high performance computing on graphics processing units: hgpu.org

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Parallel Explicit FEM Algorithms Using GPU’s

Seyed Parsa Banihashemi

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Tags: Algorithms, AMD Radeon R9 280X, ATI, ATI Radeon HD 7970, Computer science, FEM, Finite element method, nVidia, nVidia GeForce GTX Titan, OpenCL, Particle swarm optimization, Performance, Tesla M2090, Thesis

January 22, 2016 by hgpu

Basker: A Threaded Sparse LU Factorization Utilizing Hierarchical Parallelism and Data Layouts

Joshua Dennis Booth, Sivasankaran Rajamanickam, Heidi K. Thornquist

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Tags: Algorithms, Computer science, Factorization, Intel Xeon Phi, Sparse direct solvers, Sparse matrix

January 22, 2016 by hgpu

GPU Multisplit

Saman Ashkiani, Andrew Davidson, Ulrich Meyer, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 750 Ti, Tesla K40

January 22, 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

Exploring LLVM Infrastructure for Simplified Multi-GPU Programming

Alexander Matz, Mark Hummel, Holger Froning

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Tags: Computer science, CUDA, LLVM, nVidia, OpenCL, Tesla K80

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

Homomorphic Autocomplete

Gizem S. Cetin, Wei Dai, Yarkin Doroz, Berk Sunar

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 690, Security

January 16, 2016 by hgpu

Performance Analysis of Roberts Edge Detection Using CUDA and OpenGL

Marco Cali, Valeria Di Mauro

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Tags: CUDA, Edge detection, Image processing, nVidia, nVidia GeForce GTX 845 M, OpenGL, Performance

January 16, 2016 by hgpu

LHCb GPU acceleration project

A. Badalov, D. Campora, N. Neufeld, X. Vilasis-Cardona

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Tags: CUDA, High Energy Physics - Experiment, nVidia, nVidia GeForce GTX 680, Physics

January 16, 2016 by hgpu

Contributions of hybrid architectures to depth imaging: a CPU, APU and GPU comparative study

Issam Said

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Tags: APU, Computer science, Geophysics, Geoscience, GPU cluster, MPI, nVidia, OpenCL, Tesla K40, Thesis

January 16, 2016 by hgpu

A Case for Work-stealing on FPGAs with OpenCL Atomics

Nadesh Ramanathan, John Wickerson, Felix Winterstein, George A. Constantinides

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Tags: Algorithms, Clustering, Computer science, FPGA, OpenCL

January 14, 2016 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Parallel Explicit FEM Algorithms Using GPU’s

Basker: A Threaded Sparse LU Factorization Utilizing Hierarchical Parallelism and Data Layouts

GPU Multisplit

Heterogeneous (CPU+GPU) Working-set Hash Tables

Exploring LLVM Infrastructure for Simplified Multi-GPU Programming

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

Homomorphic Autocomplete

Performance Analysis of Roberts Edge Detection Using CUDA and OpenGL

LHCb GPU acceleration project

Contributions of hybrid architectures to depth imaging: a CPU, APU and GPU comparative study

A Case for Work-stealing on FPGAs with OpenCL Atomics

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

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

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