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Towards Green Computing: A Survey of Performance and Energy Efficiency of Different Platforms using OpenCL

Philip Heinisch, Katharina Ostaszewski, Hendrik Ranocha

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Tags: AMD FirePro S9150, AMD Radeon R9 280X, ARM, ATI, Benchmarking, Computer science, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia GeForce GTX 570, nVidia GRID K520, nVidia Titan RTX, OpenCL, survey, Tesla C2075, Tesla P100, Tesla V100

March 15, 2020 by hgpu

High Performance Portable Tsunami Simulations on Many-core CPU, GPU, and FPGA

Fumiya Kono

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Tags: AMD FirePro W8100, AMD FirePro W9100, AMD Radeon R9 280X, ATI, CUDA, Earth and Space Sciences, FPGA, Intel Xeon Phi, Numerical simulation, nVidia, OpenCL, Tesla K20, Thesis

December 9, 2018 by hgpu

FPGA-based Tsunami Simulation: Performance Comparison with GPUs, and Roofline Model for Scalability Analysis

Kohei Nagasu, Kentaro Sano, Fumiya Kono, Naohito Nakasato

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Tags: AMD Radeon R9 280X, ATI, Earth and Space Sciences, FPGA, nVidia, OpenCL, Performance, Tesla K20

April 3, 2017 by hgpu

Is GPGPU CCL worth it? A performance comparison between some GPU and CPU algorithms for solving connected components labeling on binary images

Alex Sundstrom, Victor Ahdel

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Tags: Algorithms, AMD Radeon R9 280X, ATI, Computer science, Image processing, nVidia, nVidia GeForce GTX 960, OpenCL, Performance, Thesis

February 26, 2017 by hgpu

Evaluation of Multi-Threading in Vulkan

Axel Blackert

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Tags: AMD Radeon R9 280X, ATI, Computer science, OpenGL, Rendering, Vulkan

January 4, 2017 by hgpu

Parallel Explicit FEM Algorithms Using GPU’s

Seyed Parsa Banihashemi

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Tags: Algorithms, AMD Radeon R9 280X, ATI, ATI Radeon HD 7970, Computer science, FEM, Finite element method, nVidia, nVidia GeForce GTX Titan, OpenCL, Particle swarm optimization, Performance, Tesla M2090, Thesis

January 22, 2016 by hgpu

GPU Kernels for High-Speed 4-Bit Astrophysical Data Processing

Peter Klages, Kevin Bandura, Nolan Denman, Andre Recnik, Jonathan Sievers, Keith Vanderlinde

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Tags: AMD Radeon R9 280X, Astrophysics, ATI, Instrumentation and Methods for Astrophysics, OpenCL, Package

March 23, 2015 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

Towards Green Computing: A Survey of Performance and Energy Efficiency of Different Platforms using OpenCL

High Performance Portable Tsunami Simulations on Many-core CPU, GPU, and FPGA

FPGA-based Tsunami Simulation: Performance Comparison with GPUs, and Roofline Model for Scalability Analysis

Is GPGPU CCL worth it? A performance comparison between some GPU and CPU algorithms for solving connected components labeling on binary images

Evaluation of Multi-Threading in Vulkan

Parallel Explicit FEM Algorithms Using GPU’s

GPU Kernels for High-Speed 4-Bit Astrophysical Data Processing

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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