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Improved Implementation of Simulation for Membrane Computing on the Graphic Processing Unit

Ali Maroosi, Ravie Chandren Muniyandi, Elankovan A. Sundararajan, Abdullah Mohd Zin

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Tags: Computer science, CUDA, Membrane computing, nVidia, nVidia GeForce GTX 480

February 5, 2014 by hgpu

Strategies for Maximizing Utilization in multi-CPU & multi-GPU Heterogeneous Architectures

Angeles Navarro, Antonio Vilches, Francisco Corbera, Rafael Asenjo

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla S2050

February 4, 2014 by hgpu

Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators

Wei Wang, Lifan Xu, John Cavazos, Howie H. Huang, Matthew Kay

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Source codes

Tags: Computer science, CUDA, Intel Xeon Phi, nVidia, OpenACC, OpenCL, Optimization, Package

February 4, 2014 by hgpu

Efficient Virtual Shadow Maps for Many Lights

Ola Olsson, Erik Sintorn, Viktor Kampe, Markus Billeter, Ulf Assarsson

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Tags: 3D Graphics and Realism, Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, OpenGL, Raytracing, Real-time graphics

February 2, 2014 by hgpu

Task migration of DSP application specified with a DFG and implemented with the BSP computing model on a CPU-GPU cluster

Farouk Mansouri, Sylvain Huet, Vincent Fristot, Dominique Houzet

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Tags: Computer science, CUDA, DSP, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia Quadro 4000, Signal processing

February 2, 2014 by hgpu

Optimized Deep Learning Architectures with Fast Matrix Operation Kernels on Parallel Platform

Ying Zhang, Saizheng Zhang

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Tags: Computer science, CUBLAS, CUDA, Machine learning, Neural networks, nVidia

February 2, 2014 by hgpu

Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs

Fabian Gieseke, Justin Heinermann, Cosmin Oancea, Christian Igel

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Tags: Computer science, KD-tree, Nearest neighbour, nVidia, nVidia GeForce GTX 770, OpenCL

February 1, 2014 by hgpu

Speeding Up Object Detection: Fast Resizing in the Integral Image Domain

Michael Gschwandtner, Andreas Uhl, Andreas Unterweger

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8500 GT

February 1, 2014 by hgpu

Survey on Efficient Linear Solvers for Porous Media Flow Models on Recent Hardware Architectures

Ani Anciaux-Sedrakian, Peter Gottschling, Jean-Marc Gratien, Thomas Guignon

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Review, Tesla M2070, Tesla M2090

February 1, 2014 by hgpu

Taking advantage of hybrid systems for sparse direct solvers via task-based runtimes

Xavier Lacoste, Mathieu Faverge, Pierre Ramet, Samuel Thibault, George Bosilca

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, nVidia, Sparse direct solvers, Tesla M2070

January 30, 2014 by hgpu

A Novel Graphical Processing Unit Method for Power Systems Security Analysis

Laurie Elizabeth Miller

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 470, Security, Sparse matrix, Thesis

January 30, 2014 by hgpu

Comparing the Performance of Different x86 SIMD Instruction Sets for a Medical Imaging Application on Modern Multi- and Manycore Chips

Johannes Hofmann, Jan Treibig, Georg Hager, Gerhard Wellein

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Tags: Algorithms, Computed tomography, Computer science, CT, CUDA, Image reconstruction, Intel Xeon Phi, Medicine, nVidia, nVidia GeForce GTX 680, Performance

January 30, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Improved Implementation of Simulation for Membrane Computing on the Graphic Processing Unit

Strategies for Maximizing Utilization in multi-CPU & multi-GPU Heterogeneous Architectures

Fast Acceleration of 2D Wave Propagation Simulations Using Modern Computational Accelerators

Efficient Virtual Shadow Maps for Many Lights

Task migration of DSP application specified with a DFG and implemented with the BSP computing model on a CPU-GPU cluster

Optimized Deep Learning Architectures with Fast Matrix Operation Kernels on Parallel Platform

Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs

Speeding Up Object Detection: Fast Resizing in the Integral Image Domain

Survey on Efficient Linear Solvers for Porous Media Flow Models on Recent Hardware Architectures

Taking advantage of hybrid systems for sparse direct solvers via task-based runtimes

A Novel Graphical Processing Unit Method for Power Systems Security Analysis

Comparing the Performance of Different x86 SIMD Instruction Sets for a Medical Imaging Application on Modern Multi- and Manycore Chips

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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