high performance computing on graphics processing units: hgpu.org

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Performance comparison of FPGA, GPU and CPU in image processing

Shuichi Asano, Tsutomu Maruyama, Yoshiki Yamaguchi

Tags: Filtering, FPGA, Image processing, Performance

March 21, 2011 by hgpu

A comparison of CPUs, GPUs, FPGAs, and massively parallel processor arrays for random number generation

David Barrie Thomas, Lee Howes, Wayne Luk

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Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 280, Pseudo-random number generators

March 20, 2011 by hgpu

Mersenne Twister Random Number Generation on FPGA, CPU and GPU

Xiang Tian, Khaled Benkrid

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Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, nVidia GeForce 8800 GTX, Pseudo-random number generators

March 20, 2011 by hgpu

FPGA vs. GPU for sparse matrix vector multiply

Yan Zhang, Yasser H. Shalabi, Rishabh Jain, Krishna K. Nagar, Jason D. Bakos

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Tags: Computer science, CUDA, FPGA, Linear Algebra, nVidia, nVidia GeForce GTX 260, Sparse matrix

March 18, 2011 by hgpu

Rotationally invariant sparse patch matching on GPU and FPGA

Zachary K Baker, Reid Porter

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Tags: FPGA, Image processing, Nearest neighbour, nVidia, nVidia GeForce 7900 GTX, OpenGL

March 16, 2011 by hgpu

Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs and GPUs

Kanupriya Gulati and Sunil P. Khatri

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Tags: Book, CAD, Computer science, CUDA, Electronic design automation, FPGA, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 280, nVidia Quadro FX 5800, Review

March 14, 2011 by hgpu

Comparison of FPGA and GPU implementations of real-time stereo vision

R. Kalarot, J. Morris

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Tags: Computer science, Computer vision, CUDA, FPGA, nVidia, nVidia GeForce GTX 280

March 9, 2011 by hgpu

Application-guided tool development for architecturally diverse computation

Roger D. Chamberlain, Jeremy Buhler, Mark A. Franklin, James H. Buckley

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Tags: Algorithms, Astrophysics, Biology, Computer science, CUDA, Finance, FPGA, Heterogeneous systems, Monte Carlo simulation, nVidia, nVidia GeForce GTX 260, Search, Security

March 7, 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

Accelerating Quantum Monte Carlo Simulations with Emerging Architectures

Akila Gothandaraman

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Tags: Computer science, CUDA, FPGA, nVidia, QMC, Tesla C1060, Tesla C870, Thesis

February 24, 2011 by hgpu

Architectural Comparisons for a Quantum Monte Carlo Application

Akila Gothandaraman, Rick Weber, Gregory D. Peterson, Robert J. Hinde, Robert J. Harrison

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Tags: AMD FireStream 9170, ATI, Brook, Computer science, CUDA, FPGA, Monte Carlo simulation, nVidia, QMC, Tesla C1060

February 23, 2011 by hgpu

Production Floating Point Applications on FPGAs

Martin C. Herbordt, Bharat Sukhwani, Matt Chiu, Md. Ashfaq Khan

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Tags: Chemistry, Computer science, CUDA, FPGA, Molecular dynamics, Molecular modeling, nVidia, Tesla C1060

February 22, 2011 by hgpu

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

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high performance computing on graphics processing units: hgpu.org

Performance comparison of FPGA, GPU and CPU in image processing

A comparison of CPUs, GPUs, FPGAs, and massively parallel processor arrays for random number generation

Mersenne Twister Random Number Generation on FPGA, CPU and GPU

FPGA vs. GPU for sparse matrix vector multiply

Rotationally invariant sparse patch matching on GPU and FPGA

Hardware Acceleration of EDA Algorithms: Custom ICs, FPGAs and GPUs

Comparison of FPGA and GPU implementations of real-time stereo vision

Application-guided tool development for architecturally diverse computation

Real-Time Approaches to Computer Vision

Accelerating Quantum Monte Carlo Simulations with Emerging Architectures

Architectural Comparisons for a Quantum Monte Carlo Application

Production Floating Point Applications on FPGAs

Recent source codes

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

LC Framework

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