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hgpu.org » Applications » Image and Signal Processing

CPU and/or GPU: Revisiting the GPU Vs. CPU Myth

Kishore Kothapalli, Dip Sankar Banerjee, P. J. Narayanan, Surinder Sood, Aman Kumar Bahl, Shashank Sharma, Shrenik Lad, Krishna Kumar Singh, Kiran Matam, Sivaramakrishna Bharadwaj, Rohit Nigam, Parikshit Sakurikar, Aditya Deshpande, Ishan Misra, Siddharth Choudhary, Shubham Gupta

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Tags: Computer science, Databases, Hybrid computing, Image processing, nVidia, nVidia GeForce GT 520, Sparse matrix, Tesla T10

March 14, 2013 by hgpu

Signal Processing and General Purpose Computing on GPU

Muge Guher

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Tags: CUDA, nVidia, Signal processing, Tesla C2050

March 9, 2013 by hgpu

Efficient Detection of Sunspots with GPU Acceleration Through CUDA

Kenny May

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Tags: Astrophysics, CUDA, Image processing, nVidia, nVidia GeForce GT 430, nVidia GeForce GTX 470, Tesla C2050

March 2, 2013 by hgpu

Full Covariance Gaussian Mixture Models Evaluation on GPU

Jan Vanek, Jan Trmal, Josef V. Psutka, Josef Psutka

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Tags: Algorithms, ATI, ATI Mobility Radeon HD 5470, ATI Radeon HD 5670, ATI Radeon HD 5870, CUDA, nVidia, nVidia GeForce GT 240, nVidia GeForce GTX 580, nVidia Quadro FX 770 M, OpenCL, Signal processing, Speech recognition

March 2, 2013 by hgpu

Multi-GPU based on multicriteria optimization for motion estimation system

Carlos Garcia, Guillermo Botella, Fermin Ayuso, Manuel Prieto, Francisco Tirado

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Tags: Algorithms, Computer vision, CUDA, Data parallelism, nVidia, Optical flow, Signal processing, Tesla C1060, Tesla M2070

February 27, 2013 by hgpu

Advanced Video Coding on CPUs and GPUs: Parallelization and RD Analysis

Svetislav Momcilovic, Aleksandar Ilic, Nuno Roma, Leonel Sousa

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Tags: Algorithms, Compression, CUDA, H.264/AVC, Image processing, nVidia, Signal processing, Video encoding

February 25, 2013 by hgpu

Investigating performance variations of an optimized GPU-ported granulometry algorithm

Vincent Boulos, Vincent Fristot, Dominique Houzet, Luc Salvo, Pierre Lhuissier

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Tags: Algorithm optimization, Algorithms, CUDA, FEM, Finite element method, Image processing, Materials Science, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia Quadro FX 4000

February 22, 2013 by hgpu

Using High Performance Computing to Improve Image Guided Cancer Treatment

Dante Gama Dessavre

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Tags: CUDA, Image processing, Medicine, nVidia, Radiotherapy, Tesla C2050, Thesis

February 18, 2013 by hgpu

MATLAB and Python for GPU Computing

Jose Unpingco, Juan Carlos Chaves

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Tags: Computer science, CUDA, Image processing, nVidia, nVidia GeForce 9800 GTS, nVidia GeForce 9800 GX2, Python, Signal processing, Tesla C1060, Tesla C2050

February 15, 2013 by hgpu

Efficient Exploitation of Heterogeneous Platforms for Images Features Extraction

Sidi Ahmed Mahmoudi, Pierre Manneback

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Tags: Algorithms, Computer science, Computer vision, CUDA, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 280, Pattern recognition, Tesla C1060

February 14, 2013 by hgpu

The Implement of Common Beam Forming Using GPU

Jing-hong Jiang, Qi-xiang Han, Hui-zhi Cai, Wei-min Hou

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Tags: CUDA, nVidia, nVidia GeForce GTX 285, Signal processing

February 12, 2013 by hgpu

A Networked Dataflow Simulation Environment for Signal Processing and Data Mining Applications

Stephen Won

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Tags: Computer vision, CUDA, Data mining, Heterogeneous systems, nVidia, nVidia GeForce GTX 260, SIFT, Signal processing, Thesis

February 12, 2013 by hgpu

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

Hardware-Aware FP4 FlashAttention-4

EinsummableV3 - graph-based computation with tensor operations support

Every Kernel Is a Join: Automatic Multi-GPU Parallelism for AI Computations in Einsummable

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