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Implementation of a High Throughput 3GPP Turbo Decoder on GPU

Michael Wu, Yang Sun, Guohui Wang, Joseph R. Cavallaro

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Tags: CUDA, Error recovery, nVidia, nVidia GeForce GTX 470, Signal processing

October 7, 2011 by hgpu

Divergence Analysis and Optimizations

Bruno Coutinho, Diogo Sampaio, Fernando Magno Quintao Pereira, Wagner Meira Jr.

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Optimization, Package, PTX

October 6, 2011 by hgpu

CUDA performance analyzer

Aniruddha Dasgupta

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Tags: Analytical model, Computer science, CUDA, Fast multipole method, nVidia, Optimization, Performance, Tesla C1060, Thesis

October 6, 2011 by hgpu

Offloading Java to Graphics Processors

Peter Calvert

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Tags: Algorithms, Benchmarking, Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce GTX 260

October 6, 2011 by hgpu

Parallelisation of Java for Graphics Processors

Peter Calvert

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Tags: Algorithms, Benchmarking, Code generation, Computer science, CUDA, Java, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 260, Package, Thesis

October 6, 2011 by hgpu

Multi-core programming with OpenCL: performance and portability: OpenCL in a memory bound scenario

Olav Aanes Fagerlund

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GTX 280, OpenCL, Thesis

October 6, 2011 by hgpu

Python for Development of OpenMP and CUDA Kernels for Multidimensional Data

Zane W. Bell, Greg G. Davidson, Ed D'Azevedo, Thomas M. Evans, Wayne Joubert, John K. Munro, Jr., Dilip R. Patlolla, Bogdan Vacaliuc

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Tags: Boltzmann equation, CUDA, Heterogeneous systems, nVidia, Package, Physics, Presentation, Python, Tesla M2070

October 6, 2011 by hgpu

Static GPU threads and an improved scan algorithm

Jens Breitbart

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 280, OpenCL, Performance, Presentation, Programming techniques

October 6, 2011 by hgpu

GPU-based single-cluster algorithm for the simulation of the Ising model

Yukihiro Komura, Yutaka Okabe

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Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 285, Physics

October 6, 2011 by hgpu

Connected-component identification and cluster update on graphics processing units

Martin Weigel

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Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Physics, Tesla M2070

October 6, 2011 by hgpu

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Andrew Nere, Atif Hashmi, Mikko Lipasti

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Image recognition, Neural networks, nVidia, nVidia GeForce 9800 GX2, nVidia GeForce GTX 280, Optimization, Tesla C2050

October 5, 2011 by hgpu

Democratic Population Decisions Result in Robust Policy-Gradient Learning: A Parametric Study with GPU Simulations

Paul Richmond, Lars Buesing, Michele Giugliano, Eleni Vasilaki

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Tags: Biology, CUDA, Neuroscience, nVidia, nVidia GeForce GTX 480, Package, Python

October 5, 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

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high performance computing on graphics processing units: hgpu.org

Implementation of a High Throughput 3GPP Turbo Decoder on GPU

Divergence Analysis and Optimizations

CUDA performance analyzer

Offloading Java to Graphics Processors

Parallelisation of Java for Graphics Processors

Multi-core programming with OpenCL: performance and portability: OpenCL in a memory bound scenario

Python for Development of OpenMP and CUDA Kernels for Multidimensional Data

Static GPU threads and an improved scan algorithm

GPU-based single-cluster algorithm for the simulation of the Ising model

Connected-component identification and cluster update on graphics processing units

Profiling Heterogeneous Multi-GPU Systems to Accelerate Cortically Inspired Learning Algorithms

Democratic Population Decisions Result in Robust Policy-Gradient Learning: A Parametric Study with GPU Simulations

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