high performance computing on graphics processing units: hgpu.org

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Indexing of Spatiotemporal Trajectories for Efficient Distance Threshold Similarity Searches on the GPU

Michael Gowanlock, Henri Casanova

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Tags: Astrophysics, Computer science, Databases, nVidia, OpenCL, Tesla C2075

January 19, 2015 by hgpu

CURFIL: Random Forests for Image Labeling on GPU

Hannes Schulz, Benedikt Waldvogel, Rasha Sheikh, Sven Behnke

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 675 M, nVidia GeForce GTX Titan, Package, Tesla K20

January 16, 2015 by hgpu

SW#db: GPU-accelerated exact sequence similarity database search

Matija Korpar, Martin Sosic, Dino Blazeka, Mile Sikic

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Tags: Algorithms, Biology, CUDA, Databases, Next-Generation sequencing, nVidia, nVidia GeForce GTX 690, nVidia GeForce GTX 780, Package, Smith-Waterman algorithm

January 16, 2015 by hgpu

Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units

Amlan Chatterjee

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Sorting, Tesla K20, Thesis

January 16, 2015 by hgpu

GPU Processing for UAS-Based LFM-CW Stripmap SAR

Craig Stringham, David G. Long

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Tags: Algorithms, CUDA, Image processing, Motion compensation, nVidia, nVidia GeForce GTX 285, SAR

January 16, 2015 by hgpu

Parallel Implementation of the Finite Element Method on Graphics Processors for the Solution of Incompressible Flows

Mahmut Murat Gocmen

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Tags: Algorithms, CUBLAS, CUDA, FEM, Finite element method, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 280, Package, Tesla C2075, Thesis

January 16, 2015 by hgpu

A Novel Computational Model for GPUs with Applications to Efficient Algorithms

Atsushi Koike, Kunihiko Sadakane

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Tags: Algorithms, Computer science, CUDA, nVidia, Sorting, Tesla C1060, Tesla K20

January 15, 2015 by hgpu

Identification and Elimination of Platform-Specific Code Smells in High Performance Computing Applications

Chunyan Wang, Shoichi Hirasawa, Hiroyuki Takizawa, Hiroaki Kobayashi

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Tags: Computer science, CUDA, nVidia, OpenACC, OpenCL, Tesla C1060, Tesla C2070, Tesla K20

January 15, 2015 by hgpu

Reducing overheads of dynamic scheduling on heterogeneous chips

Francisco Corbera, Andres Rodriguez, Rafael Asenjo, Angeles Navarro, Antonio Vilches, Maria J. Garzaran

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Tags: Computer science, Heterogeneous systems, OpenCL, Operating systems

January 15, 2015 by hgpu

Batched Matrix Computations on Hardware Accelerators Based on GPUs

Azzam Haidar, Tingxing Dong, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Factorization, nVidia, Tesla K40

January 15, 2015 by hgpu

High Performance GPU-based Fourier Volume Rendering

Marwan Abdellah, Ayman Eldeib, Amr Sharawi

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 640, nVidia Quadro K5000, OpenGL, Rendering, Visualization

January 15, 2015 by hgpu

Linear Performance-Breakdown Model: A Framework for GPU kernel programs performance analysis

Chapa Martell Mario Alberto, Hiroyuki Sato

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Tags: Computer science, nVidia, nVidia GeForce GTX 660, OpenCL, Performance

January 13, 2015 by hgpu

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

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

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high performance computing on graphics processing units: hgpu.org

Applications

Indexing of Spatiotemporal Trajectories for Efficient Distance Threshold Similarity Searches on the GPU

CURFIL: Random Forests for Image Labeling on GPU

SW#db: GPU-accelerated exact sequence similarity database search

Parallel Algorithms for Counting Problems on Graphs Using Graphics Processing Units

GPU Processing for UAS-Based LFM-CW Stripmap SAR

Parallel Implementation of the Finite Element Method on Graphics Processors for the Solution of Incompressible Flows

A Novel Computational Model for GPUs with Applications to Efficient Algorithms

Identification and Elimination of Platform-Specific Code Smells in High Performance Computing Applications

Reducing overheads of dynamic scheduling on heterogeneous chips

Batched Matrix Computations on Hardware Accelerators Based on GPUs

High Performance GPU-based Fourier Volume Rendering

Linear Performance-Breakdown Model: A Framework for GPU kernel programs performance analysis

Recent source codes

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

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

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