CUDA | Page 340 | hgpu.org

Programming

hgpu.org » Programming » CUDA

Seismic Attributes Extraction Based on GPU

Zhang Guang-Zhi, Chen Lei, Ye Duan-Nan

View

Download (PDF)

Tags: CUDA, Earth and Space Sciences, nVidia, Tesla C1060

February 12, 2013 by hgpu

Implementing an architecture for efficient network traffic processing on modern graphics hardware

Lazaros Koromilas

View

Download (PDF)

Tags: Computer science, CUDA, Network communications, nVidia, nVidia GeForce GTX 480

February 12, 2013 by hgpu

Extending the Computational Application of Reaction-Diffusion Chemistry by Modelling Artificial Neural Networks

James Stovold

View

Download (PDF)

Tags: Biology, Chemistry, CUDA, Neural networks, nVidia, nVidia GeForce 9600 M GT

February 12, 2013 by hgpu

Adaptation of the MapReduce programming framework to compute-intensive data-analytics kernels

Reza Farivar

View

Download (PDF)

Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, nVidia GeForce GTX 275, Thesis

February 9, 2013 by hgpu

A multi-lane traffic simulation model via continuous cellular automata

Emanuele Rodaro, Oznur Yeldan

View

Download (PDF)

Source codes

Tags: Cellular automata, Computer science, CUDA, nVidia, nVidia GeForce GT 555 M, Package, Python

February 9, 2013 by hgpu

Practical Patient-Specific Cardiac Blood Flow Simulations Using SPH

Scott Kulp, Mingchen Gao, Shaoting Zhang, Zhen Qian, Szilard Voros, Dimitris Metaxas, Leon Axel

View

Download (PDF)

Tags: Collision detection, CUDA, Fluid simulation, Heart, Medicine, nVidia, nVidia GeForce GTX 590

February 9, 2013 by hgpu

Enabling Inter-Machine Parallelism in High-Level Languages with SEJITS and MapReduce

Michael Driscoll, Evangelos Georganas, Penporn Koanantakool

View

Download (PDF)

Tags: Computer science, CUDA, MapReduce, nVidia, Programming techniques, Python, Tesla M2050

February 9, 2013 by hgpu

Fast 3D Wavelet Transform on Multicore and Manycore Computing Platforms

V. Galiano, O. Lopez-Granado, M.P. Malumbres, H. Migallon

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Image processing, nVidia, nVidia GeForce GTX 280, Optimization, Wavelet

February 9, 2013 by hgpu

Document Stream Clustering using GPUs

Michael J. Szaszy, Hanan Samet

View

Download (PDF)

Tags: Algorithms, Clustering, Computer science, CUDA, Information Retrieval, nVidia, nVidia GeForce GTX 480, Performance

February 9, 2013 by hgpu

Effectiveness of program transformations and compilers for directive-based GPU programming models

Swapnil Avinash Ghike

View

Download (PDF)

Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, Optimization, Performance, Tesla X2090, Thesis

February 9, 2013 by hgpu

Using Hybrid Shared and Distributed Caching for Mixed-Coherency GPU Workloads

Nasser Anssari

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Performance, Thesis

February 9, 2013 by hgpu

Optimized GPU Implementation and Performance Analysis of HC Series of Stream Ciphers

Ayesha Khalid, Deblin Bagchi, Goutam Paul, Anupam Chattopadhyay

View

Download (PDF)

Tags: Block Ciphers, Computer science, CUDA, nVidia, nVidia GeForce GTX 590, Optimization, Security, Stream Ciphers

February 8, 2013 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

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

Agentic Code Optimization via Compiler-LLM Cooperation

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Programming

Seismic Attributes Extraction Based on GPU

Implementing an architecture for efficient network traffic processing on modern graphics hardware

Extending the Computational Application of Reaction-Diffusion Chemistry by Modelling Artificial Neural Networks

Adaptation of the MapReduce programming framework to compute-intensive data-analytics kernels

A multi-lane traffic simulation model via continuous cellular automata

Practical Patient-Specific Cardiac Blood Flow Simulations Using SPH

Enabling Inter-Machine Parallelism in High-Level Languages with SEJITS and MapReduce

Fast 3D Wavelet Transform on Multicore and Manycore Computing Platforms

Document Stream Clustering using GPUs

Effectiveness of program transformations and compilers for directive-based GPU programming models

Using Hybrid Shared and Distributed Caching for Mixed-Coherency GPU Workloads

Optimized GPU Implementation and Performance Analysis of HC Series of Stream Ciphers

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

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

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

Most viewed papers (last 30 days)