high performance computing on graphics processing units: hgpu.org

hgpu.org » Video decoding

Frame-based parallelization of MPEG-4 on compute unified device architecture (CUDA)

Dishant Ailawadi, Milan Kumar Mohapatra, Ankush Mittal

View

Tags: CUDA, Image processing, nVidia, nVidia Quadro FX 370, Video decoding

March 8, 2011 by hgpu

Fast implementation of Wyner-Ziv Video codec using GPGPU

Ryanggeun Oh, Jongbin Park, Byeungwoo Jeon

Tags: CUDA, nVidia, Signal processing, Video decoding

March 7, 2011 by hgpu

Software parallel CAVLC encoder based on stream processing

Ju Ren, Yi He, Wei Wu, Mei Wen, Nan Wu, Chunyuan Zhang

View

Tags: Computer science, H.264/AVC, nVidia, nVidia GeForce 8800 GTX, Video decoding

February 2, 2011 by hgpu

Accelerating video decoding using GPU

Guobin Shen,Lihua Zhu,Shipeng Li,Heung-Yeung Shum,Ya-Qin Zhang

Tags: Computer science, nVidia, Video decoding

October 27, 2010 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

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?

PELSI: Power-Efficient Layer-Switched Inference

Efficient deep learning inference on end devices

Ouroboros: Virtualized Queues for dynamic memory management

Dynamic Memory Management on GPUs with SYCL

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

MSCCL++: Rethinking GPU Communication Abstractions for Cutting-edge AI Applications

Benchmark compute shader of Unity against InteropUnityCUDA

InteropUnityCUDA: A Tool for Interoperability Between Unity and CUDA

Data-efficient LLM Fine-tuning for Code Generation

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

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

See all packages

* * *

* * *

HGPU group © 2010-2025 hgpu.org

All rights belong to the respective authors

Login | Sitemap | Feedback | Policy

Contact us: