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Efficient Particle-Mesh Spreading on GPUs

Xiangyu Guo, Xing Liu, Peng Xu, Zhihui Du, Edmond Chow

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Tesla K40

October 29, 2014 by hgpu

Performance Modeling, Optimization, and Characterization on Heterogeneous Architectures

Lokendra Singh Panwar

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Computational Complexity, Computer science, CUDA, Finite difference, GPU cluster, Heterogeneous systems, MPI, nVidia, OpenCL, Seismology, Tesla C1060, Tesla C2050, Thesis

October 29, 2014 by hgpu

Parallel training of Deep Neural Networks with Natural Gradient and Parameter Averaging

Daniel Povey, Xiaohui Zhang, Sanjeev Khudanpur

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, Speech recognition, Tesla K10, Tesla K20

October 29, 2014 by hgpu

Testing and Exposing Weak Graphics Processing Unit Memory Models

Tyler Rey Sorensen

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 750, nVidia GeForce GTX Titan, PTX, Tesla C2075, Thesis

October 27, 2014 by hgpu

Parallel Finite Volume Algorithm on Graphic Processing Units (GPU)

Amirsaman Farrokhpanah, Hanif Montazeri, Javad Mostaghimi

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Tags: Algorithms, CUDA, Fluid dynamics, nVidia, Tesla K20

October 27, 2014 by hgpu

Bayesian Neural Networks in Data-Intensive High Energy Physics Applications

Michelle Perry

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Tags: Bayesian, CUDA, High Energy Physics - Phenomenology, Neural networks, nVidia, nVidia GeForce GT 320 M, Physics, Tesla M2050

October 27, 2014 by hgpu

Finding Longest Common Subsequences by GPU-Based Parallel Ant Colony Optimization

David Markvica

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Tags: Algorithms, Biology, Computational biology, Computer science, Heterogeneous systems, Metaheuristics, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, Optimization, Pattern recognition, Thesis

October 27, 2014 by hgpu

Contract-Based General-Purpose GPU Programming

Alexey Kolesnichenko, Christopher M. Poskitt, Sebastian Nanz, Bertrand Meyer

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Source codes

Tags: Code generation, Computer science, CUDA, nVidia, nVidia Quadro K 2000 M, Package, Software Engineering

October 27, 2014 by hgpu

GPGPU Acceleration for Skeletal Animation-comparing OpenCL with CUDA and GLSL

Shousheng Liu, Ge Chen, Chunyong Ma, Yong Han

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Tags: ATI, ATI Radeon HD 7750, Computer science, CUDA, GLSL, nVidia, nVidia GeForce GTS 250, nVidia GeForce GTX 670, OpenCL, OpenGL, Performance, Rendering

October 25, 2014 by hgpu

Evacuation Route Modeling and Planning with General Purpose GPU Computing

David D. Prentiss

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Tags: Algorithms, ATI, ATI Radeon HD 7770, Computer science, OpenCL, Path problems, Thesis

October 25, 2014 by hgpu

On the Efficiency of CPU and Hybrid CPU-GPU Systems in Computational Biology Tasks

Nikolay Pydiura, Pavel Karpov, Yaroslav Blume

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Tags: AMD Radeon R9 280, ATI, Biology, Computational biology, CUDA, Molecular dynamics, nVidia, nVidia GeForce GTX 480, OpenCL

October 25, 2014 by hgpu

Medical imaging using CUDA

Thomas Kovac

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Tags: CUDA, Image registration, Medicine, MRI, nVidia, Thesis

October 25, 2014 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

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

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

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

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

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high performance computing on graphics processing units: hgpu.org

Applications

Efficient Particle-Mesh Spreading on GPUs

Performance Modeling, Optimization, and Characterization on Heterogeneous Architectures

Parallel training of Deep Neural Networks with Natural Gradient and Parameter Averaging

Testing and Exposing Weak Graphics Processing Unit Memory Models

Parallel Finite Volume Algorithm on Graphic Processing Units (GPU)

Bayesian Neural Networks in Data-Intensive High Energy Physics Applications

Finding Longest Common Subsequences by GPU-Based Parallel Ant Colony Optimization

Contract-Based General-Purpose GPU Programming

GPGPU Acceleration for Skeletal Animation-comparing OpenCL with CUDA and GLSL

Evacuation Route Modeling and Planning with General Purpose GPU Computing

On the Efficiency of CPU and Hybrid CPU-GPU Systems in Computational Biology Tasks

Medical imaging using CUDA

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

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

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

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

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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