high performance computing on graphics processing units: hgpu.org

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A Survey Of Techniques for Architecting and Managing Asymmetric Multicore Processors

Sparsh Mittal

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Tags: asymmetric multicore processor (AMP), big/little system, classification, heterogeneous multicore architecture, reconfigurable AMP, Review, survey

November 13, 2015 by sparsh0mittal

Sequential Code Parallelization for Multi-core Embedded Systems: A Survey of Models, Algorithms and Tools

Jorge Alberto Castro Godinez

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Tags: Computer science, Parallelization, Review, Thesis

October 22, 2015 by hgpu

Use of modern GPUs in Design Optimization

M.H. Aissa, T. Verstraete, C. Vuik

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Tags: Computer science, Optimization, Review

May 19, 2015 by hgpu

A Survey Of Architectural Approaches for Data Compression in Cache and Main Memory Systems

Sparsh Mittal and Jeffrey S. Vetter

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Tags: 3D memory, bandwidth compression, cache, classification, cpu, GPU, HPC, main memory, NVM, Review

May 18, 2015 by sparsh0mittal

Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

Vadim Demchik

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, Computer science, Monte Carlo simulation, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 560 M, nVidia GeForce GTX 780, OpenCL, Package, Pseudo-random number generators, Review, Tesla K40

March 25, 2015 by hgpu

A Review of CUDA, MapReduce, and Pthreads Parallel Computing Models

Kato Mivule, Benjamin Harvey, Crystal Cobb, Hoda El Sayed

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Tags: Computer science, CUDA, MapReduce, nVidia, Overview, Pthreads, Review, Tesla K20

October 18, 2014 by hgpu

Interactive Wave Simulations

Akash Mittal

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Tags: CUDA, Fluid dynamics, Fluid simulation, nVidia, Review, Thesis, Visualization

September 15, 2014 by hgpu

Improvements to Physically Based Cloth Simulation

Tsz Ho Wong

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Tags: 3D Graphics and Realism, Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 780, Review, Thesis

September 9, 2014 by hgpu

Professional CUDA C Programming

John Cheng, Max Grossman, Ty McKercher

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Tags: Algorithms, Book, Computer science, CUDA, Memory model, nVidia, Review

September 8, 2014 by hgpu

Multi-Agent Systems and General-Purpose Computing on Graphics Processing Units: A Survey

Emmanuel Hermellin, Fabien Michel, Jacques Ferber

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Tags: Computer science, CUDA, nVidia, Review

August 7, 2014 by hgpu

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

David Rohr

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Review, Thesis

July 14, 2014 by hgpu

GPU Implementation of Bayesian Neural Network Construction for Data-Intensive Applications

Michelle Perry, Harrison B. Prosper, Anke Meyer-Baese

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Tags: Bayesian, CUDA, Neural networks, nVidia, nVidia GeForce GTX 480, Physics, Review

June 17, 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

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

A Survey Of Techniques for Architecting and Managing Asymmetric Multicore Processors

Sequential Code Parallelization for Multi-core Embedded Systems: A Survey of Models, Algorithms and Tools

Use of modern GPUs in Design Optimization

A Survey Of Architectural Approaches for Data Compression in Cache and Main Memory Systems

Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

A Review of CUDA, MapReduce, and Pthreads Parallel Computing Models

Interactive Wave Simulations

Improvements to Physically Based Cloth Simulation

Professional CUDA C Programming

Multi-Agent Systems and General-Purpose Computing on Graphics Processing Units: A Survey

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

GPU Implementation of Bayesian Neural Network Construction for Data-Intensive Applications

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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