high performance computing on graphics processing units: hgpu.org

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Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, Alan L. Yuille

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Tags: Algorithms, CNN, Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce GTX Titan

December 26, 2014 by hgpu

Computationally Efficient Implementation of a Hamming Code Decoder using a Graphics Processing Unit

Shohidul Islam, Cheol-Hong Kim, Jong-Myon Kim

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, Signal processing

December 26, 2014 by hgpu

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Nicolas Vasilache, Jeff Johnson, Michael Mathieu, Soumith Chintala, Serkan Piantino, Yann LeCun

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Tags: Algorithms, CNN, Computer science, CUDA, FFT, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia, Package, Tesla K40

December 26, 2014 by hgpu

Legion: Programming Distributed Heterogeneous Architectures with Logical Regions

Michael Edward Bauer

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Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, Package, Tesla K20, Tesla M2090, Thesis

December 22, 2014 by hgpu

Purine: A bi-graph based deep learning framework

Min Lin, Shuo Li, Xuan Luo, Shuicheng Yan

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Tags: Computer science, CUDA, Machine learning, Neural and Evolutionary Computing, nVidia

December 22, 2014 by hgpu

Manycore processing of repeated k-NN queries over massive moving objects observations

Francesco Lettich, Salvatore Orlando, Claudio Silvestri

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Tags: Computer science, CUDA, Data Structures and Algorithms, Databases, Nearest neighbour, nVidia, nVidia GeForce GTX 580

December 22, 2014 by hgpu

GPU Pro 5: Advanced Rendering Techniques

Wolfgang Engel

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Tags: 3D Graphics and Realism, ATI, Computer science, nVidia, OpenCL, OpenGL, Rasterization, Raytracing, Rendering

December 22, 2014 by hgpu

GPGPU-Sim

Filip Andersson

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Tesla C2050, Thesis

December 22, 2014 by hgpu

GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian

Sankha Baran Dutta

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Tags: Ant colony optimization, Computational Complexity, Computer science, CUDA, nVidia, nVidia GeForce GTX 560 Ti, Thesis, Vehicular traffic

December 22, 2014 by hgpu

Fast Solving of Influence Diagrams for Multiagent Planning on GPU-enabled Architectures

Fadel Adoe, Yingke Chen, Prashant Doshi

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Tags: Algorithms, Bayesian, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Package

December 22, 2014 by hgpu

Efficient Workload Balancing on Heterogeneous GPUs using Mixed-Integer Non-Linear Programming

Chih-Sheng Lin, Chih-Wei Hsieh, Hsi-Ya Chang, Pao-Ann Hsiung

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTS 250, nVidia GeForce GTX 690, Tesla C2050, Tesla K20

December 20, 2014 by hgpu

A Review on Parallelization of Node based Game Tree Search Algorithms on GPU

Rutuja U. Gosavi, Payal S. Kulkarni

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, nVidia

December 20, 2014 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

Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFs

Computationally Efficient Implementation of a Hamming Code Decoder using a Graphics Processing Unit

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

Legion: Programming Distributed Heterogeneous Architectures with Logical Regions

Purine: A bi-graph based deep learning framework

Manycore processing of repeated k-NN queries over massive moving objects observations

GPU Pro 5: Advanced Rendering Techniques

GPGPU-Sim

GPU Accelerated Nature Inspired Methods for Modelling Large Scale Bi-Directional Pedestrian

Fast Solving of Influence Diagrams for Multiagent Planning on GPU-enabled Architectures

Efficient Workload Balancing on Heterogeneous GPUs using Mixed-Integer Non-Linear Programming

A Review on Parallelization of Node based Game Tree Search Algorithms on GPU

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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