high performance computing on graphics processing units: hgpu.org

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VOCL: An Optimized Environment for Transparent Virtualization of Graphics Processing Units

Shucai Xiao, Pavan Balaji, Qian Zhu, Rajeev Thakur, Susan Coghlan, Heshan Lin, Gaojin Wen, Jue Hong, Wu-chun Feng

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Tags: Computer science, nVidia, OpenCL, Tesla M2070, Virtualization

March 18, 2012 by hgpu

Globally scheduled real-time multiprocessor systems with GPUs

Glenn A. Elliott, James H. Anderson

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Task scheduling

March 16, 2012 by hgpu

CUDA 2D Stencil Computations for the Jacobi Method

Jose Maria Cecilia, Jose Manuel Garcia, Manuel Ujaldon

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Differential equations, Linear Algebra, nVidia, Optimization, Tesla C1060, Tesla C870

March 16, 2012 by hgpu

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Dimitar Lukarski

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Tags: Algorithms, Computer science, CUDA, Differential equations, Factorization, FEM, Finite difference, Finite element method, Linear Algebra, nVidia, nVidia GeForce GTX 580, Partial differential equations, PDEs, Sparse matrix, Tesla M1060, Tesla S1070, Thesis

March 16, 2012 by hgpu

Developing a CUDA solver for large sparse matrices for MARIN

Martijn de Jong

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Tags: Computer science, CUDA, Mathematics, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 580, nVidia Quadro NVS 295, Thesis

March 16, 2012 by hgpu

Multi-platform Linear Algebra

E. Ketelaer, D. Lukarski

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Tags: Computer science, CUDA, Differential equations, Distributed data structures, Linear Algebra, nVidia, Package, Partial differential equations, PDEs

March 16, 2012 by hgpu

On the Use of Small 2D Convolutions on GPUs

Shams A.H. Al Umairy, Alexander S. van Amesfoort, Irwan D. Setija, Martijn C. van Beurden, Henk J. Sips

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Tags: Computer science, CUDA, Electrodynamics, FFT, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Optimization, Physics, Tesla C1060

March 15, 2012 by hgpu

Iterative Statistical Kernels on Contemporary GPUs

Thilina Gunarathne, Bimalee Salpitikorala, Arun Chauhan, Geoffrey Fox

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Tags: Algorithms, Cloud, Clustering, Computer science, nVidia, OpenCL, Sparse matrix, Tesla C1060, Tesla C2070, Tesla M2050

March 15, 2012 by hgpu

Performance analysis and optimization of the OP2 framework on many-core architectures

M.B. Giles, G.R. Mudalige, Z. Sharif, G. Markall, P.H.J. Kelly

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Tags: Benchmarking, Computer science, CUDA, Fluid dynamics, nVidia, OpenMP, Optimization, Package, Performance, Tesla C2050

March 15, 2012 by hgpu

A Spiking Neural P system simulator based on CUDA

Francis Cabarle, Henry Adorna, Miguel A. Martinez-del-Amor

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Tags: Algorithms, Computer science, CUDA, Membrane computing, nVidia, nVidia GeForce 9400 M, Package

March 15, 2012 by hgpu

Targeting heterogeneous architectures via macro data flow

M. Aldinucci, M. Danelutto, P. Kilpatrick, M. Torquati

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Tags: Algorithms, Computer science, Heterogeneous systems, nVidia, Tesla C2050

March 13, 2012 by hgpu

Expressive Array Constructs in an Embedded GPU Kernel Programming Language

Koen Claessen, Mary Sheeran, Bo Joel Svensson

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Tags: Algorithms, Code generation, Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Sorting

March 13, 2012 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

VOCL: An Optimized Environment for Transparent Virtualization of Graphics Processing Units

Globally scheduled real-time multiprocessor systems with GPUs

CUDA 2D Stencil Computations for the Jacobi Method

Parallel Sparse Linear Algebra for Multi-core and Many-core Platforms: Parallel Solvers and Preconditioners

Developing a CUDA solver for large sparse matrices for MARIN

Multi-platform Linear Algebra

On the Use of Small 2D Convolutions on GPUs

Performance analysis and optimization of the OP2 framework on many-core architectures

A Spiking Neural P system simulator based on CUDA

Targeting heterogeneous architectures via macro data flow

Expressive Array Constructs in an Embedded GPU Kernel Programming Language

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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