high performance computing on graphics processing units: hgpu.org

hgpu.org » Heterogeneous systems

Efficient shallow water simulations on GPUs: Implementation, visualization, verification, and validation

Andre R. Brodtkorb, Martin L. Saetra, Mustafa Altinakar

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Visualization

December 22, 2011 by hgpu

A simulation suite for lattice Boltzmann based real time CFD applications exploiting multi-level parallelism on modern multi-and many-core architectures

Markus Geveler, Dirk Ribbrock, Sven Mallach, Dominik Goddeke

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Tags: CUDA, Fluid dynamics, Heterogeneous systems, Lattice Boltzmann model, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 285

December 21, 2011 by hgpu

Towards Automatic C Programs Optimization and Parallelization using the PIPS-PoCC Integration

Dounia Khaldi, Corinne Ancourt, Francois Irigoin

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Tags: Benchmarking, Code generation, Computer science, CUDA, FPGA, Heterogeneous systems, MPI, nVidia, OpenMP, Optimization, Package

December 19, 2011 by hgpu

Leveraging Parallelism with CUDA and OpenCL

S. Park, D. Shires, J. Ross, D. Richie

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Tags: AMD FireStream 9250, ATI, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Programming techniques, Tesla C1060

December 18, 2011 by hgpu

Quartile and Outlier Detection on Heterogeneous Clusters Using Distributed Radix Sort

Kyle L. Spafford, Jeremy S. Meredith, Jeffrey S. Vetter

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Sorting, Tesla M2070

December 17, 2011 by hgpu

Toward Accelerating the Matrix Inversion Computation of Symmetric Positive-Definite Matrices on Heterogeneous GPU-Based Systems

Huda Ibeid, Dinesh Kaushik, David Keyes, Hatem Ltaief

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, Matrix inversion, nVidia, Tesla C2070

December 14, 2011 by hgpu

GPU Programming in a High Level Language: Compiling X10 to CUDA

Dave Cunningham, Rajesh Bordawekar, Vijay Saraswat

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, High-level Languages, nVidia, nVidia Quadro FX 3700 M, OpenCL, Tesla C1060, Tesla S1070

December 12, 2011 by hgpu

A design tool for efficient mapping of multimedia applications onto heterogeneous platforms

Chung-Ching Shen, Hsiang-Huang Wu, Nimish Sane, William Plishker, Shuvra S. Bhattacharyya

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Tags: Computer science, CUDA, Flow analysis, Heterogeneous systems, nVidia, nVidia GeForce GTX 260

December 9, 2011 by hgpu

GPU implementations of scheduling heuristics for heterogeneous computing environments

Sergio Nesmachnow, Mauro Canabe

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Task scheduling, Tesla C1060

December 9, 2011 by hgpu

Objective-Driven Workload Allocation in Heterogeneous Computing Systems

Qiang Liu, Wayne Luk

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, Performance, Tesla C2070

December 9, 2011 by hgpu

Exploring the Optimization Space of Multi-Core Architectures with OpenCL Benchmarks

Deepak Mathews Panickal

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Tags: ATI, ATI Radeon HD 5470, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Optimization, Tesla C2070, Thesis

December 9, 2011 by hgpu

A dynamic scheduling runtime and tuning system for heterogeneous multi and many-core desktop platforms

Alecio Pedro Delazari Binotto

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 285, OpenCL, Task scheduling, Thesis

December 5, 2011 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

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high performance computing on graphics processing units: hgpu.org

Efficient shallow water simulations on GPUs: Implementation, visualization, verification, and validation

A simulation suite for lattice Boltzmann based real time CFD applications exploiting multi-level parallelism on modern multi-and many-core architectures

Towards Automatic C Programs Optimization and Parallelization using the PIPS-PoCC Integration

Leveraging Parallelism with CUDA and OpenCL

Quartile and Outlier Detection on Heterogeneous Clusters Using Distributed Radix Sort

Toward Accelerating the Matrix Inversion Computation of Symmetric Positive-Definite Matrices on Heterogeneous GPU-Based Systems

GPU Programming in a High Level Language: Compiling X10 to CUDA

A design tool for efficient mapping of multimedia applications onto heterogeneous platforms

GPU implementations of scheduling heuristics for heterogeneous computing environments

Objective-Driven Workload Allocation in Heterogeneous Computing Systems

Exploring the Optimization Space of Multi-Core Architectures with OpenCL Benchmarks

A dynamic scheduling runtime and tuning system for heterogeneous multi and many-core desktop platforms

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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