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Understanding the ISA impact on GPU Architecture

Mayank Vinodbhai Kothiya

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Tags: Computer science, CUDA, GPGPU-sim, Hardware Architecture, nVidia, PTX, Tesla, Thesis

July 28, 2014 by hgpu

Cofactorization on Graphics Processing Units

Andrea Miele, Joppe W. Bos, Thorsten Kleinjung, Arjen K. Lenstra

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Tags: Computer science, CUDA, Factorization, nVidia, nVidia GeForce GTX 580, PTX, Security

June 3, 2014 by hgpu

Performance Optimization of GPU ELF-Codes

Fausto Artico

Tags: Algorithms, Computer science, CUDA, nVidia, Optimization, PTX, Tesla C2070, Thesis

May 15, 2014 by hgpu

Piko: A Design Framework for Programmable Graphics Pipelines

Anjul Patney, Stanley Tzeng, Kerry A. Seitz Jr., John D. Owens

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Tags: 3D Graphics and Realism, Code generation, Computer science, nVidia, nVidia GeForce GTX 680, OpenCL, PTX, Rasterization, Raytracing, Rendering

April 29, 2014 by hgpu

The Promises of Hybrid Hexagonal/Classical Tiling for GPU

Tobias Grosser, Sven Verdoolaege, Albert Cohen, P. Sadayappan

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, nVidia Quadro NVS 5200 M, PTX

July 31, 2013 by hgpu

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

Dmitry Mikushin, Nikolay Likhogrud, Eddy Zheng Zhang, Christopher Bergstrom

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Tags: Code generation, Compilers, Computer science, CUDA, Fortran, nVidia, OpenACC, Package, PTX, Tesla K20

July 15, 2013 by hgpu

A model of dynamic compilation for heterogeneous compute platforms

Andrew Kerr

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, OpenCL, PTX, Thesis

June 29, 2013 by hgpu

GPU Programming in Rust: Implementing High Level Abstractions in a Systems Level Language

Eric Holk, Milinda Pathirage, Arun Chauhan, Andrew Lumsdaine, Nicholas D. Matsakis

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Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GTX 460, OpenCL, Package, PTX

June 17, 2013 by hgpu

Towards shared memory consistency models for GPUs

Tyler Sorensen

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Tags: Computer science, CUDA, Memory model, nVidia, Performance, PTX, Thesis

June 4, 2013 by hgpu

Fast Makespan Estimation for GPU Threads on a Single Streaming Multiprocessor

Kostiantyn Berezovskyi, Konstantinos Bletsas, Stefan M. Petters

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Tags: Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 680, PTX, Timing analysis

April 22, 2013 by hgpu

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Yongchao Liu, Adrianto Wirawan, Bertil Schmidt

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Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 690, Package, PTX, Sequence alignment, Smith-Waterman algorithm

April 10, 2013 by hgpu

Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling

Jianlong Zhong, Bingsheng He

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, PTX, Task scheduling, Tesla C2050

March 23, 2013 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

Understanding the ISA impact on GPU Architecture

Cofactorization on Graphics Processing Units

Performance Optimization of GPU ELF-Codes

Piko: A Design Framework for Programmable Graphics Pipelines

The Promises of Hybrid Hexagonal/Classical Tiling for GPU

KernelGen – the design and implementation of a next generation compiler platform for accelerating numerical models on GPUs

A model of dynamic compilation for heterogeneous compute platforms

GPU Programming in Rust: Implementing High Level Abstractions in a Systems Level Language

Towards shared memory consistency models for GPUs

Fast Makespan Estimation for GPU Threads on a Single Streaming Multiprocessor

CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions

Kernelet: High-Throughput GPU Kernel Executions with Dynamic Slicing and Scheduling

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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