high performance computing on graphics processing units: hgpu.org

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Hybrid CPU-GPU generation of the Hamiltonian and Overlap matrices in FLAPW methods

Diego Fabregat-Traver, Davor Davidovic, Markus Hohnerbach, Edoardo Di Napoli

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Tags: Computer science, CUDA, nVidia, Performance, Tesla K20, Tesla K40, Tesla K80

November 3, 2016 by hgpu

Classification Performance of Convolutional Neural Networks

Niklas Mattsson

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Tags: Computer science, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 960, nVidia Tegra TX1, Performance, Python, Theano, Thesis

November 1, 2016 by hgpu

Towards Automating Multi-dimensional Data Decomposition for Executing a Single-GPU Code on a Multi-GPU System

Ryotaro Sakai, Fumihiko Ino, Kenichi Hagihara

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, Performance, Tesla K40

November 1, 2016 by hgpu

Performance Optimization of 3-D Lattice Boltzmann Flow Solver on a GPU

Nhat-Phuong Tran, Myungho Lee, Sugwon Hong

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Tags: Computer science, CUDA, Fluid dynamics, Lattice Boltzmann model, Numerical simulation, nVidia, Performance, Tesla K20

November 1, 2016 by hgpu

Hetero-Mark, A Benchmark Suite for CPU-GPU Collaborative Computing

Yifan Sun, Xiang Gong, Amir Kavyan Ziabari, Leiming Yu, Xiangyu Li, Saoni Mukherjee, Carter McCardwell, Alejandro Villegas, David Kaeli

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Tags: Benchmarking, Computer science, Heterogeneous systems, OpenCL, Package, Performance

October 29, 2016 by hgpu

GPU Performance Modeling and Optimization

Ang Li

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, Performance, PTX, Thesis

October 29, 2016 by hgpu

Understanding Latency Hiding on GPUs

Vasily Volkov

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Performance, Thesis

October 12, 2016 by hgpu

FastCollect: Offloading Generational Garbage Collection to Integrated GPUs

Abhinav, Rupesh Nasre

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Tags: Algorithms, Benchmarking, Computer science, Intel HD Graphics 4000, Java, OpenCL, Performance

September 27, 2016 by hgpu

Solving Batched Linear Programs on GPU and Multicore CPU

Amit Gurung, Rajarshi Ray

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Tags: Computer science, CUDA, nVidia, Package, Performance, Tesla K40

September 27, 2016 by hgpu

A Lightweight Approach to Performance Portability with targetDP

Alan Gray, Kevin Stratford

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Tags: Computer science, CUDA, Intel Xeon Phi, nVidia, Package, Performance, performance portability, QCD, Tesla K20, Tesla K40

September 8, 2016 by hgpu

A Non-linear GPU Thread Map for Triangular Domains

Cristobal A. Navarro, Benjamin Bustos, Nancy Hitschfeld

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 765 M, Performance, Tesla K40

September 8, 2016 by hgpu

A Survey of Techniques for Architecting Processor Components using Domain Wall Memory

Sparsh Mittal

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Tags: cache, cpu, energy, GPU, main memory, Performance, Register file, Reliability

September 5, 2016 by sparsh0mittal

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

Hybrid CPU-GPU generation of the Hamiltonian and Overlap matrices in FLAPW methods

Classification Performance of Convolutional Neural Networks

Towards Automating Multi-dimensional Data Decomposition for Executing a Single-GPU Code on a Multi-GPU System

Performance Optimization of 3-D Lattice Boltzmann Flow Solver on a GPU

Hetero-Mark, A Benchmark Suite for CPU-GPU Collaborative Computing

GPU Performance Modeling and Optimization

Understanding Latency Hiding on GPUs

FastCollect: Offloading Generational Garbage Collection to Integrated GPUs

Solving Batched Linear Programs on GPU and Multicore CPU

A Lightweight Approach to Performance Portability with targetDP

A Non-linear GPU Thread Map for Triangular Domains

A Survey of Techniques for Architecting Processor Components using Domain Wall Memory

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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