Throughput Computing through OpenCL

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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