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Parallel Implementation of the Finite Element Method on Graphics Processors for the Solution of Incompressible Flows

Mahmut Murat Gocmen

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Tags: Algorithms, CUBLAS, CUDA, FEM, Finite element method, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 280, Package, Tesla C2075, Thesis

January 16, 2015 by hgpu

A Novel Computational Model for GPUs with Applications to Efficient Algorithms

Atsushi Koike, Kunihiko Sadakane

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Tags: Algorithms, Computer science, CUDA, nVidia, Sorting, Tesla C1060, Tesla K20

January 15, 2015 by hgpu

Identification and Elimination of Platform-Specific Code Smells in High Performance Computing Applications

Chunyan Wang, Shoichi Hirasawa, Hiroyuki Takizawa, Hiroaki Kobayashi

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Tags: Computer science, CUDA, nVidia, OpenACC, OpenCL, Tesla C1060, Tesla C2070, Tesla K20

January 15, 2015 by hgpu

Reducing overheads of dynamic scheduling on heterogeneous chips

Francisco Corbera, Andres Rodriguez, Rafael Asenjo, Angeles Navarro, Antonio Vilches, Maria J. Garzaran

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Tags: Computer science, Heterogeneous systems, OpenCL, Operating systems

January 15, 2015 by hgpu

Batched Matrix Computations on Hardware Accelerators Based on GPUs

Azzam Haidar, Tingxing Dong, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, nVidia, Tesla K40

January 15, 2015 by hgpu

High Performance GPU-based Fourier Volume Rendering

Marwan Abdellah, Ayman Eldeib, Amr Sharawi

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 640, nVidia Quadro K5000, OpenGL, Rendering, Visualization

January 15, 2015 by hgpu

Linear Performance-Breakdown Model: A Framework for GPU kernel programs performance analysis

Chapa Martell Mario Alberto, Hiroyuki Sato

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Tags: Computer science, nVidia, nVidia GeForce GTX 660, OpenCL, Performance

January 13, 2015 by hgpu

Development of an Algorithm for Extracting Parallelism and Pipeline Structure from Stream-based Processing flow with Spanning Tree

Shinichi Yamagiwa, Guyue Wang, Koichi Wada

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Tags: Computer science, CUDA, nVidia, OpenCL, Tesla C2050

January 13, 2015 by hgpu

Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors

Ming Zeng, Le T. Nguyen, Bo Yu, Ole J. Mengshoel, Jiang Zhu, Pang Wu, Joy Zhang

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Tags: CNN, CUDA, Image recognition, Neural networks, nVidia, Sensing, Speech recognition, Tesla K20

January 13, 2015 by hgpu

A Time Optimal Parallel Algorithm for the Dynamic Programming on the Hierarchical Memory Machine

Koji Nakano

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 680

January 13, 2015 by hgpu

Thorough Evaluation of GPU Shared Memory Load and Store Instructions

Satoshi Okamoto, Yasuaki Ito, Koji Nakano, Jacir L. Bordim

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 780 Ti, Performance, PTX

January 13, 2015 by hgpu

A Survey Of Architectural Approaches for Managing Embedded DRAM and Non-volatile On-chip Caches

Sparsh Mittal; Jeffrey S. Vetter; Dong Li

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Tags: cache, Compiler, cpu, Energy-efficient computing, GPU, Hardware Architecture, Memory model

January 12, 2015 by sparsh0mittal

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

Applications

Parallel Implementation of the Finite Element Method on Graphics Processors for the Solution of Incompressible Flows

A Novel Computational Model for GPUs with Applications to Efficient Algorithms

Identification and Elimination of Platform-Specific Code Smells in High Performance Computing Applications

Reducing overheads of dynamic scheduling on heterogeneous chips

Batched Matrix Computations on Hardware Accelerators Based on GPUs

High Performance GPU-based Fourier Volume Rendering

Linear Performance-Breakdown Model: A Framework for GPU kernel programs performance analysis

Development of an Algorithm for Extracting Parallelism and Pipeline Structure from Stream-based Processing flow with Spanning Tree

Convolutional Neural Networks for Human Activity Recognition using Mobile Sensors

A Time Optimal Parallel Algorithm for the Dynamic Programming on the Hierarchical Memory Machine

Thorough Evaluation of GPU Shared Memory Load and Store Instructions

A Survey Of Architectural Approaches for Managing Embedded DRAM and Non-volatile On-chip Caches

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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