high performance computing on graphics processing units: hgpu.org

Mark S. Friedrichs, Peter Eastman, Vishal Vaidyanathan, Mike Houston, Scott Legrand, Adam L. Beberg, Daniel L. Ensign, Christopher M. Bruns, Vijay S. Pande

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Source codes

Tags: ATI, ATI Radeon HD 4870, ATI Stream, Biology, Brook, Chemistry, Computational chemistry, Molecular dynamics, nVidia, nVidia GeForce GTX 280, Package, Solvent effects

October 30, 2010 by hgpu

A performance study of general-purpose applications on graphics processors using CUDA

S. Che, M. Boyer, J. Meng, D. Tarjan, J. Sheaffer, K. Skadron

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, OpenMP, Package, Performance

October 30, 2010 by hgpu

Rise of the Graphics Processor

D. Blythe

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Tags: Computer science, Review

October 30, 2010 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

Applications

Accelerating Density Functional Calculations with Graphics Processing Unit

A Memory Model for Scientific Algorithms on Graphics Processors

A hardware redundancy and recovery mechanism for reliable scientific computation on graphics processors

Performance enhancement of MAGIC FDTD-PIC plasma-wave simulations using GPU processing

Optimizing data intensive GPGPU computations for DNA sequence alignment

Accelerating molecular modeling applications with graphics processors

Mars: a MapReduce framework on graphics processors

Exploiting graphics processing units for computational biology and bioinformatics

High performance direct gravitational N-body simulations on graphics processing units II: An implementation in CUDA

Accelerating molecular dynamic simulation on graphics processing units

A performance study of general-purpose applications on graphics processors using CUDA

Rise of the Graphics Processor

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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