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Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU

Ichitaro Yamazaki, Stanimire Tomov, Jack Dongarra

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Tags: BLAS, Computer science, CUDA, Linear Algebra, Matrix decomposition, Mixed precision, Numerical Analysis, nVidia, Performance, Tesla K20

July 16, 2016 by hgpu

An investigation of GPU-based stiff chemical kinetics integration methods

Nicholas J. Curtis, Kyle E. Niemeyer, Chih-Jen Sung

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Tags: Algorithms, Chemistry, Computational Physics, CUDA, nVidia, Physics, Tesla C2075

July 16, 2016 by hgpu

Finite Element Integration with Quadrature on the GPU

Matthew G. Knepley, Karl Rupp, Andy R. Terrel

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Tags: AMD FirePro W9100, ATI, Computer science, Differential equations, Mathematical Software, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 750 Ti, OpenCL, Partial differential equations, PDEs, Tesla K20

July 16, 2016 by hgpu

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

Ye Fang, Yun Ding, Wei P. Feinstein, David M. Koppelman, Juana Moreno, Mark Jarrell, J. Ramanujam, Michal Brylinski

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Tags: Algorithms, Chemistry, CUDA, Heterogeneous systems, Intel Xeon Phi, Medicine, Molecular dynamics, nVidia, nVidia GeForce GTX 980, OpenMP, Package

July 16, 2016 by hgpu

Accelerating Eulerian Fluid Simulation With Convolutional Networks

Jonathan Tompson, Kristofer Schlachter, Pablo Sprechmann, Ken Perlin

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Tags: 3D Graphics and Realism, CNN, Computational Complexity, CUDA, Deep learning, Fluid dynamics, Fluid simulation, Machine learning, nVidia, nVidia GeForce GTX Titan X

July 16, 2016 by hgpu

GPU Accelerated Discrete Element Method (DEM) Molecular Dynamics for Conservative, Faceted Particle Simulations

Matthew Spellings, Ryan L. Marson, Joshua A. Anderson, Sharon C. Glotzer

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Tags: Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia Quadro M 6000, Package, Particle simulation, Physics

July 13, 2016 by hgpu

Survey of Domain-Specific Languages for FPGA Computing

Nachiket Kapre, Samuel Bayliss

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Tags: Computer science, DSL, FPGA, survey

July 13, 2016 by hgpu

OpenFace: A general-purpose face recognition library with mobile applications

Brandon Amos, Bartosz Ludwiczuk, Mahadev Satyanarayanan

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Tags: Computer science, Computer vision, CUDA, Deep learning, Lua, Neural networks, nVidia, Package, Python, Tesla K40

July 13, 2016 by hgpu

LU, QR, and Cholesky factorizations: Programming Model, Performance Analysis and Optimization Techniques for the Intel Knights Landing Xeon Phi

Azzam Haidar, Stanimire Tomov, Konstantin Arturov, Murat Guney, Shane Story, Jack Dongarra

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Tags: Algorithms, Computer science, Factorization, Heterogeneous systems, Intel Xeon Phi, Linear Algebra, Performance, Task scheduling

July 13, 2016 by hgpu

The Vectorization of the Tersoff Multi-Body Potential: An Exercise in Performance Portability

Markus Hohnerbach, Ahmed E. Ismail, Paolo Bientinesi

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Tags: Chemistry, Computational chemistry, Computer science, CUDA, Intel Xeon Phi, Materials Science, Molecular dynamics, MPI, nVidia, Package, performance portability, Tesla K20, Tesla K40

July 13, 2016 by hgpu

Using Deep Convolutional Neural Networks in Monte Carlo Tree Search

Tobias Graf, Marco Platzner

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Tags: Algorithms, CNN, Computer science, CUDA, Deep learning, Neural networks, nVidia, Search, Tesla K20

July 11, 2016 by hgpu

Comparing Parallel Hardware Architectures for Visually Guided Robot Navigation

Wolfram Schenck, Michael Horst, Tim Tiedemann, Sergius Gaulik, Ralf Moller

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Tags: ATI, ATI Radeon HD 7970, Computer science, Computer vision, FPGA, nVidia, nVidia GeForce GTX 570, nVidia Quadro NVS 4200 M, OpenCL, Review, Robotics

July 11, 2016 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

Stability and Performance of Various Singular Value QR Implementations on Multicore CPU with a GPU

An investigation of GPU-based stiff chemical kinetics integration methods

Finite Element Integration with Quadrature on the GPU

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

Accelerating Eulerian Fluid Simulation With Convolutional Networks

GPU Accelerated Discrete Element Method (DEM) Molecular Dynamics for Conservative, Faceted Particle Simulations

Survey of Domain-Specific Languages for FPGA Computing

OpenFace: A general-purpose face recognition library with mobile applications

LU, QR, and Cholesky factorizations: Programming Model, Performance Analysis and Optimization Techniques for the Intel Knights Landing Xeon Phi

The Vectorization of the Tersoff Multi-Body Potential: An Exercise in Performance Portability

Using Deep Convolutional Neural Networks in Monte Carlo Tree Search

Comparing Parallel Hardware Architectures for Visually Guided Robot Navigation

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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