high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

Optimization and Large Scale Computation of an Entropy-Based Moment Closure

C. Kristopher Garrett, Cory Hauck, Judith Hill

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Tags: Algorithms, CUDA, Heterogeneous systems, nVidia, OpenMP, Physics, Tesla K20

February 3, 2016 by hgpu

GPGPU Multi Object Bayesian Tracking with an embedded System on a Chip

David Webb

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Tags: Bayesian, Computer science, Computer vision, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 960, nVidia Jetson TK1, SoC, Thesis

February 2, 2016 by hgpu

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

Luka Stanisic

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Tesla C2050, Tesla K20, Tesla K40, Tesla M2070, Tesla M2075, Thesis

February 1, 2016 by hgpu

Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language

Tobias Klein

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Tags: Computer science, CUDA, DSL, Heterogeneous systems, Image processing, nVidia, nVidia Quadro 6000, OpenCL, Thesis, Visualization

January 29, 2016 by hgpu

Heterogeneous (CPU+GPU) Working-set Hash Tables

Ziaul Choudhury, Suresh Purini

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Tags: Computer science, CUDA, Hashing, Heterogeneous systems, nVidia, Tesla K20

January 22, 2016 by hgpu

Adaptive and Hybrid Machine Learning Approaches Utilizing General Purpose Computing on Graphical Processing Units

Mohammed Abdelrahim

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Tags: Computer science, CUDA, Heterogeneous systems, LSTM, Machine learning, nVidia, nVidia GeForce GTX 770, OpenMP, Thesis

January 19, 2016 by hgpu

A framework for efficient execution on GPU and CPU+GPU systems

Jean-Francois Dollinger

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 590, nVidia GeForce GTX 680, Performance, Thesis

January 19, 2016 by hgpu

Batched Linear Algebra Problems on GPU Accelerators

Tingxing Dong

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Tags: Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K40, Thesis

January 4, 2016 by hgpu

Programming Models and Scheduling Techniques for Heterogeneous Architectures

Judit Planas Carbonell

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OmpSs, Task scheduling, Tesla K20, Tesla K40, Tesla M2090, Thesis

January 4, 2016 by hgpu

On the Development and Implementation of High-Order Flux Reconstruction Schemes for Computational Fluid Dynamics

Freddie David Witherden

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Source codes

Tags: AMD FirePro W9100, ATI, CUDA, Finite difference, Fluid dynamics, Heterogeneous systems, MPI, nVidia, OpenCL, Package, Python, Tesla K40, Thesis

December 23, 2015 by hgpu

OpenDwarfs: Characterization of Dwarf-Based Benchmarks on Fixed and Reconfigurable Architectures

Konstantinos Krommydas, Wu-chun Feng, Christos D. Antonopoulos, Nikolaos Bellas

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Tags: ATI, ATI Radeon HD 6550, ATI Radeon HD 7660, ATI Radeon HD 7970, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, OpenCL, Package

December 22, 2015 by hgpu

Parallel FDTD Arithmetic Simulation Based on Distributed Heterogeneous Cluster System

Feng Yuan, Tang Xiaobin, Gong Xiaoyan

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Tags: Computer science, Electrodynamics, FDTD, Finite-difference time-domain, GPU cluster, Heterogeneous systems, MPI, nVidia, OpenCL, Physics, Tesla K20, Tesla M2070

December 22, 2015 by hgpu

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

hls4ml: Machine learning on FPGAs using HLS

hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

See all packages

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high performance computing on graphics processing units: hgpu.org

Optimization and Large Scale Computation of an Entropy-Based Moment Closure

GPGPU Multi Object Bayesian Tracking with an embedded System on a Chip

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language

Heterogeneous (CPU+GPU) Working-set Hash Tables

Adaptive and Hybrid Machine Learning Approaches Utilizing General Purpose Computing on Graphical Processing Units

A framework for efficient execution on GPU and CPU+GPU systems

Batched Linear Algebra Problems on GPU Accelerators

Programming Models and Scheduling Techniques for Heterogeneous Architectures

On the Development and Implementation of High-Order Flux Reconstruction Schemes for Computational Fluid Dynamics

OpenDwarfs: Characterization of Dwarf-Based Benchmarks on Fixed and Reconfigurable Architectures

Parallel FDTD Arithmetic Simulation Based on Distributed Heterogeneous Cluster System

Recent source codes

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

hls4ml: Machine learning on FPGAs using HLS

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

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