high performance computing on graphics processing units: hgpu.org

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Beyond Amdahl’s Law: An Objective Function That Links Multiprocessor Performance Gains To Delay and Energy

Andrew S. Cassidy, Andreas G. Andreou

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Tags: Computer science, Performance

December 22, 2011 by hgpu

A block-asynchronous relaxation method for graphics processing units

Hartwig Anzt, Stanimire Tomov, Jack Dongarra, Vincent Heuveline

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Tesla C2050

December 22, 2011 by hgpu

AES Encryption and Decryption Using Direct3D 10 API

Adrian Marius Chiuta

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Tags: AES, Algorithms, Computer science, CUDA, DirectX, nVidia, nVidia GeForce 9800 GTX, Security

December 22, 2011 by hgpu

GPU-based parallel collision detection for real-time motion planning

Jia Pan, Dinesh Manocha

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Tags: Algorithms, Benchmarking, Clustering, Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 480

December 22, 2011 by hgpu

Generative programming methods for parallel partial differential field equation solvers

Daniel Peter Playne

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Tags: Code generation, Computer science, CUDA, Field equations, MPI, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Tesla C2050, Thesis

December 22, 2011 by hgpu

Extending adaptive sparse grids for stochastic collocation to hybrid parallel architectures

Richard K. Archibald, Ralf Deiterding, John Jakeman

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Tags: Computer science, CUDA, Hybrid computing, nVidia, Stochastic simulation, Tesla C2050

December 22, 2011 by hgpu

Solving Quadratic Programming Problems on Graphics Processing Unit

Yunlong Huang, Keck Voon Ling, Simon See

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Tags: Algorithms, Computer science, CUDA, nVidia, Tesla S1070

December 22, 2011 by hgpu

Warp-Level Parallelism: Enabling Multiple Replications In Parallel on GPU

Jonathan Passerat-Palmbach, Jonathan Caux, Pridi Siregar, Claude Mazel, D.R.C.Hill

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Tags: Benchmarking, Computer science, CUDA, nVidia, Stochastic simulation, Tesla C2050, Warp level parallelism

December 21, 2011 by hgpu

Parallel Inference on Structured Data with CRFs on GPUs

Nico Piatkowski, Katharina Morik

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Source codes

Tags: Algorithms, Computer science, CUDA, Databases, Graph theory, nVidia, Package, Tesla C2050

December 21, 2011 by hgpu

Implementation of a Parallel Tree Method on a GPU

Naohito Nakasato

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Tags: Astrophysics, ATI, ATI IL, ATI Radeon HD 5870, Computational Complexity, Computer science, Galaxy Astrophysics, Instrumentation and Methods for Astrophysics, KD-tree, OpenCL, Optimization, Performance

December 21, 2011 by hgpu

Performance and Quality of Random Number Generators

V. du Preez, M.G.B. Johnson, A. Leist, K.A. Hawick

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Tags: Algorithms, Computer science, CUDA, Monte Carlo simulation, Numerical simulation, nVidia, nVidia GeForce GTX 580, Pseudo-random number generators, Review

December 20, 2011 by hgpu

A Framework for Genetic Algorithms in Parallel Environments

Tomoyuki Hiroyasu, Ryosuke Yamanaka, Masato Yoshimi, Mitsunori Miki

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 250

December 20, 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

Beyond Amdahl’s Law: An Objective Function That Links Multiprocessor Performance Gains To Delay and Energy

A block-asynchronous relaxation method for graphics processing units

AES Encryption and Decryption Using Direct3D 10 API

GPU-based parallel collision detection for real-time motion planning

Generative programming methods for parallel partial differential field equation solvers

Extending adaptive sparse grids for stochastic collocation to hybrid parallel architectures

Solving Quadratic Programming Problems on Graphics Processing Unit

Warp-Level Parallelism: Enabling Multiple Replications In Parallel on GPU

Parallel Inference on Structured Data with CRFs on GPUs

Implementation of a Parallel Tree Method on a GPU

Performance and Quality of Random Number Generators

A Framework for Genetic Algorithms in Parallel Environments

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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