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An Analysis of OpenACC Programming Model: Image Processing Algorithms as a Case Study

M. J. Misic, D. D. Dasic, M. V. Tomasevic

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GT 335 M, OpenACC

August 2, 2014 by hgpu

Extracting Maximal Exact Matches on GPU

Anas Abu-Doleh, Kamer Kaya, Mohamed Abouelhoda, Umit V. Catalyurek

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Tags: Algorithms, Bioinformatics, Computer science, CUDA, Indexing, nVidia, Suffix trees, Tesla K20

August 2, 2014 by hgpu

Integrated Arrival and Departure Schedule Optimization Under Uncertainty

Min Xue, Shannon Zelinski

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Tags: CUDA, Earth and Space Sciences, Monte Carlo simulation, nVidia, nVidia GeForce GTX 690, Optimization

August 2, 2014 by hgpu

Accelerated Matrix Element Method with Parallel Computing

Doug Schouten, Adam DeAbreu, Bernd Stelzer

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Tags: AMD Radeon R9 290, ATI, Computational Complexity, Computational Physics, Monte Carlo integration, Neural networks, OpenCL, Physics, Probability

August 2, 2014 by hgpu

CUDA Accelerated Entropy Constrained Vector Quantization and Multiple K-Means

John Ashley, Amy J. Braverman

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Tags: Compression, Computer science, CUDA, nVidia, Tesla K40, Vector quantization, Visualization

August 1, 2014 by hgpu

Scalable and High Performance Betweenness Centrality on the GPU

Adam McLaughlin, David A. Bader

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Tags: Algorithms, Computer science, CUDA, Graph theory, Numerical simulation, nVidia, nVidia GeForce GTX Titan, Package, Tesla M2090

August 1, 2014 by hgpu

A Scalable Approach to Solving Dense Linear Algebra Problems on Hybrid CPU-GPU Systems

Fengguang Song, Jack Dongarra

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, Linear Algebra, nVidia, Tesla K20

August 1, 2014 by hgpu

Optimizing performance per watt on GPUs in High Performance Computing: temperature, frequency and voltage effects

D. C. Price, M. A. Clark, B. R. Barsdell, R. Babich, L. J. Greenhill

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Tags: Astrophysics, CUDA, Energy-efficient computing, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 780, Package, Performance, Signal processing, Tesla K20

August 1, 2014 by hgpu

Discriminative Convolutional Sum-Product Networks on GPU

Tobias Hartmann

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Tags: Algorithms, Benchmarking, Computer science, Computer vision, CUDA, Neural networks, nVidia, Tesla K20, Thesis

August 1, 2014 by hgpu

Automatic Parallelization of Tiled Stencil Loop Nests on GPUs

Peng Di

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Performance, Tesla C1060, Tesla C2050, Thesis

July 30, 2014 by hgpu

Dynamic Data Management Among Multiple Databases for Optimization of Parallel Computations in Heterogeneous HPC Systems

Pawel Rosciszewski

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Tags: Computer science, Databases, Heterogeneous systems, nVidia, nVidia Quadro FX 3800, OpenCL, Prefetch, Tesla C2050

July 30, 2014 by hgpu

Scaling Multifluid Compressible Fluid Dynamics to 700,000 cores, 1.5 Pflop/s, and a Trillion Grid Cells

Paul R. Woodward, Jagan Jayaraj, Pei-Hung Lin, Michael Knox, Sarah E. Anderson, James Greensky

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Tags: Fluid dynamics, Intel Xeon Phi

July 30, 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

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

An Analysis of OpenACC Programming Model: Image Processing Algorithms as a Case Study

Extracting Maximal Exact Matches on GPU

Integrated Arrival and Departure Schedule Optimization Under Uncertainty

Accelerated Matrix Element Method with Parallel Computing

CUDA Accelerated Entropy Constrained Vector Quantization and Multiple K-Means

Scalable and High Performance Betweenness Centrality on the GPU

A Scalable Approach to Solving Dense Linear Algebra Problems on Hybrid CPU-GPU Systems

Optimizing performance per watt on GPUs in High Performance Computing: temperature, frequency and voltage effects

Discriminative Convolutional Sum-Product Networks on GPU

Automatic Parallelization of Tiled Stencil Loop Nests on GPUs

Dynamic Data Management Among Multiple Databases for Optimization of Parallel Computations in Heterogeneous HPC Systems

Scaling Multifluid Compressible Fluid Dynamics to 700,000 cores, 1.5 Pflop/s, and a Trillion Grid Cells

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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