high performance computing on graphics processing units: hgpu.org

R. Ammendola, A. Biagioni, L. Deri, M. Fiorini, O. Frezza, G. Lamanna, F. Lo Cicero, A. Lonardo, A. Messina, M. Sozzi, F. Pantaleo, P.S. Paolucci, D. Rossetti, F. Simula, L. Tosoratto, P. Vicini

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Tags: CUDA, Data acquisition, High Energy Physics - Experiment, nVidia, nVidia GeForce GTX 680, Physics, Tesla C1060, Tesla C2050

January 14, 2014 by hgpu

A Framework for Productive, Efficient and Portable Parallel Computing

Ekaterina I. Gonina

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Tags: Algorithms, Code generation, Computer science, CUDA, MapReduce, nVidia, nVidia GeForce GTX 480, Package, Python, Thesis

January 12, 2014 by hgpu

A tool for mapping Single Nucleotide Polymorphisms using Graphics Processing Units

Andrea Manconi, Alessandro Orro, Emanuele Manca, Giuliano Armano, Luciano Milanesi

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 480, Package, Smith-Waterman algorithm, Tesla K20

January 12, 2014 by hgpu

Warp-Level Divergence in GPUs: Characterization, Impact, and Mitigation

Ping Xiang, Yi Yang, Huiyang Zhou

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance

January 12, 2014 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

GPU Accelerated Vessel Segmentation Using Laplacian Eigenmaps

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GPUs for real-time processing in HEP trigger systems

A Framework for Productive, Efficient and Portable Parallel Computing

A tool for mapping Single Nucleotide Polymorphisms using Graphics Processing Units

Warp-Level Divergence in GPUs: Characterization, Impact, and Mitigation

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