paper | Page 318 | hgpu.org

Jayanth Chennamangalam, Simon Scott, Glenn Jones, Hong Chen, John Ford, Amanda Kepley, D. R. Lorimer, Jun Nie, Richard Prestage, D. Anish Roshi, Mark Wagner, Dan Werthimer

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Tags: Astrophysics, CUDA, FFT, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX Titan, Package, Signal processing

November 5, 2014 by hgpu

Profiling of Data-Parallel Processors

Daniel Kruck, Holger Froening

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Tags: Computer science, CUDA, nVidia, Performance, Tesla K20

November 3, 2014 by hgpu

A Fast Poisson Solver with Periodic Boundary Conditions for GPU Clusters in Various Configurations

Dale Nicholas Rattermann

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Tags: CUDA, FFT, Fluid dynamics, GPU cluster, Laplace and Poisson equation, nVidia, Poisson equation, Tesla M2050, Tesla M2070, Thesis

November 3, 2014 by hgpu

Bounds on the Energy Consumption of Computational Kernels

Andrew Gearhart

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Tags: Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, Package, Tesla K20, Thesis

November 3, 2014 by hgpu

A GPU-based Framework for Real-time Free Viewpoint Television

Kyrylo Shegeda

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Tags: Computer science, CUDA, GLSL, nVidia, nVidia Quadro FX 1700, nVidia Quadro FX 5800, Rendering, Thesis

November 3, 2014 by hgpu

Performance Optimization Using Partitioned SpMV on GPUs and Multicore CPUs

Wangdong Yang, Kenli Li, Zeyao Mo, Keqin Li

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 460, Performance, Probability, Sparse matrix

November 3, 2014 by hgpu

Compoundly weighted Voronoi: a sequential and parallel implementation

Vincent Boerjan

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Tags: Algorithms, Computer science, nVidia, nVidia Quadro NVS 5200 M, OpenCL, OpenGL, Tessellation, Thesis, Voronoi diagram

October 31, 2014 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

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kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

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