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GPU Array Access Auto-Tuning

Nicolas Weber

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 440, nVidia GeForce GT 620, nVidia GeForce GT 730, nVidia GeForce GTX 1080, nVidia GeForce GTX 480, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 570, nVidia GeForce GTX 590, nVidia GeForce GTX 680, nVidia GeForce GTX 780, nVidia GeForce GTX 980, nVidia GeForce GTX Titan X, Performance, performance portability, Tesla C2070, Tesla K20, Thesis

August 8, 2017 by hgpu

Synthesis of Embedded Software using Dataflow Schedule Graphs

Abhay Raina

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Tags: Computer science, DSP, nVidia, nVidia GeForce GTX 680, OpenCL, Signal processing, Thesis

July 2, 2017 by hgpu

Advanced Concurrency Control Algorithm Design and GPU System Support for High Performance In-Memory Data Management

Yuan Yuan

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenCL, Thesis

February 7, 2017 by hgpu

Parallelization of BVH and BSP on the GPU

Martin Imre

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Tags: 3D Graphics and Realism, Algorithms, Computer science, nVidia, nVidia GeForce GTX 680, OpenCL, Raytracing, Rendering, Sorting, Thesis, Visualization

January 10, 2017 by hgpu

A Comparison of GPU Execution Time Prediction using Machine Learning and Analytical Modeling

Marcos Amaris, Raphael Y. de Camargo, Mohamed Dyab, Alfredo Goldman, Denis Trystram

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Tags: Analytical model, Benchmarking, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX 970, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, nVidia GeForce GTX Titan Black, nVidia GeForce GTX Titan X, nVidia Quadro K5200, Package, Performance, Tesla K20, Tesla K40

December 6, 2016 by hgpu

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

Pedro Miguel Marques Pereira

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Tags: Algorithms, AMD Radeon R9 290X, ARM, ATI, ATI Radeon HD 7970, Compression, Computer science, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 570 M, nVidia GeForce GTX 680, nVidia GeForce GTX 750 Ti, nVidia GeForce GTX Titan Black, nVidia Jetson TK1, OpenCL, OpenMP, Thesis

November 30, 2016 by hgpu

HPVM: A Portable Virtual Instruction Set for Heterogeneous Parallel Systems

Prakalp Srivastava, Maria Kotsifakou, Vikram Adve

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Tags: Code generation, Computer science, Data parallelism, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, OpenCL, performance portability

November 5, 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

The GPU-based Parallel Ant Colony System

Rafal Skinderowicz

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Tags: Ant colony optimization, Computer science, CUDA, Metaheuristics, nVidia, nVidia GeForce GTX 680

May 11, 2016 by hgpu

A Graph-based Model for GPU Caching Problems

Lingda Li, Ari B. Hayes, Stephen A. Hackler, Eddy Z. Zhang, Mario Szegedy, Shuaiwen Leon Song

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 680, Task scheduling

May 9, 2016 by hgpu

Machine Learning at the Limit

John Canny, Huasha Zhao, Ye Chen, Bobby Jaros, Jiangchang Mao

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan X, Package

March 12, 2016 by hgpu

Parallel Approaches to Shortest-Path Problems for Multilevel Heterogeneous Computing

Hector Ortega Arranz

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Path problems, Thesis

February 25, 2016 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

GPU Array Access Auto-Tuning

Synthesis of Embedded Software using Dataflow Schedule Graphs

Advanced Concurrency Control Algorithm Design and GPU System Support for High Performance In-Memory Data Management

Parallelization of BVH and BSP on the GPU

A Comparison of GPU Execution Time Prediction using Machine Learning and Analytical Modeling

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

HPVM: A Portable Virtual Instruction Set for Heterogeneous Parallel Systems

A Non-linear GPU Thread Map for Triangular Domains

The GPU-based Parallel Ant Colony System

A Graph-based Model for GPU Caching Problems

Machine Learning at the Limit

Parallel Approaches to Shortest-Path Problems for Multilevel Heterogeneous Computing

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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