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An Optimized Parallel IDCT on Graphics Processing Units

Biao Wang, Mauricio Alvarez-Mesa, Chi Ching Chi, Ben Juurlink

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Tags: Computer science, H.264/AVC, nVidia, nVidia GeForce GT 430, nVidia GeForce GTS 450, nVidia GeForce GTX 560 Ti, OpenCL

September 14, 2012 by hgpu

Parallel Ray Tracing Simulations with MATLAB for Dynamic Lens Systems

Nicolai Wengert, Dan Negrut

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GT 540 M, nVidia GeForce GTX 480, Raytracing, Tesla C2050

September 14, 2012 by hgpu

On the Validation and Applications of a Parallel Flexible Multi-Body Dynamics Implementation

Daniel J. Melanz

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Tesla C2070, Thesis

September 14, 2012 by hgpu

Accelerating Sparse Matrix Kernels on Graphics Processing Units

Kiran Kumar Matam

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, Sparse matrix, Tesla C1060, Tesla C2050, Thesis

September 14, 2012 by hgpu

Data Sorting Using Graphics Processing Units

Marko J. Misic, Milo V. Tomasevic

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTS 250, Sorting

September 13, 2012 by hgpu

Exploring Heterogeneous Scheduling using the Task-Centric Programming Model

Artur Podobas, Mats Brorsson, Vladimir Vlassov

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 570, Task scheduling

September 13, 2012 by hgpu

Systematic Approach in Optimizing Numerical Memory-Bound Kernels on GPU

Ahmad Abdelfattah, David Keyes, Hatem Ltaief

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2070

September 13, 2012 by hgpu

Mapping a Dataflow Programming Model onto Heterogeneous Architectures

Alina Sbirlea

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 580, Tesla C1060, Thesis

September 12, 2012 by hgpu

Medusa: Simplified Graph Processing on GPUs

Jianlong Zhong, Bingsheng He

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Optimization, Performance, Tesla C2050

September 12, 2012 by hgpu

A First Step Towards GPU-assisted Query Optimization

Max Heimel, Volker Markl

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Tags: Computer science, Databases, nVidia, nVidia GeForce GTX 460, OpenCL, Optimization, Package

September 11, 2012 by hgpu

Assembly-Free Large-Scale Modal Analysis on the GPU

Praveen Yadav, Krishnan Suresh

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Voxelization

September 11, 2012 by hgpu

Design and Modeling of a Non-blocking Checkpointing System

Kento Sato, Kathryn Mohror, Adam Moody, Naoya Maruyama, Satoshi Matsuoka

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Tags: Computer science, Fault tolerance, GPU cluster, nVidia, Tesla M2050

September 11, 2012 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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high performance computing on graphics processing units: hgpu.org

An Optimized Parallel IDCT on Graphics Processing Units

Parallel Ray Tracing Simulations with MATLAB for Dynamic Lens Systems

On the Validation and Applications of a Parallel Flexible Multi-Body Dynamics Implementation

Accelerating Sparse Matrix Kernels on Graphics Processing Units

Data Sorting Using Graphics Processing Units

Exploring Heterogeneous Scheduling using the Task-Centric Programming Model

Systematic Approach in Optimizing Numerical Memory-Bound Kernels on GPU

Mapping a Dataflow Programming Model onto Heterogeneous Architectures

Medusa: Simplified Graph Processing on GPUs

A First Step Towards GPU-assisted Query Optimization

Assembly-Free Large-Scale Modal Analysis on the GPU

Design and Modeling of a Non-blocking Checkpointing System

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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