high performance computing on graphics processing units: hgpu.org

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Analyzing and Improving the Performance of Spatial Database Processing

Bogdan Simion

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Thesis

March 20, 2016 by hgpu

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices

Nicholas D. Lane, Sourav Bhattacharya, Petko Georgiev, Claudio Forlivesi, Lei Jiao, Lorena Qendro, Fahim Kawsar

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia Jetson TK1, SoC

March 15, 2016 by hgpu

DySel: Lightweight Dynamic Selection for Kernel-based Data-parallel Programming Model

Li-Wen Chang, Hee-Seok Kim, Wen-mei Hwu

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, OpenCL, Performance, Tesla K20

March 15, 2016 by hgpu

Faster and Cheaper: Parallelizing Large-Scale Matrix Factorization on GPUs

Wei Tan, Liangliang Cao, Liana Fong

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Factorization, nVidia, nVidia GeForce GTX Titan X, OpenMP, Tesla K80

March 15, 2016 by hgpu

Machine Learning at the Limit

John Canny, Huasha Zhao, Ye Chen, Bobby Jaros, Jiangchang Mao

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan X, Package

March 12, 2016 by hgpu

Accelerating Wright-Fisher Forward Simulations on the Graphics Processing Unit

David S. Lawrie

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Tags: Algorithms, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 780 M, nVidia GeForce GTX 980

March 10, 2016 by hgpu

Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Varun Nagpal

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Tesla C1060, Thesis

March 10, 2016 by hgpu

Testing fine-grained parallelism for the ADMM on a factor-graph

Ning Hao, AmirReza Oghbaee, Mohammad Rostami, Nate Derbinsky, Jose Bento

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Tags: Algorithms, Computer science, CUDA, Mathematical Software, nVidia, OpenMP, Package, Tesla K40

March 10, 2016 by hgpu

Pragma Directed Shared Memory Centric Optimizations on GPUs

Jing Li, Lei Liu, Yuan Wu, Xiang-Hua Liu, Yi Gao, Xiao-Bing Feng, Cheng-Yong Wu

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Tags: ATI, ATI Radeon HD 7850, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, OpenACC, OpenCL, Tesla C2050

March 10, 2016 by hgpu

D-face: Parallel Implementation of CNN Based Face Classifier using Drone Data On K40 & Jetson TK1

Harish, Ayyappa, Santosh, P K Baruah, Kaliuday Balleda, Sairam K M Menon

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Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia Jetson TK1, Tesla K40

March 8, 2016 by hgpu

Topology optimization design of 3D electrothermomechanical actuators by using GPU as a co-processor

Francisco Javier Ramírez-Gil, Emilío Carlos Nelli Silva, Wilfredo Montealegre-Rubio

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Tags: CUDA

March 7, 2016 by fjramireg

Performance Analysis of kNN on large datasets using CUDA & Pthreads

Sriram Kankatala

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Tags: Computer science, CUDA, Data mining, Databases, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX 550 Ti, Pattern recognition, Pthreads, Thesis

March 5, 2016 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Analyzing and Improving the Performance of Spatial Database Processing

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices

DySel: Lightweight Dynamic Selection for Kernel-based Data-parallel Programming Model

Faster and Cheaper: Parallelizing Large-Scale Matrix Factorization on GPUs

Machine Learning at the Limit

Accelerating Wright-Fisher Forward Simulations on the Graphics Processing Unit

Study and evaluation of an Irregular Graph Algorithm on Multicore and GPU Processor Architectures

Testing fine-grained parallelism for the ADMM on a factor-graph

Pragma Directed Shared Memory Centric Optimizations on GPUs

D-face: Parallel Implementation of CNN Based Face Classifier using Drone Data On K40 & Jetson TK1

Topology optimization design of 3D electrothermomechanical actuators by using GPU as a co-processor

Performance Analysis of kNN on large datasets using CUDA & Pthreads

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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