high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

A Domain-Specific Approach To Heterogeneous Parallelism

Hassan Chafi, Arvind K. Sujeeth, Kevin J. Brown, HyoukJoong Lee, Anand R. Atreya, Kunle Olukotun

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, High-level Languages, nVidia, nVidia GeForce GTX 275

February 27, 2011 by hgpu

StarPU: a Runtime System for Scheduling Tasks over Accelerator-Based Multicore Machines

Cedric Augonnet, Samuel Thibault, Raymond Namyst

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Tags: Computer science, CUDA, Distributed computing, nVidia, nVidia Quadro FX 4600, nVidia Quadro FX 5800, Package, Performance

February 26, 2011 by hgpu

A Tuning Framework for Software-Managed Memory Hierarchies

Manman Ren, Ji Young Park, Mike Houston, Alex Aiken, William J. Dally

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Tags: Algorithms, Cell processor, Compilers, Computer science, Optimization, Performance, Playstation, Programming Languages

February 26, 2011 by hgpu

Believe it or Not! Multi-core CPUs Can Match GPU Performance for FLOP-intensive Application!

Rajesh Bordawekar, Uday Bondhugula, Ravi Rao

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Performance, Programming techniques

February 26, 2011 by hgpu

Real-Time Approaches to Computer Vision

Ron Tal

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Tags: Algorithms, Computer science, Computer vision, CUDA, FPGA, nVidia

February 26, 2011 by hgpu

Concurrent GPU Programming

Lesley Northam

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 M GTX, Programming techniques, Review

February 26, 2011 by hgpu

A Watermarking Co-Processor for New Generation Graphics Processing Units

Saraju P. Mohanty, Nishikanta Pati, Elias Kougianos

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Tags: Algorithms, Image processing, Security

February 26, 2011 by hgpu

Handbook of open source tools

Sandeep Koranne

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Tags: Book, Cluster computing, Computer science, CUDA, MPI, nVidia, OpenCL, Pthreads

February 26, 2011 by hgpu

Real-time blood flow visualization using the graphics processing unit

Owen Yang, David Cuccia, Bernard Choi

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Tags: CUDA, Image processing, Medicine, nVidia, nVidia GeForce 8800 GTS, Optics, Package

February 26, 2011 by hgpu

Porous Rock Simulations and Lattice Boltzmann on GPUs

Eirik O. Aksnes, and Anne C. Elster

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia Quadro FX 5800

February 25, 2011 by hgpu

Towards real time 2D to 3D registration for ultrasound-guided endoscopic and laparoscopic procedures

Raul San Jose Estepar, Carl-Fredrik Westin and Kirby G. Vosburgh

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Tags: Algorithms, Computed tomography, CT, CUDA, Image registration, Medicine, nVidia, Ultrasound

February 25, 2011 by hgpu

HexServer: an FFT-based protein docking server powered by graphics processors

Gary Macindoe, Lazaros Mavridis, Vishwesh Venkatraman, Marie-Dominique Devignes, David W. Ritchie

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Tags: Bioinformatics, Biology, CUDA, FFT, Molecular simulation, nVidia, Tesla C1060

February 25, 2011 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

A Domain-Specific Approach To Heterogeneous Parallelism

StarPU: a Runtime System for Scheduling Tasks over Accelerator-Based Multicore Machines

A Tuning Framework for Software-Managed Memory Hierarchies

Believe it or Not! Multi-core CPUs Can Match GPU Performance for FLOP-intensive Application!

Real-Time Approaches to Computer Vision

Concurrent GPU Programming

A Watermarking Co-Processor for New Generation Graphics Processing Units

Handbook of open source tools

Real-time blood flow visualization using the graphics processing unit

Porous Rock Simulations and Lattice Boltzmann on GPUs

Towards real time 2D to 3D registration for ultrasound-guided endoscopic and laparoscopic procedures

HexServer: an FFT-based protein docking server powered by graphics processors

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Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

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