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Efficient computational noise in GLSL

Ian McEwan, David Sheets, Stefan Gustavson, Mark Richardson

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Tags: 3D Graphics and Realism, ATI, ATI Radeon HD 3650, ATI Radeon HD 4850, ATI Radeon HD 5870, Computer science, GLSL, nVidia, nVidia GeForce 7600 GS, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenGL, Package

April 9, 2012 by hgpu

Real-time Flame Rendering with GPU and CUDA

Wei Wei,Yanqiong Huang

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Tags: 3D Graphics and Realism, Computer science, CUDA, Fluid dynamics, nVidia, nVidia GeForce 7600 GS, OpenGL, Particle simulation, Rendering

November 5, 2011 by hgpu

High-performance GPU based Rendering for Real-Time, rigid 2D/3D-Image Registration in Radiation Oncology

Jakob Spork

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Tags: Cg, Image registration, Medicine, nVidia, nVidia GeForce 7600 GS, nVidia Quadro FX 570 M, OpenGL, Review, Thesis

March 5, 2011 by hgpu

GPU-based rendering for deformable translucent objects

Yi Gong, Wei Chen, Long Zhang, Yun Zeng, Qunsheng Peng

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce 7600 GS, OpenGL, Real-time graphics, Rendering

December 11, 2010 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

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

Can Large Language Models Predict Parallel Code Performance?

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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high performance computing on graphics processing units: hgpu.org

Efficient computational noise in GLSL

Real-time Flame Rendering with GPU and CUDA

High-performance GPU based Rendering for Real-Time, rigid 2D/3D-Image Registration in Radiation Oncology

GPU-based rendering for deformable translucent objects

Recent source codes

CFAL-bench

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

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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