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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

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

Performance of a code migration for the simulation of supersonic ejector flow to SMP, MIC and GPU using OpenMP, OpenMP+LEO, and OpenACC directives

C. Couder-Castaneda, H. Barrios-Pina, I. Gitler, M. Arroyo

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Tags: Computer science, Fortran, Intel Xeon Phi, nVidia, OpenACC, OpenMP, Performance, Tesla C2070

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

Design and optimization of DBSCAN Algorithm based on CUDA

Bingchen Wang, Chenglong Zhang, Lei Song, Lianhe Zhao, Yu Dou, Zihao Yu

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, Tesla K10

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

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

Parallelization of DIRA and CTmod using OpenMP and OpenCL

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

Performance of a code migration for the simulation of supersonic ejector flow to SMP, MIC and GPU using OpenMP, OpenMP+LEO, and OpenACC directives

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

Sequential Monte Carlo Optimisation for Air Traffic Management

Design and optimization of DBSCAN Algorithm based on CUDA

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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