high performance computing on graphics processing units: hgpu.org

hgpu.org » Computer science

Searching for Concurrent Design Patterns in Video Games

Micah J. Best, Alexandra Fedorova, Ryan Dickie, Andrea Tagliasacchi, Alex Couture-Beil, Craig Mustard, Shane Mottishaw, Aron Brown, Zhi Feng Huang, Xiaoyuan Xu, Nasser Ghazali, Andrew Brownsword

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Tags: Algorithms, Computer science, Games, Performance

September 16, 2011 by hgpu

A Light-Weight Approach to Dynamical Runtime Linking Supporting Heterogenous, Parallel, and Reconfigurable Architectures

Rainer Buchty, David Kramer, Mario Kicherer, Wolfgang Karl

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Tags: Algorithms, Computer science, Heterogeneous systems, Programming techniques

September 16, 2011 by hgpu

Optimizations and Performance of a Robotics Grasping Algorithm Described in Geometric Algebra

Florian Worsdorfer, Florian Stock, Eduardo Bayro-Corrochano, Dietmar Hildenbrand

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Optimization, Package, Performance

September 16, 2011 by hgpu

A Generic Approach to Topic Models

Gregor Heinrich

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Tags: Algorithms, Bayesian, Computer science

September 16, 2011 by hgpu

Implicit and dynamic trees for high performance rendering

Nathan Andrysco, Xavier Tricoche

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Tags: 3D Graphics and Realism, Computer science, CUDA, KD-tree, nVidia, nVidia GeForce GTX 480, Raytracing, Rendering

September 16, 2011 by hgpu

Processing data streams with hard real-time constraints on heterogeneous systems

Uri Verner, Assaf Schuster, Mark Silberstein

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Tags: AES, Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Performance, Security, Task scheduling

September 15, 2011 by hgpu

Strategies for preparing computer science students for the multicore world

Richard Brown, Elizabeth Shoop, Joel Adams, Curtis Clifton, Mark Gardner, Michael Haupt, Peter Hinsbeeck

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Tags: Algorithms, Computer science, Performance, Tutorial

September 15, 2011 by hgpu

Performing with CUDA

William B. Langdon

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Tags: Computer science, CUDA, nVidia, Operating systems, Performance, Review, Software Engineering, Tutorial

September 15, 2011 by hgpu

Scalable and deterministic timing-driven parallel placement for FPGAs

Chris C. Wang, Guy G.F. Lemieux

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Tags: Algorithms, Computer science, FPGA, Package, Programming techniques, Timing analysis

September 15, 2011 by hgpu

A platform-independent tool for modeling parallel programs

Ferosh Jacob, Jeff Gray, Yu Sun, Purushotham Bangalore

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Tags: Algorithms, Computer science, MPI, OpenMP, Performance, Programming Languages, Programming techniques

September 15, 2011 by hgpu

Ambient occlusion volumes

M. McGuire

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Tags: 3D Graphics and Realism, Algorithms, Computer science, GLSL, nVidia, nVidia GeForce GT 280, OpenGL

September 15, 2011 by hgpu

Auto-tuning of fast fourier transform on graphics processors

Yuri Dotsenko, Sara S. Baghsorkhi, Brandon Lloyd, Naga K. Govindaraju

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Tags: Computer science, CUDA, FFT, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 260, nVidia GeForce GTX 280, Performance, Software Engineering

September 14, 2011 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

Searching for Concurrent Design Patterns in Video Games

A Light-Weight Approach to Dynamical Runtime Linking Supporting Heterogenous, Parallel, and Reconfigurable Architectures

Optimizations and Performance of a Robotics Grasping Algorithm Described in Geometric Algebra

A Generic Approach to Topic Models

Implicit and dynamic trees for high performance rendering

Processing data streams with hard real-time constraints on heterogeneous systems

Strategies for preparing computer science students for the multicore world

Performing with CUDA

Scalable and deterministic timing-driven parallel placement for FPGAs

A platform-independent tool for modeling parallel programs

Ambient occlusion volumes

Auto-tuning of fast fourier transform on graphics processors

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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