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Full-Parallax Hologram Synthesis of Triangular Meshes using a Graphical Processing Unit

Ivo Hanak, Martin Janda, Vaclav Skala

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Tags: Computer holography, Computer science, DirectX, nVidia, nVidia GeForce FX 6800, Rendering

July 16, 2011 by hgpu

Spring-Bead Animation of Viscoelastic Materials

Nobuhiko Tamura, Norimichi Tsumura, Toshiya Nakaguchi, Yoichi Miyake

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Tags: Computer science, DirectX, nVidia, nVidia GeForce FX 6800, Particle simulation, Viscoelasticity, Visualization

June 28, 2011 by hgpu

Direct evaluation of NURBS curves and surfaces on the GPU

Adarsh Krishnamurthy, Rahul Khardekar, Sara Mcmains

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Tags: 3D Graphics and Realism, ATI, ATI Radeon X1900, Computer science, nVidia, nVidia GeForce FX 6800, nVidia Quadro FX 3000, nVidia Quadro FX 4500, OpenGL

March 16, 2011 by hgpu

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

Engineering Supercomputing Platforms for Biomolecular Applications

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations

microSYCL: SYCL micro-benchmarks repository

Exploring SYCL as a Portability Layer for High-Performance Computing on CPUs

XaaS containers

Acceleration as a Service (XaaS) Source Containers

CASS: Cuda-Amd aSSembly

CASS: Nvidia to AMD Transpilation with Data, Models, and Benchmark

Cluser of smartphones for edge computing application using TensorFlow

Low-cost edge computing using upcycled smartphones

SYCL Container

Exploring SYCL for batched kernels with memory allocations

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

Can Large Language Models Predict Parallel Code Performance?

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