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hgpu.org » Applications » Computer science

Performance Evaluation and Tuning of An OpenCL based Matrix Multiplier

Yiyu Tan, Toshiyuki Imamura

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Tags: Computer science, FPGA, Linear Algebra, Matrix multiplication, OpenCL

September 2, 2018 by hgpu

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

Jianyu Huang, Chenhan D. Yu, Robert A. van de Geijn

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Package, Tesla V100

September 2, 2018 by hgpu

Full Speed Ahead: 3D Spatial Database Acceleration with GPUs

Lucas C. Villa Real, Bruno Silva

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Tags: Computer science, CUDA, Databases, nVidia, Tesla V100

September 2, 2018 by hgpu

A study of integer sorting on multicores

Alexandros V. Gerbessiotis

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Tags: Algorithms, Computer science, MPI, Package, Performance, Sorting

September 2, 2018 by hgpu

Optimizing Web Virtual Reality

Rabimba Karanjai

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Tags: Benchmarking, Computer science, Java, OpenGL, Rendering, Thesis, Virtual reality, WebGL

August 26, 2018 by hgpu

Auto-tuning Hybrid CPU-GPU Execution of Algorithmic Skeletons in SkePU

Tomas Ohberg

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Tags: Computer science, CUDA, Heterogeneous systems, Hybrid computing, nVidia, OpenCL, Tesla K20, Thesis

August 26, 2018 by hgpu

Performance Evaluation of OpenMP’s Target Construct on GPUs – Exploring Compiler Optimizations

Akihiro Hayashi, Jun Shirako, Etorre Tiotto, Robert Ho, Vivek Sarkar

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Tags: Compilers, Computer science, CUDA, LLVM, nVidia, OpenMP, Performance, Tesla K80, Tesla P100

August 26, 2018 by hgpu

A Qualitative Comparison Study Between Common GPGPU Frameworks

Adam Soderstrom

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Tags: Computer science, CUDA, DirectCompute, DirectX, N-body simulation, nVidia, nVidia GeForce GTX 1050, OpenCL, Thesis

August 26, 2018 by hgpu

Kernel Tuner: A search-optimizing GPU code auto-tuner

Ben van Werkhoven

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Tags: AMD Radeon Vega Frontier Edition, ATI, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, OpenCL, Optimization, Package

August 19, 2018 by hgpu

Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures

Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke

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Tags: Computer science, Deep learning, Intel Xeon Phi, OpenMP, Package, Performance

August 19, 2018 by hgpu

Matrix Factorization on GPUs with Memory Optimization and Approximate Computing

Wei Tan, Shiyu Chang, Liana Fong, Cheng Li, Zijun Wang, Liangliang Cao

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Tags: Algorithms, Compression, Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX Titan X, Package

August 19, 2018 by hgpu

libhclooc: Software Library Facilitating Out-of-core Implementations of Accelerator Kernels on Hybrid Computing Platforms

Daniel Hanlon, Hamidreza Khalighzadeh, Ravi Reddy Manumachu, Alexey Lastovetsky

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Tags: Cloud, Computer science, CUDA, FPGA, Hybrid computing, Intel Xeon Phi, Matrix multiplication, nVidia, OpenCL, Package

August 19, 2018 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

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high performance computing on graphics processing units: hgpu.org

Applications

Performance Evaluation and Tuning of An OpenCL based Matrix Multiplier

Implementing Strassen’s Algorithm with CUTLASS on NVIDIA Volta GPUs

Full Speed Ahead: 3D Spatial Database Acceleration with GPUs

A study of integer sorting on multicores

Optimizing Web Virtual Reality

Auto-tuning Hybrid CPU-GPU Execution of Algorithmic Skeletons in SkePU

Performance Evaluation of OpenMP’s Target Construct on GPUs – Exploring Compiler Optimizations

A Qualitative Comparison Study Between Common GPGPU Frameworks

Kernel Tuner: A search-optimizing GPU code auto-tuner

Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures

Matrix Factorization on GPUs with Memory Optimization and Approximate Computing

Recent source codes

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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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