high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Characterizing Dataset Dependence for Sparse Matrix-Vector Multiplication on GPUs

N. Sedaghati, A. Ashari, L. N. Pouchet, S. Parthasarathy, P. Sadayappan

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Performance, Sparse matrix, Tesla K40

June 16, 2015 by hgpu

Parallelization of DIRA and CTmod using OpenMP and OpenCL

Alexander Ortenberg

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Tags: AMD Radeon R7 260, ATI, Computed tomography, CT, Image processing, Image reconstruction, Intel Xeon Phi, Medicine, OpenCL, OpenMP, Thesis, Tomography

June 16, 2015 by hgpu

GPU Predictor-Corrector Interior Point Method for Large-Scale Linear Programming

David Rydberg

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Thesis

June 16, 2015 by hgpu

Type-safe Runtime Code Generation: Accelerate to LLVM

Trevor L. McDonell, Manuel M. T. Chakravarty, Vinod Grover, Ryan R. Newton

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Tags: Code generation, Computer science, CUDA, nVidia, Package, Sparse matrix, Tesla K40

June 14, 2015 by hgpu

Automatic Selection of Sparse Matrix Representation on GPUs

Naser Sedaghati, Te Mu, Louis-Noel Pouchet, Srinivasan Parthasarathy, P. Sadayappan

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 580, Physics, Sparse matrix, Tesla K20, Tesla K40

June 14, 2015 by hgpu

A GPU vs CPU performance evaluation of an experimental video compression algorithm

Stamos Katsigiannis, Vasilis Dimitsas, Dimitris Maroulis

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Tags: Algorithms, Compression, CUDA, Image processing, nVidia, Tesla C2070, Video encoding

June 14, 2015 by hgpu

Poisson-Boltzmann model for protein-surface electrostatic interactions and grid-convergence study using the PyGBe code

Christopher D. Cooper, Lorena A. Barba

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Tags: Biomolecules, Boltzmann equation, Computational Physics, CUDA, Electrostatics, nVidia, Package, Physics, Poisson Boltzmann, Python, Tesla C2075

June 14, 2015 by hgpu

Accelerating parameter synthesis for stochastic models

Petr Pilar

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Package, Probability, Sparse matrix, Thesis

June 14, 2015 by hgpu

A GPU-Accelerated Two Stage Visual Matching

Hannes Fassold, Harald Stiegler, Jakub Rosnery, Marcus Thaler, Werner Bailer

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Tags: CUDA, Image retrieval, SIFT

June 13, 2015 by HannesF99

Practical Symbolic Execution Analysis and Methodology for GPU Programs

Peng Li

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Thesis

June 10, 2015 by hgpu

A Pattern Specification and Optimizations Framework for Accelerating Scientific Computations on Heterogeneous Clusters

Linchuan Chen, Xin Huo, Gagan Agrawal

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, Tesla M2070

June 10, 2015 by hgpu

Sequential Monte Carlo Optimisation for Air Traffic Management

A.J. Eele, J.M. Maciejowski

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Tags: Algorithms, CUDA, Mathematics, nVidia, nVidia GeForce GTX 580, Optimization, Tesla C2070

June 10, 2015 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

Programming

Characterizing Dataset Dependence for Sparse Matrix-Vector Multiplication on GPUs

Parallelization of DIRA and CTmod using OpenMP and OpenCL

GPU Predictor-Corrector Interior Point Method for Large-Scale Linear Programming

Type-safe Runtime Code Generation: Accelerate to LLVM

Automatic Selection of Sparse Matrix Representation on GPUs

A GPU vs CPU performance evaluation of an experimental video compression algorithm

Poisson-Boltzmann model for protein-surface electrostatic interactions and grid-convergence study using the PyGBe code

Accelerating parameter synthesis for stochastic models

A GPU-Accelerated Two Stage Visual Matching

Practical Symbolic Execution Analysis and Methodology for GPU Programs

A Pattern Specification and Optimizations Framework for Accelerating Scientific Computations on Heterogeneous Clusters

Sequential Monte Carlo Optimisation for Air Traffic Management

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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