high performance computing on graphics processing units: hgpu.org

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Acceleration of Cellular Automata through Parallel Computing with OpenCL

Maelso Bruno Pacheco Nunes Pereira, Christian Azambuja Pagot, Josue da Silva Gomes Junior, Jorge Gabriel Gomes de Souza Ramos, Tiago P. Nascimento, Alisson V. Brito

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Tags: Cellular automata, Computer science, nVidia, nVidia Quadro 600, OpenCL

December 10, 2017 by hgpu

On algorithmic reductions in task-parallel programming models

Jan Ciesko

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Tags: Computer science, Intel Xeon Phi, OpenMP, Package, Thesis

December 10, 2017 by hgpu

Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers

Azzam Haidar, Panruo Wu, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Artificial intelligence, BLAS, Computer science, Linar Algebra, Mixed precision, Neural networks, nVidia, Tesla P100

December 10, 2017 by hgpu

Distributed learning of CNNs on heterogeneous CPU/GPU architectures

Jose Marques, Gabriel Falcao, Luis A. Alexandre

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Tags: ATI, ATI Radeon HD 7500 M, CNN, Computer science, CUDA, Deep learning, Heterogeneous systems, Matlab, Neural networks, nVidia, nVidia GeForce GTX 840 M, nVidia GeForce GTX 940 M, nVidia GeForce GTX 950 M, OpenCL, Tesla K20

December 10, 2017 by hgpu

A tutorial on the implementations of linear image filters in CPU and GPU

Alvaro Pardo

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 430, Signal processing, Tutorial

December 7, 2017 by hgpu

Study of Bandwidth Partitioning for Co-executing GPU Kernels

Erik Melander

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Tags: Computer science, CUDA, nVidia, Performance, Tesla K20, Thesis

December 7, 2017 by hgpu

Methods for GPU Acceleration of Big Data Applications

Reza Mokhtari

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Tags: big data, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan Black, Thesis

December 3, 2017 by hgpu

Blocked All-Pairs Shortest Paths Algorithm on Intel Xeon Phi KNL Processor: A Case Study

Enzo Rucci, Armando De Giusti, Marcelo Naiouf

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Tags: All-Pairs Distance, Computer science, Intel Xeon Phi, OpenMP

December 3, 2017 by hgpu

A Hybrid-parallel Architecture for Applications in Bioinformatics

Jan Christian Kassens

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Tags: Algorithms, Bioinformatics, Biology, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 780 Ti, Thesis

December 3, 2017 by hgpu

STAR-RT: Visual attention for real-time video game playing

Iuliia Kotseruba, John K. Tsotsos

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Tags: AMD FirePro W7000, Artificial intelligence, ATI, Computer science, Games, GLSL, OpenCL, OpenGL

December 3, 2017 by hgpu

Qualcomm Snapdragon Mobile Platform OpenCL General Programming and Optimization

Qualcomm Technologies, Inc

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Tags: Computer science, OpenCL, Package, Whitepaper

November 30, 2017 by hgpu

Implementing implicit OpenMP data sharing on GPUs

Gheorghe-Teodor Bercea, Carlo Bertolli, Arpith C. Jacob, Alexandre Eichenberger, Alexey Bataev, Georgios Rokos, Hyojin Sung, Tong Chen, Kevin O'Brien

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Tags: Computer science, CUDA, LLVM, Memory model, nVidia, OpenMP, Programming Languages, PTX, Tesla K40, Tesla P100

November 30, 2017 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Acceleration of Cellular Automata through Parallel Computing with OpenCL

On algorithmic reductions in task-parallel programming models

Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers

Distributed learning of CNNs on heterogeneous CPU/GPU architectures

A tutorial on the implementations of linear image filters in CPU and GPU

Study of Bandwidth Partitioning for Co-executing GPU Kernels

Methods for GPU Acceleration of Big Data Applications

Blocked All-Pairs Shortest Paths Algorithm on Intel Xeon Phi KNL Processor: A Case Study

A Hybrid-parallel Architecture for Applications in Bioinformatics

STAR-RT: Visual attention for real-time video game playing

Qualcomm Snapdragon Mobile Platform OpenCL General Programming and Optimization

Implementing implicit OpenMP data sharing on GPUs

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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