high performance computing on graphics processing units: hgpu.org

hgpu.org » Memory level parallelism

Scalable Kernel Fusion for Memory-Bound GPU Applications

Mohamed Wahib and Naoya Maruyama

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Tags: CUDA, Memory level parallelism, nVidia GeForce GTX 750 Ti, Tesla K20, Tesla K40

September 1, 2014 by wahibium

Resource-Aware Compiler Prefetching for Fine-Grained Many-Cores

George C. Caragea, Alexandros Tzannes, Fuat Keceli, Rajeev Barua, Uzi Vishkin

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Tags: Algorithms, ASIC, Benchmarking, Computer science, Memory level parallelism, nVidia, Package, Prefetch

December 29, 2011 by hgpu

Memory-level and Thread-level Parallelism Aware GPU Architecture Performance Analytical Model

Sunpyo Hong, Hyesoon Kim

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Tags: Analytical model, Benchmarking, Computer science, CUDA, Memory level parallelism, nVidia, nVidia Quadro FX 5600, Warp level parallelism

December 15, 2011 by hgpu

Accelerating Parameter Sweep Applications Using CUDA

Masaya Motokubota, Fumihiko Ino, Kenichi Hagihara

Tags: Computer science, CUDA, Memory level parallelism, nVidia, Performance

June 14, 2011 by hgpu

An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness

Sunpyo Hong, Hyesoon Kim

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Tags: Analytical model, Computer science, CUDA, Memory level parallelism, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 8800 GTX, nVidia Quadro FX 5600, Warp level parallelism

October 29, 2010 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

Scalable Kernel Fusion for Memory-Bound GPU Applications

Resource-Aware Compiler Prefetching for Fine-Grained Many-Cores

Memory-level and Thread-level Parallelism Aware GPU Architecture Performance Analytical Model

Accelerating Parameter Sweep Applications Using CUDA

An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness

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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